-
Homogeneous and Heterogeneous Mixture | Chemistry
In this animated lecture, I will teach you about homogeneous mixture and heterogeneous mixture.
#HomogeneousMixture
#HeterogeneousMixture
#Chemistry
Subscribe my channel at:https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Youtube link: https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Facebook link: https://www.facebook.com/Najamacademy/
published: 06 Jun 2020
-
What is Homogeneity?
published: 13 Jan 2022
-
Homogeneous and Heterogeneous Mixtures Examples, Classification of Matter, Chemistry
This chemistry video tutorial explains the difference between homogeneous and heterogeneous mixtures within the subtopic of the classification of matter.
Chemistry - Basic Introduction: https://www.youtube.com/watch?v=-KfG8kH-r3Y
Scientific Notation Review:
https://www.youtube.com/watch?v=ZtB0vJMGve4
Significant Figures Review:
https://www.youtube.com/watch?v=l2yuDvwYq5g
Unit Conversion Problems:
https://www.youtube.com/watch?v=eK8gXP3pImU
Accuracy and Precision:
https://www.youtube.com/watch?v=0IiHPKAvo7g
Density Practice Problems:
https://www.youtube.com/watch?v=9CKDQE35qXQ
__...
published: 06 Aug 2017
-
10 Examples of Homogeneous Mixtures and Heterogeneous Mixtures
In this animated lecture, I will teach you about 10 examples of homogeneous mixtures and 10 examples of heterogeneous mixtures.
Q: What are 10 examples of homogeneous mixtures?
Ans: Following are the 10 different examples of homogeneous mixtures.
1) Salt and water solution
2) Vinegar
3) Alcohol and water
4) Air
5) Sea water
6) Coffee
7) Carbonated drinks
8) Sugar and water solution
9) Orange juice
10) Coins or Steel.
Q: What are 10 examples of heterogeneous mixtures?
Ans: Following are the 10 different examples of heterogeneous mixtures.
1) Sand and water
2) Oil and water
3) Ice cubes in Cola
4) Apple juice with pulp in it
5) Chicken noodle soup
6) Salad
To learn more, watch this lecture til the end.
7) Tomato ketchup
8) Chocolate chips
9) Pizza
10) Sandwich...
published: 14 Oct 2020
-
Introduction to the chi-square test for homogeneity | AP Statistics | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity
Introduction to the chi-square test for homogeneity.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introduc...
published: 17 Apr 2018
-
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 1 | ANY 10
EDIT: Enable subtitle/caption in English to know the answer in number 9.
Can you identify if these ANY 10 mixtures are homogeneous or heterogeneous? Watch to know and comment down your score. Enjoy!
Be sure to subscribe for more ANY 10 videos. Thank you!
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 2 https://www.youtube.com/watch?v=RE2yKPf0PVM
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 3 https://www.youtube.com/watch?v=rA_4LmJN_SU
Science Quiz: Mixture
https://www.youtube.com/watch?v=PDExez3cqEU
#homogeneousmixture #heterogeneousmixture #sciencequiz #science #quizforkids #educationalvideos #ANY10
published: 30 Jul 2020
-
Homogeneity of Variance (part 1)
What is homogeneity of variance and why is it important? I answer these questions. Also, I describe three different types of Levene's tests, two of which are robust to non-normal distributions and unequal sample sizes. Finally, I provide some brief guidelines relevant to how robust the t-test and ANOVA are to violations of the homogeneity of variance assumption.
Here's the link to the video where I demonstrate how to perform the three different levene's tests:
http://www.youtube.com/watch?v=81Yi0cTuwzw
published: 13 Oct 2011
-
Heterogeneous / heterogeneity, homogeneous /homogeneity, statistical test to check it, and example
Hello students,
Welcome to statistics classes in this video we will discuss on concept of homogeneous and heterogeneous.
Please like this video, share it, subscribe my channel and press the bell icon.
published: 04 Jul 2020
-
Basic Concepts of Heterogeneity
This "Basic Concepts of Heterogeneity" Module was created by Enderson Miranda for Oxford University's Center for Evidence-Based Medicine (CEBM). This module is part of the "Using Virtual Learning Environments to Teach Evidence-Based Practice" project, which aims to use an adaptive VLE to teach key EBM concepts.
published: 14 Jan 2018
-
Is it homogeneous or heterogeneous mixture?
when a mixture is homogeneous and when it is heterogeneous?
#homogeneous #heterogeneous #mixture #mixtures #homogenous
salt and water mixture
water and tea mixture
water and ice mixture
published: 14 Oct 2022
5:01
Homogeneous and Heterogeneous Mixture | Chemistry
In this animated lecture, I will teach you about homogeneous mixture and heterogeneous mixture.
#HomogeneousMixture
#HeterogeneousMixture
#Chemistry
Subscrib...
In this animated lecture, I will teach you about homogeneous mixture and heterogeneous mixture.
#HomogeneousMixture
#HeterogeneousMixture
#Chemistry
Subscribe my channel at:https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Youtube link: https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Facebook link: https://www.facebook.com/Najamacademy/
https://wn.com/Homogeneous_And_Heterogeneous_Mixture_|_Chemistry
In this animated lecture, I will teach you about homogeneous mixture and heterogeneous mixture.
#HomogeneousMixture
#HeterogeneousMixture
#Chemistry
Subscribe my channel at:https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Youtube link: https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Facebook link: https://www.facebook.com/Najamacademy/
- published: 06 Jun 2020
- views: 1390873
5:50
Homogeneous and Heterogeneous Mixtures Examples, Classification of Matter, Chemistry
This chemistry video tutorial explains the difference between homogeneous and heterogeneous mixtures within the subtopic of the classification of matter.
Che...
This chemistry video tutorial explains the difference between homogeneous and heterogeneous mixtures within the subtopic of the classification of matter.
Chemistry - Basic Introduction: https://www.youtube.com/watch?v=-KfG8kH-r3Y
Scientific Notation Review:
https://www.youtube.com/watch?v=ZtB0vJMGve4
Significant Figures Review:
https://www.youtube.com/watch?v=l2yuDvwYq5g
Unit Conversion Problems:
https://www.youtube.com/watch?v=eK8gXP3pImU
Accuracy and Precision:
https://www.youtube.com/watch?v=0IiHPKAvo7g
Density Practice Problems:
https://www.youtube.com/watch?v=9CKDQE35qXQ
________________________________
Pure Substances & Mixtures:
https://www.youtube.com/watch?v=OHhnm2p5G3o
Homogeneous & Heterogeneous Mixtures:
https://www.youtube.com/watch?v=eI-tmv4DLEk
Physical and Chemical Changes:
https://www.youtube.com/watch?v=YE2xaMsoGFU
Solids, Liquids, Gases, & Plasma:
https://www.youtube.com/watch?v=9TVOlTolKFA
Physical Vs Chemical Properties:
https://www.youtube.com/watch?v=gH1R87ahFvA
__________________________________
Law of Conservation of Mass:
https://www.youtube.com/watch?v=eBTNzScLUg4
Law of Definite Proportions:
https://www.youtube.com/watch?v=ly0ywRdVG_M
Law of Multiple Proportions:
https://www.youtube.com/watch?v=sxE95VOY-YY
Rutherford's Gold Foil Experiment:
https://www.youtube.com/watch?v=sNQsdrqsD_s
Cathode Ray Tube Experiment:
https://www.youtube.com/watch?v=i6zyPOSreCg
_________________________________
Atoms - Basic Introduction:
https://www.youtube.com/watch?v=acdkMeEKCNQ
Cations and Anions Explained:
https://www.youtube.com/watch?v=aAV2DMAI5f8
Diatomic Elements & Molecules:
https://www.youtube.com/watch?v=gi337Mx7wTc
Elements, Atoms, & Molecules:
https://www.youtube.com/watch?v=pSJeMJaCkVU
Protons, Neutrons, & Electrons:
https://www.youtube.com/watch?v=65dDZulPhtg
_______________________________
Final Exams and Video Playlists:
https://www.video-tutor.net/
Full-Length Videos and Worksheets:
https://www.patreon.com/MathScienceTutor/collections
https://wn.com/Homogeneous_And_Heterogeneous_Mixtures_Examples,_Classification_Of_Matter,_Chemistry
This chemistry video tutorial explains the difference between homogeneous and heterogeneous mixtures within the subtopic of the classification of matter.
Chemistry - Basic Introduction: https://www.youtube.com/watch?v=-KfG8kH-r3Y
Scientific Notation Review:
https://www.youtube.com/watch?v=ZtB0vJMGve4
Significant Figures Review:
https://www.youtube.com/watch?v=l2yuDvwYq5g
Unit Conversion Problems:
https://www.youtube.com/watch?v=eK8gXP3pImU
Accuracy and Precision:
https://www.youtube.com/watch?v=0IiHPKAvo7g
Density Practice Problems:
https://www.youtube.com/watch?v=9CKDQE35qXQ
________________________________
Pure Substances & Mixtures:
https://www.youtube.com/watch?v=OHhnm2p5G3o
Homogeneous & Heterogeneous Mixtures:
https://www.youtube.com/watch?v=eI-tmv4DLEk
Physical and Chemical Changes:
https://www.youtube.com/watch?v=YE2xaMsoGFU
Solids, Liquids, Gases, & Plasma:
https://www.youtube.com/watch?v=9TVOlTolKFA
Physical Vs Chemical Properties:
https://www.youtube.com/watch?v=gH1R87ahFvA
__________________________________
Law of Conservation of Mass:
https://www.youtube.com/watch?v=eBTNzScLUg4
Law of Definite Proportions:
https://www.youtube.com/watch?v=ly0ywRdVG_M
Law of Multiple Proportions:
https://www.youtube.com/watch?v=sxE95VOY-YY
Rutherford's Gold Foil Experiment:
https://www.youtube.com/watch?v=sNQsdrqsD_s
Cathode Ray Tube Experiment:
https://www.youtube.com/watch?v=i6zyPOSreCg
_________________________________
Atoms - Basic Introduction:
https://www.youtube.com/watch?v=acdkMeEKCNQ
Cations and Anions Explained:
https://www.youtube.com/watch?v=aAV2DMAI5f8
Diatomic Elements & Molecules:
https://www.youtube.com/watch?v=gi337Mx7wTc
Elements, Atoms, & Molecules:
https://www.youtube.com/watch?v=pSJeMJaCkVU
Protons, Neutrons, & Electrons:
https://www.youtube.com/watch?v=65dDZulPhtg
_______________________________
Final Exams and Video Playlists:
https://www.video-tutor.net/
Full-Length Videos and Worksheets:
https://www.patreon.com/MathScienceTutor/collections
- published: 06 Aug 2017
- views: 700036
3:41
10 Examples of Homogeneous Mixtures and Heterogeneous Mixtures
In this animated lecture, I will teach you about 10 examples of homogeneous mixtures and 10 examples of heterogeneous mixtures.
Q: What are 10 examples of homo...
In this animated lecture, I will teach you about 10 examples of homogeneous mixtures and 10 examples of heterogeneous mixtures.
Q: What are 10 examples of homogeneous mixtures?
Ans: Following are the 10 different examples of homogeneous mixtures.
1) Salt and water solution
2) Vinegar
3) Alcohol and water
4) Air
5) Sea water
6) Coffee
7) Carbonated drinks
8) Sugar and water solution
9) Orange juice
10) Coins or Steel.
Q: What are 10 examples of heterogeneous mixtures?
Ans: Following are the 10 different examples of heterogeneous mixtures.
1) Sand and water
2) Oil and water
3) Ice cubes in Cola
4) Apple juice with pulp in it
5) Chicken noodle soup
6) Salad
To learn more, watch this lecture til the end.
7) Tomato ketchup
8) Chocolate chips
9) Pizza
10) Sandwich.
To learn more about homogeneous and heterogeneous mixtures, watch this lecture till the end.
#ExamplesOfHomogeneousMixtures
#ExamplesOfHeterogenousMixtures
#10ExamplesofHomogeneousMixtures
#10ExamplesOfHeterogenousMixtures
#HomogenousAndHeterogenousMixtures
#NajamAcademy
Subscribe my channel at:https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Youtube link: https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Facebook link: https://www.facebook.com/Najamacademy/
https://wn.com/10_Examples_Of_Homogeneous_Mixtures_And_Heterogeneous_Mixtures
In this animated lecture, I will teach you about 10 examples of homogeneous mixtures and 10 examples of heterogeneous mixtures.
Q: What are 10 examples of homogeneous mixtures?
Ans: Following are the 10 different examples of homogeneous mixtures.
1) Salt and water solution
2) Vinegar
3) Alcohol and water
4) Air
5) Sea water
6) Coffee
7) Carbonated drinks
8) Sugar and water solution
9) Orange juice
10) Coins or Steel.
Q: What are 10 examples of heterogeneous mixtures?
Ans: Following are the 10 different examples of heterogeneous mixtures.
1) Sand and water
2) Oil and water
3) Ice cubes in Cola
4) Apple juice with pulp in it
5) Chicken noodle soup
6) Salad
To learn more, watch this lecture til the end.
7) Tomato ketchup
8) Chocolate chips
9) Pizza
10) Sandwich.
To learn more about homogeneous and heterogeneous mixtures, watch this lecture till the end.
#ExamplesOfHomogeneousMixtures
#ExamplesOfHeterogenousMixtures
#10ExamplesofHomogeneousMixtures
#10ExamplesOfHeterogenousMixtures
#HomogenousAndHeterogenousMixtures
#NajamAcademy
Subscribe my channel at:https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Youtube link: https://www.youtube.com/channel/UC_ltCdLVMRZ7r3IPzF2Toyg
Facebook link: https://www.facebook.com/Najamacademy/
- published: 14 Oct 2020
- views: 477359
7:56
Introduction to the chi-square test for homogeneity | AP Statistics | Khan Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: Courses on Khan Academy are always 100% free. Start practicing—and ...
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity
Introduction to the chi-square test for homogeneity.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.
Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today!
Donate here: https://www.khanacademy.org/donate?utm_source=youtube&utm_medium=desc
Volunteer here: https://www.khanacademy.org/contribute?utm_source=youtube&utm_medium=desc
https://wn.com/Introduction_To_The_Chi_Square_Test_For_Homogeneity_|_Ap_Statistics_|_Khan_Academy
Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: Courses on Khan Academy are always 100% free. Start practicing—and saving your progress—now: https://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity
Introduction to the chi-square test for homogeneity.
View more lessons or practice this subject at http://www.khanacademy.org/math/ap-statistics/chi-square-tests/chi-square-tests-two-way-tables/v/chi-square-test-homogeneity?utm_source=youtube&utm_medium=desc&utm_campaign=apstatistics
AP Statistics on Khan Academy: Meet one of our writers for AP¨_ Statistics, Jeff. A former high school teacher for 10 years in Kalamazoo, Michigan, Jeff taught Algebra 1, Geometry, Algebra 2, Introductory Statistics, and AP¨_ Statistics. Today he's hard at work creating new exercises and articles for AP¨_ Statistics.
Khan Academy is a nonprofit organization with the mission of providing a free, world-class education for anyone, anywhere. We offer quizzes, questions, instructional videos, and articles on a range of academic subjects, including math, biology, chemistry, physics, history, economics, finance, grammar, preschool learning, and more. We provide teachers with tools and data so they can help their students develop the skills, habits, and mindsets for success in school and beyond. Khan Academy has been translated into dozens of languages, and 15 million people around the globe learn on Khan Academy every month. As a 501(c)(3) nonprofit organization, we would love your help! Donate or volunteer today!
Donate here: https://www.khanacademy.org/donate?utm_source=youtube&utm_medium=desc
Volunteer here: https://www.khanacademy.org/contribute?utm_source=youtube&utm_medium=desc
- published: 17 Apr 2018
- views: 61777
3:22
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 1 | ANY 10
EDIT: Enable subtitle/caption in English to know the answer in number 9.
Can you identify if these ANY 10 mixtures are homogeneous or heterogeneous? Watch to k...
EDIT: Enable subtitle/caption in English to know the answer in number 9.
Can you identify if these ANY 10 mixtures are homogeneous or heterogeneous? Watch to know and comment down your score. Enjoy!
Be sure to subscribe for more ANY 10 videos. Thank you!
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 2 https://www.youtube.com/watch?v=RE2yKPf0PVM
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 3 https://www.youtube.com/watch?v=rA_4LmJN_SU
Science Quiz: Mixture
https://www.youtube.com/watch?v=PDExez3cqEU
#homogeneousmixture #heterogeneousmixture #sciencequiz #science #quizforkids #educationalvideos #ANY10
https://wn.com/Science_Quiz_Homogeneous_Or_Heterogeneous_Mixtures_Part_1_|_Any_10
EDIT: Enable subtitle/caption in English to know the answer in number 9.
Can you identify if these ANY 10 mixtures are homogeneous or heterogeneous? Watch to know and comment down your score. Enjoy!
Be sure to subscribe for more ANY 10 videos. Thank you!
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 2 https://www.youtube.com/watch?v=RE2yKPf0PVM
Science Quiz: Homogeneous or Heterogeneous Mixtures - Part 3 https://www.youtube.com/watch?v=rA_4LmJN_SU
Science Quiz: Mixture
https://www.youtube.com/watch?v=PDExez3cqEU
#homogeneousmixture #heterogeneousmixture #sciencequiz #science #quizforkids #educationalvideos #ANY10
- published: 30 Jul 2020
- views: 94517
5:04
Homogeneity of Variance (part 1)
What is homogeneity of variance and why is it important? I answer these questions. Also, I describe three different types of Levene's tests, two of which are ro...
What is homogeneity of variance and why is it important? I answer these questions. Also, I describe three different types of Levene's tests, two of which are robust to non-normal distributions and unequal sample sizes. Finally, I provide some brief guidelines relevant to how robust the t-test and
ANOVA are to violations of the homogeneity of variance assumption.
Here's the link to the video where I demonstrate how to perform the three different levene's tests:
http://www.youtube.com/watch?v=81Yi0cTuwzw
https://wn.com/Homogeneity_Of_Variance_(Part_1)
What is homogeneity of variance and why is it important? I answer these questions. Also, I describe three different types of Levene's tests, two of which are robust to non-normal distributions and unequal sample sizes. Finally, I provide some brief guidelines relevant to how robust the t-test and
ANOVA are to violations of the homogeneity of variance assumption.
Here's the link to the video where I demonstrate how to perform the three different levene's tests:
http://www.youtube.com/watch?v=81Yi0cTuwzw
- published: 13 Oct 2011
- views: 138683
18:34
Heterogeneous / heterogeneity, homogeneous /homogeneity, statistical test to check it, and example
Hello students,
Welcome to statistics classes in this video we will discuss on concept of homogeneous and heterogeneous.
Please like this video, share it, subsc...
Hello students,
Welcome to statistics classes in this video we will discuss on concept of homogeneous and heterogeneous.
Please like this video, share it, subscribe my channel and press the bell icon.
https://wn.com/Heterogeneous_Heterogeneity,_Homogeneous_Homogeneity,_Statistical_Test_To_Check_It,_And_Example
Hello students,
Welcome to statistics classes in this video we will discuss on concept of homogeneous and heterogeneous.
Please like this video, share it, subscribe my channel and press the bell icon.
- published: 04 Jul 2020
- views: 1921
9:24
Basic Concepts of Heterogeneity
This "Basic Concepts of Heterogeneity" Module was created by Enderson Miranda for Oxford University's Center for Evidence-Based Medicine (CEBM). This module is ...
This "Basic Concepts of Heterogeneity" Module was created by Enderson Miranda for Oxford University's Center for Evidence-Based Medicine (CEBM). This module is part of the "Using Virtual Learning Environments to Teach Evidence-Based Practice" project, which aims to use an adaptive VLE to teach key EBM concepts.
https://wn.com/Basic_Concepts_Of_Heterogeneity
This "Basic Concepts of Heterogeneity" Module was created by Enderson Miranda for Oxford University's Center for Evidence-Based Medicine (CEBM). This module is part of the "Using Virtual Learning Environments to Teach Evidence-Based Practice" project, which aims to use an adaptive VLE to teach key EBM concepts.
- published: 14 Jan 2018
- views: 30674
0:54
Is it homogeneous or heterogeneous mixture?
when a mixture is homogeneous and when it is heterogeneous?
#homogeneous #heterogeneous #mixture #mixtures #homogenous
salt and water mixture
water and tea m...
when a mixture is homogeneous and when it is heterogeneous?
#homogeneous #heterogeneous #mixture #mixtures #homogenous
salt and water mixture
water and tea mixture
water and ice mixture
https://wn.com/Is_It_Homogeneous_Or_Heterogeneous_Mixture
when a mixture is homogeneous and when it is heterogeneous?
#homogeneous #heterogeneous #mixture #mixtures #homogenous
salt and water mixture
water and tea mixture
water and ice mixture
- published: 14 Oct 2022
- views: 6485
-
Name disambiguation in Aminer
Name disambiguation in Aminer
Zhang, Jing; Tang, Jie
Sci China Inf Sci, 2021, 64(4): 144101
Name disambiguation, aiming at disambiguating who is who, is one of the fundamental problems of the online academic network platforms such as Google scholar, microsoft academic and AMiner. This study takes AMiner, a free online academic search and mining system, as the example to explain how we deal with the name ambiguity problem under three different scenarios. AMiner has already extracted 13 million researchers' profiles from the Web and integrated with 20 million papers from heterogeneous publication databases, with a growth rate of over 500000 per month. From the beginning when the system is built to the running and updating phases, we need to pay continuous attention on the problem of name ...
published: 20 Jan 2022
-
Detecting COIs in Heterogeneous Data - Talk by Angelos-Christos Anadiotis (Ecole Polytechnique)
According to the French transparency law, a conflict of interest is any situation where a public interest may interfere with a public or private interest, in such a way that the public interest may be, or appear to be, unduly influenced. Discovering conflicts of interest is a tedious task, as it requires the exploration of several data sources, including both structured and unstructured data, in order to discover connections among entities that could be problematic. Investigative journalism has been actively involved in the pursue of conflicts of interest, and the investigation may take years in order to sort out all the data sources needed and then process the data that they include. This talk addresses the problem of finding connections among entities that belong to heterogeneous data so...
published: 20 Apr 2022
-
What is Transfer Learning? [Explained in 3 minutes]
In this video, we are bringing you a short but effective explanation of what Transfer Learning is and how it works.
By formal definition, “Transfer Learning is the improvement of learning in a new task through the transfer of knowledge from a related task that has already been learned.”
Do you have three minutes to spare? 🤔
Watch the video to find out what this actually means - with two easy-to-understand examples!
#TransferLearning #ML #AI #explained #nocode #automation
__________________________________________
Levity is an AI software that allows you to create custom models to train for image, document, and text classification.
Levity is completely no-code, meaning you don’t need to have any prior knowledge of machine learning or coding algorithms!
Our tool is intended for non...
published: 19 Oct 2022
-
Entity Matching across Heterogeneous Sources
Authors: Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juanzi Li
Abstract:
Given an entity in a source domain, finding its matched entities from another (target) domain is an important task in many applications. Traditionally, the problem was usually addressed by first extracting major keywords corresponding to the source entity and then query relevant entities from the target domain using those keywords. However, the method would inevitably fails if the two domains have less or no overlapping in the content. An extreme case is that the source domain is in English and the target domain is in Chinese.
In this paper, we formalize the problem as entity matching across heterogeneous sources and propose a probabilistic topic model to solve the problem. The model integrates the topic extraction an...
published: 13 Oct 2015
-
OPENED Tool for Managing eBPF Heterogeneity
The recent past has been the emergence of eBPF in building high performance networking use cases such as load balancing, K8s CNI, DDoS protection, traffic shaping etc. However, unlike traditional software datapath technologies, eBPF code development exhibits enormous heterogeneity in terms of choice of kernel hook points, data sharing mechanisms as well as kernel loading tools. Today, these decisions are made at code development time; however, to be truly effective such decision must be made holistically using information about other eBPF programs running on the server.
We argue that the developer of an network function (NF) (consisting of multiple eBPF functions) has no idea of the other NFs that will be chained together at run time to create the datapath. Hence, decisions taken at the d...
published: 30 Dec 2022
-
DomainNet: Homograph Detection for Data Lake Disambiguation
Talk recorded for EDBT 2021
Develops a method to detect homographs (i.e. data values with multiple meanings) in data lakes
Group web page:
https://db.khoury.northeastern.edu
EDBT 2021 paper:
https://northeastern-datalab.github.io/table-as-query/download/EDBT21-DomainNet-Homograph-Detection.pdf
published: 16 Mar 2021
-
Named Entity Disambiguation for Noisy Text - Yotam Eshel
published: 04 Jul 2017
-
Interactive Machine Learning for Heterogeneous Geo-spatial Data - UF Geography Colloquium
Speaker: Dr. Morteza Karimzadeh
Associate Professor, Department of Geography, University of Colorado Boulder
Thursday, February 11, 2021
2:50-3:50 PM (Period 8)
Turlington Hall 3018 and Zoom, livestreamed on YouTube
University of Florida
All are welcome to attend.
Dr. Karimzadeh is a spatial data scientist, with contributions in geographic information retrieval, machine learning, geo-visualization, and visual analytics. His integrative research brings together data science with social/environmental science to inform best practices for a more sustainable and equitable society.
For more information, email Dr. Tim Fik at [email protected]
published: 12 Feb 2021
-
Fighting COVID-19 by Mining Insights from Heterogeneous Datasets Part 1
-The first session, "COVID19-net" was presented by Peter Rose and Ilya Zaslavsky (SDSC, University of California, San Diego) where they demonstrated their open knowledge graph: COVID19-Net and linked heterogeneous COVID-19 data sources.
-The second session, "From Data to Knowledge" was presented by Iris Shen, Principal Data Scientist (Microsoft Academic Team, Microsoft) where Microsoft Academic resources were discussed, and their application to COVID-19 research.
-The third session for, "Distant Reading for Quick Insights" was presented by Natalie Meyers, E-Research Librarian (Navari Center for Digital Scholarship, Hesburgh Library) and Eric Morgan (Hesburgh Library, Notre Dame) where they gave their insights into their use of the US CORD-19 dataset and how simple surveys can yield quick i...
published: 04 May 2020
-
Entity Linking (similarity) at Scale Over Heterogeneous Datasets using Elasticsearch.
Atif Khan's talk at Waterloo-Kitchener Elasticsearch Meetup, Nov. 7, 2018 https://www.meetup.com/Waterloo-Kitchener-Elasticsearch-Meetup/events/255677927/
Disregard the wrong timestamp at video's beginning. It should be November 7 instead of September.
Recorded with Canon SX520 HS superzoom camera, not with SX540 model specified at the end of recording.
published: 18 Dec 2018
2:13
Name disambiguation in Aminer
Name disambiguation in Aminer
Zhang, Jing; Tang, Jie
Sci China Inf Sci, 2021, 64(4): 144101
Name disambiguation, aiming at disambiguating who is who, is one ...
Name disambiguation in Aminer
Zhang, Jing; Tang, Jie
Sci China Inf Sci, 2021, 64(4): 144101
Name disambiguation, aiming at disambiguating who is who, is one of the fundamental problems of the online academic network platforms such as Google scholar, microsoft academic and AMiner. This study takes AMiner, a free online academic search and mining system, as the example to explain how we deal with the name ambiguity problem under three different scenarios. AMiner has already extracted 13 million researchers' profiles from the Web and integrated with 20 million papers from heterogeneous publication databases, with a growth rate of over 500000 per month. From the beginning when the system is built to the running and updating phases, we need to pay continuous attention on the problem of name disambiguation. In the following parts, we discuss the problem on three scenarios during the whole life cycle of AMiner, i.e., name disambiguation when the system is built from scratch (full ND), name disambiguation when persons' profiles are continuously updated (continuous ND) and error detection upon existing persons' profiles (error detection).
https://wn.com/Name_Disambiguation_In_Aminer
Name disambiguation in Aminer
Zhang, Jing; Tang, Jie
Sci China Inf Sci, 2021, 64(4): 144101
Name disambiguation, aiming at disambiguating who is who, is one of the fundamental problems of the online academic network platforms such as Google scholar, microsoft academic and AMiner. This study takes AMiner, a free online academic search and mining system, as the example to explain how we deal with the name ambiguity problem under three different scenarios. AMiner has already extracted 13 million researchers' profiles from the Web and integrated with 20 million papers from heterogeneous publication databases, with a growth rate of over 500000 per month. From the beginning when the system is built to the running and updating phases, we need to pay continuous attention on the problem of name disambiguation. In the following parts, we discuss the problem on three scenarios during the whole life cycle of AMiner, i.e., name disambiguation when the system is built from scratch (full ND), name disambiguation when persons' profiles are continuously updated (continuous ND) and error detection upon existing persons' profiles (error detection).
- published: 20 Jan 2022
- views: 14
52:01
Detecting COIs in Heterogeneous Data - Talk by Angelos-Christos Anadiotis (Ecole Polytechnique)
According to the French transparency law, a conflict of interest is any situation where a public interest may interfere with a public or private interest, in su...
According to the French transparency law, a conflict of interest is any situation where a public interest may interfere with a public or private interest, in such a way that the public interest may be, or appear to be, unduly influenced. Discovering conflicts of interest is a tedious task, as it requires the exploration of several data sources, including both structured and unstructured data, in order to discover connections among entities that could be problematic. Investigative journalism has been actively involved in the pursue of conflicts of interest, and the investigation may take years in order to sort out all the data sources needed and then process the data that they include. This talk addresses the problem of finding connections among entities that belong to heterogeneous data sources, in a scalable manner. It describes an end-to-end pipeline which integrates the heterogeneous data in a graph and then discovers connections among nodes in the graph that correspond to a given set of keywords. The work has been carried out in collaboration with several researchers, most notably: Ioana Manolescu, Oana Balalau, Helena Galhardas, and many others. More details on the project can be found here: https://sourcessay.inria.fr.
https://wn.com/Detecting_Cois_In_Heterogeneous_Data_Talk_By_Angelos_Christos_Anadiotis_(Ecole_Polytechnique)
According to the French transparency law, a conflict of interest is any situation where a public interest may interfere with a public or private interest, in such a way that the public interest may be, or appear to be, unduly influenced. Discovering conflicts of interest is a tedious task, as it requires the exploration of several data sources, including both structured and unstructured data, in order to discover connections among entities that could be problematic. Investigative journalism has been actively involved in the pursue of conflicts of interest, and the investigation may take years in order to sort out all the data sources needed and then process the data that they include. This talk addresses the problem of finding connections among entities that belong to heterogeneous data sources, in a scalable manner. It describes an end-to-end pipeline which integrates the heterogeneous data in a graph and then discovers connections among nodes in the graph that correspond to a given set of keywords. The work has been carried out in collaboration with several researchers, most notably: Ioana Manolescu, Oana Balalau, Helena Galhardas, and many others. More details on the project can be found here: https://sourcessay.inria.fr.
- published: 20 Apr 2022
- views: 81
3:26
What is Transfer Learning? [Explained in 3 minutes]
In this video, we are bringing you a short but effective explanation of what Transfer Learning is and how it works.
By formal definition, “Transfer Learning is...
In this video, we are bringing you a short but effective explanation of what Transfer Learning is and how it works.
By formal definition, “Transfer Learning is the improvement of learning in a new task through the transfer of knowledge from a related task that has already been learned.”
Do you have three minutes to spare? 🤔
Watch the video to find out what this actually means - with two easy-to-understand examples!
#TransferLearning #ML #AI #explained #nocode #automation
__________________________________________
Levity is an AI software that allows you to create custom models to train for image, document, and text classification.
Levity is completely no-code, meaning you don’t need to have any prior knowledge of machine learning or coding algorithms!
Our tool is intended for non-technical process managers who are part of small- and mid-size organizations and banish repetitive and mind-numbing tasks from their workdays entirely.
Give us a follow on socials! We're active almost every day and love chatting to our community members!
👨🏫 JOIN OUR WEEKLY DEMO: https://levity.ai/webinar
👉 SIGN UP FOR LEVITY + tell us about your use case!: https://levity.ai/
🐦 Twitter: https://twitter.com/levityai
📘 Facebook: https://www.facebook.com/levityai
💼 LinkedIn: https://www.linkedin.com/company/levityai
⏩ YouTube: https://www.youtube.com/c/LevityAI
https://wn.com/What_Is_Transfer_Learning_Explained_In_3_Minutes
In this video, we are bringing you a short but effective explanation of what Transfer Learning is and how it works.
By formal definition, “Transfer Learning is the improvement of learning in a new task through the transfer of knowledge from a related task that has already been learned.”
Do you have three minutes to spare? 🤔
Watch the video to find out what this actually means - with two easy-to-understand examples!
#TransferLearning #ML #AI #explained #nocode #automation
__________________________________________
Levity is an AI software that allows you to create custom models to train for image, document, and text classification.
Levity is completely no-code, meaning you don’t need to have any prior knowledge of machine learning or coding algorithms!
Our tool is intended for non-technical process managers who are part of small- and mid-size organizations and banish repetitive and mind-numbing tasks from their workdays entirely.
Give us a follow on socials! We're active almost every day and love chatting to our community members!
👨🏫 JOIN OUR WEEKLY DEMO: https://levity.ai/webinar
👉 SIGN UP FOR LEVITY + tell us about your use case!: https://levity.ai/
🐦 Twitter: https://twitter.com/levityai
📘 Facebook: https://www.facebook.com/levityai
💼 LinkedIn: https://www.linkedin.com/company/levityai
⏩ YouTube: https://www.youtube.com/c/LevityAI
- published: 19 Oct 2022
- views: 37182
13:07
Entity Matching across Heterogeneous Sources
Authors: Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juanzi Li
Abstract:
Given an entity in a source domain, finding its matched entities from another (target) d...
Authors: Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juanzi Li
Abstract:
Given an entity in a source domain, finding its matched entities from another (target) domain is an important task in many applications. Traditionally, the problem was usually addressed by first extracting major keywords corresponding to the source entity and then query relevant entities from the target domain using those keywords. However, the method would inevitably fails if the two domains have less or no overlapping in the content. An extreme case is that the source domain is in English and the target domain is in Chinese.
In this paper, we formalize the problem as entity matching across heterogeneous sources and propose a probabilistic topic model to solve the problem. The model integrates the topic extraction and entity matching, two core subtasks for dealing with the problem, into a unified model. Specifically, for handling the text disjointing problem, we use a cross-sampling process in our model to extract topics with terms coming from all the sources, and leverage existing matching relations through latent topic layers instead of at text layers. Benefit from the proposed model, we can not only find the matched documents for a query entity, but also explain why these documents are related by showing the common topics they share. Our experiments in two real-world applications show that the proposed model can extensively improve the matching performance (+19.8% and +7.1% in two applications respectively) compared with several alternative methods.
ACM DL: http://dl.acm.org/citation.cfm?id=2783353
DOI: http://dx.doi.org/10.1145/2783258.2783353
https://wn.com/Entity_Matching_Across_Heterogeneous_Sources
Authors: Yang Yang, Yizhou Sun, Jie Tang, Bo Ma, Juanzi Li
Abstract:
Given an entity in a source domain, finding its matched entities from another (target) domain is an important task in many applications. Traditionally, the problem was usually addressed by first extracting major keywords corresponding to the source entity and then query relevant entities from the target domain using those keywords. However, the method would inevitably fails if the two domains have less or no overlapping in the content. An extreme case is that the source domain is in English and the target domain is in Chinese.
In this paper, we formalize the problem as entity matching across heterogeneous sources and propose a probabilistic topic model to solve the problem. The model integrates the topic extraction and entity matching, two core subtasks for dealing with the problem, into a unified model. Specifically, for handling the text disjointing problem, we use a cross-sampling process in our model to extract topics with terms coming from all the sources, and leverage existing matching relations through latent topic layers instead of at text layers. Benefit from the proposed model, we can not only find the matched documents for a query entity, but also explain why these documents are related by showing the common topics they share. Our experiments in two real-world applications show that the proposed model can extensively improve the matching performance (+19.8% and +7.1% in two applications respectively) compared with several alternative methods.
ACM DL: http://dl.acm.org/citation.cfm?id=2783353
DOI: http://dx.doi.org/10.1145/2783258.2783353
- published: 13 Oct 2015
- views: 426
33:07
OPENED Tool for Managing eBPF Heterogeneity
The recent past has been the emergence of eBPF in building high performance networking use cases such as load balancing, K8s CNI, DDoS protection, traffic shapi...
The recent past has been the emergence of eBPF in building high performance networking use cases such as load balancing, K8s CNI, DDoS protection, traffic shaping etc. However, unlike traditional software datapath technologies, eBPF code development exhibits enormous heterogeneity in terms of choice of kernel hook points, data sharing mechanisms as well as kernel loading tools. Today, these decisions are made at code development time; however, to be truly effective such decision must be made holistically using information about other eBPF programs running on the server.
We argue that the developer of an network function (NF) (consisting of multiple eBPF functions) has no idea of the other NFs that will be chained together at run time to create the datapath. Hence, decisions taken at the development stage are bound to be suboptimal. A solution for this problem can be taking eBPF specific decisions (such as hook point) at run-time. Unfortunately the process of altering design choices at run time is non-trivial due to two properties of the eBPF runtime. First, porting code written for one hook point to another requires modification in terms of input data structures and available bpf_helper functions. Second, deciding the optimal and most efficient combination eBPF specific decisions (e.g., data structures) requires exploring a large number of design choices.
For example, porting and reusing existing functionalities, say GUE encap/decap processing from Meta's Katran code base, in a new program would require isolating the GUE specific functionalities and their associated control and data dependencies, and modifying them for use in the new program. This process requires complete understanding of the program, is time consuming and typically tends to be error prone.
For more details, see link in the description below.
Status
Our current prototype is able to transform XDP programs to TC compatible programs and we have validated results on a variety of opensource code bases viz. xdp tutorial, Mizar, suricata xdp filter and Meta's Katran. The prototype is written in 425 LoC of C++ code. We currently have seven rules for transforming the TC compatible programs. For the largest program, Katran, our tool took ~500ms. One of the many instances of the user-in-the-loop intervention that we observed while running our tool on Katran was: during the extraction phase, our tool identified many functions defined in multiple files and required the user to determine which to keep (e.g., process_packet).
When: Recorded at LPC 2022
Presented by:
Prof. Theophilus Benson (Brown University)
Dr Palanivel Kodeswaran (IBM Research)
Dr Sayandeep Sen (IBM Research)
More details: https://lpc.events/event/16/contributions/1370/
---
The Linux Plumbers Conference is the premier event for developers working at all levels of the plumbing layer and beyond. https://lpc.events/
https://wn.com/Opened_Tool_For_Managing_Ebpf_Heterogeneity
The recent past has been the emergence of eBPF in building high performance networking use cases such as load balancing, K8s CNI, DDoS protection, traffic shaping etc. However, unlike traditional software datapath technologies, eBPF code development exhibits enormous heterogeneity in terms of choice of kernel hook points, data sharing mechanisms as well as kernel loading tools. Today, these decisions are made at code development time; however, to be truly effective such decision must be made holistically using information about other eBPF programs running on the server.
We argue that the developer of an network function (NF) (consisting of multiple eBPF functions) has no idea of the other NFs that will be chained together at run time to create the datapath. Hence, decisions taken at the development stage are bound to be suboptimal. A solution for this problem can be taking eBPF specific decisions (such as hook point) at run-time. Unfortunately the process of altering design choices at run time is non-trivial due to two properties of the eBPF runtime. First, porting code written for one hook point to another requires modification in terms of input data structures and available bpf_helper functions. Second, deciding the optimal and most efficient combination eBPF specific decisions (e.g., data structures) requires exploring a large number of design choices.
For example, porting and reusing existing functionalities, say GUE encap/decap processing from Meta's Katran code base, in a new program would require isolating the GUE specific functionalities and their associated control and data dependencies, and modifying them for use in the new program. This process requires complete understanding of the program, is time consuming and typically tends to be error prone.
For more details, see link in the description below.
Status
Our current prototype is able to transform XDP programs to TC compatible programs and we have validated results on a variety of opensource code bases viz. xdp tutorial, Mizar, suricata xdp filter and Meta's Katran. The prototype is written in 425 LoC of C++ code. We currently have seven rules for transforming the TC compatible programs. For the largest program, Katran, our tool took ~500ms. One of the many instances of the user-in-the-loop intervention that we observed while running our tool on Katran was: during the extraction phase, our tool identified many functions defined in multiple files and required the user to determine which to keep (e.g., process_packet).
When: Recorded at LPC 2022
Presented by:
Prof. Theophilus Benson (Brown University)
Dr Palanivel Kodeswaran (IBM Research)
Dr Sayandeep Sen (IBM Research)
More details: https://lpc.events/event/16/contributions/1370/
---
The Linux Plumbers Conference is the premier event for developers working at all levels of the plumbing layer and beyond. https://lpc.events/
- published: 30 Dec 2022
- views: 146
10:16
DomainNet: Homograph Detection for Data Lake Disambiguation
Talk recorded for EDBT 2021
Develops a method to detect homographs (i.e. data values with multiple meanings) in data lakes
Group web page:
https://db.khoury.n...
Talk recorded for EDBT 2021
Develops a method to detect homographs (i.e. data values with multiple meanings) in data lakes
Group web page:
https://db.khoury.northeastern.edu
EDBT 2021 paper:
https://northeastern-datalab.github.io/table-as-query/download/EDBT21-DomainNet-Homograph-Detection.pdf
https://wn.com/Domainnet_Homograph_Detection_For_Data_Lake_Disambiguation
Talk recorded for EDBT 2021
Develops a method to detect homographs (i.e. data values with multiple meanings) in data lakes
Group web page:
https://db.khoury.northeastern.edu
EDBT 2021 paper:
https://northeastern-datalab.github.io/table-as-query/download/EDBT21-DomainNet-Homograph-Detection.pdf
- published: 16 Mar 2021
- views: 155
1:08:31
Interactive Machine Learning for Heterogeneous Geo-spatial Data - UF Geography Colloquium
Speaker: Dr. Morteza Karimzadeh
Associate Professor, Department of Geography, University of Colorado Boulder
Thursday, February 11, 2021
2:50-3:50 PM (Period...
Speaker: Dr. Morteza Karimzadeh
Associate Professor, Department of Geography, University of Colorado Boulder
Thursday, February 11, 2021
2:50-3:50 PM (Period 8)
Turlington Hall 3018 and Zoom, livestreamed on YouTube
University of Florida
All are welcome to attend.
Dr. Karimzadeh is a spatial data scientist, with contributions in geographic information retrieval, machine learning, geo-visualization, and visual analytics. His integrative research brings together data science with social/environmental science to inform best practices for a more sustainable and equitable society.
For more information, email Dr. Tim Fik at
[email protected]
https://wn.com/Interactive_Machine_Learning_For_Heterogeneous_Geo_Spatial_Data_Uf_Geography_Colloquium
Speaker: Dr. Morteza Karimzadeh
Associate Professor, Department of Geography, University of Colorado Boulder
Thursday, February 11, 2021
2:50-3:50 PM (Period 8)
Turlington Hall 3018 and Zoom, livestreamed on YouTube
University of Florida
All are welcome to attend.
Dr. Karimzadeh is a spatial data scientist, with contributions in geographic information retrieval, machine learning, geo-visualization, and visual analytics. His integrative research brings together data science with social/environmental science to inform best practices for a more sustainable and equitable society.
For more information, email Dr. Tim Fik at
[email protected]
- published: 12 Feb 2021
- views: 1496
22:15
Fighting COVID-19 by Mining Insights from Heterogeneous Datasets Part 1
-The first session, "COVID19-net" was presented by Peter Rose and Ilya Zaslavsky (SDSC, University of California, San Diego) where they demonstrated their open ...
-The first session, "COVID19-net" was presented by Peter Rose and Ilya Zaslavsky (SDSC, University of California, San Diego) where they demonstrated their open knowledge graph: COVID19-Net and linked heterogeneous COVID-19 data sources.
-The second session, "From Data to Knowledge" was presented by Iris Shen, Principal Data Scientist (Microsoft Academic Team, Microsoft) where Microsoft Academic resources were discussed, and their application to COVID-19 research.
-The third session for, "Distant Reading for Quick Insights" was presented by Natalie Meyers, E-Research Librarian (Navari Center for Digital Scholarship, Hesburgh Library) and Eric Morgan (Hesburgh Library, Notre Dame) where they gave their insights into their use of the US CORD-19 dataset and how simple surveys can yield quick insight into national response trends.
https://wn.com/Fighting_Covid_19_By_Mining_Insights_From_Heterogeneous_Datasets_Part_1
-The first session, "COVID19-net" was presented by Peter Rose and Ilya Zaslavsky (SDSC, University of California, San Diego) where they demonstrated their open knowledge graph: COVID19-Net and linked heterogeneous COVID-19 data sources.
-The second session, "From Data to Knowledge" was presented by Iris Shen, Principal Data Scientist (Microsoft Academic Team, Microsoft) where Microsoft Academic resources were discussed, and their application to COVID-19 research.
-The third session for, "Distant Reading for Quick Insights" was presented by Natalie Meyers, E-Research Librarian (Navari Center for Digital Scholarship, Hesburgh Library) and Eric Morgan (Hesburgh Library, Notre Dame) where they gave their insights into their use of the US CORD-19 dataset and how simple surveys can yield quick insight into national response trends.
- published: 04 May 2020
- views: 8
42:36
Entity Linking (similarity) at Scale Over Heterogeneous Datasets using Elasticsearch.
Atif Khan's talk at Waterloo-Kitchener Elasticsearch Meetup, Nov. 7, 2018 https://www.meetup.com/Waterloo-Kitchener-Elasticsearch-Meetup/events/255677927/
Disr...
Atif Khan's talk at Waterloo-Kitchener Elasticsearch Meetup, Nov. 7, 2018 https://www.meetup.com/Waterloo-Kitchener-Elasticsearch-Meetup/events/255677927/
Disregard the wrong timestamp at video's beginning. It should be November 7 instead of September.
Recorded with Canon SX520 HS superzoom camera, not with SX540 model specified at the end of recording.
https://wn.com/Entity_Linking_(Similarity)_At_Scale_Over_Heterogeneous_Datasets_Using_Elasticsearch.
Atif Khan's talk at Waterloo-Kitchener Elasticsearch Meetup, Nov. 7, 2018 https://www.meetup.com/Waterloo-Kitchener-Elasticsearch-Meetup/events/255677927/
Disregard the wrong timestamp at video's beginning. It should be November 7 instead of September.
Recorded with Canon SX520 HS superzoom camera, not with SX540 model specified at the end of recording.
- published: 18 Dec 2018
- views: 116