Server names may be named by their role or follow a common theme such as colors, countries, cities, planets, chemical element, scientists, etc. If servers are in multiple different geographical locations they may be named by closest airport code.
Such as web-01, web-02, web-03, mail-01, db-01, db-02.
Airport code example:
City-State-Nation example:
Thus, a production server in Minneapolis, Minnesota would be nnn.ps.min.mn.us.example.com, or a development server in Vancouver, BC, would be nnn.ds.van.bc.ca.example.com.
Large networks often use a systematic naming scheme, such as using a location (e.g. a department) plus a purpose to generate a name for a computer.
For example, a web server in NY may be called "nyc-www-04.xyz.net".
汪 is typically romanized identically, despite its distinct tone. It is also Wong in Cantonese, Ong or Ang in Hokkien, Wang (왕) in Korean, and Ō or Oh in Japanese. However, in Vietnamese, it is written Uông.
Distribution
Wáng is one of the most common surnames in the world and was listed by the People's Republic of China's National Citizen ID Information System as the most common surname in mainland China in April 2007, with 92.88 million bearers and comprising 7.25% of the general population. It was the 6th most common surname on Taiwan in 2005, comprising 4.12% of the general population.
Ray is the seventh album by L'Arc-en-Ciel, released on July 1, 1999, simultaneously with Ark. It reached number two on the Oricon chart, behind only Ark, and sold over two million copies, being certified by the RIAJ.
ElixirConf 2021 - Vanessa Lee - And Yet Akin: Name Disambiguation in Elixir
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
published: 23 Oct 2021
A Visual Analytics Approach to Author Name Disambiguation
Title: A Visual Analytics Approach to Author Name Disambiguation
published: 11 Oct 2016
And Yet Akin: Name Disambiguation in Elixir | Vanessa Lee | Code BEAM America 2021
This video was recorded at Code BEAM America 2021 - https://codesync.global/conferences/code-beam-sf-2021/
And Yet Akin: Name Disambiguation in Elixir | Vanessa Lee - Senior Software Engineer at Interfolio
ABSTRACT
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
OBJECTIVES:
To introduce the ...
published: 16 Sep 2022
A Visual Approach for Name Disambiguation in Coauthorship Networks
published: 17 Oct 2018
Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop
Authors:
Yutao Zhang (Tsinghua University); Fanjin Zhang (Tsinghua University); Peiran Yao (Tsinghua University); Jie Tang (Tsinghua University)
More on http://www.kdd.org/kdd2018/
published: 12 Jun 2018
Author Name Disambiguation Top # 6 Facts
Author Name Disambiguation Top # 6 Facts
published: 28 Oct 2015
Technical Track: gambit – An Open Source Name Disambiguation Tool for Version Control Systems
Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score.
Uploaded with Clowdr https://clowdr.org/
published: 01 Jun 2021
DisamBERT: Author name disambiguation based on BERT [SciNLP poster presentation]
Scientific endeavor revolves around scientists. Yet data about scientists are notoriously inaccurate due to the challenging and ubiquitous problem of author name disambiguation. Here, we propose a new disambiguation framework based on BERT, which can automatically select the most useful features for disambiguation and achieved a decent performance. Visit our poster at SciNLP!
published: 30 Sep 2021
Disambiguation – Linking Data Science and Engineering | NLP Summit 2020
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as a...
published: 07 Jan 2021
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 ...
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added ...
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
This video was recorded at Code BEAM America 2021 - https://codesync.global/conferences/code-beam-sf-2021/
And Yet Akin: Name Disambiguation in Elixir | Vanes...
This video was recorded at Code BEAM America 2021 - https://codesync.global/conferences/code-beam-sf-2021/
And Yet Akin: Name Disambiguation in Elixir | Vanessa Lee - Senior Software Engineer at Interfolio
ABSTRACT
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
OBJECTIVES:
To introduce the problem of name disambiguation and string comparison by looking at two existing string comparison libraries before addressing the process of combining them into a single repository. I hope attendees will leave understanding the problem as well as the strengths, limitations, and possibilities of the new library and how it can be used to address the challenges of name disambiguation.
AUDIENCE:
Beginner to intermediate programmers.
• Timecodes
00:00 - 03:54 - Intro
03:55 - 05:14 - String Comparison Algorithms
05:15 - 09:42 - Akin
09:43 - 13:20 - Axon & Training Data: DBLP
13:21 - 18:09 - NX and Axon
18:10 - 19:36 - What's next?
19:36 - 36:43 - QnA
• Follow us on social:
Twitter: https://twitter.com/CodeBEAMio
LinkedIn: https://www.linkedin.com/company/27159258
• Looking for a unique learning experience?
Attend the next Code Sync conference near you!
See what's coming up at: https://codesync.global
• SUBSCRIBE TO OUR CHANNEL
https://www.youtube.com/channel/UC47eUBNO8KBH_V8AfowOWOw
See what's coming up at: https://codesync.global
This video was recorded at Code BEAM America 2021 - https://codesync.global/conferences/code-beam-sf-2021/
And Yet Akin: Name Disambiguation in Elixir | Vanessa Lee - Senior Software Engineer at Interfolio
ABSTRACT
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
OBJECTIVES:
To introduce the problem of name disambiguation and string comparison by looking at two existing string comparison libraries before addressing the process of combining them into a single repository. I hope attendees will leave understanding the problem as well as the strengths, limitations, and possibilities of the new library and how it can be used to address the challenges of name disambiguation.
AUDIENCE:
Beginner to intermediate programmers.
• Timecodes
00:00 - 03:54 - Intro
03:55 - 05:14 - String Comparison Algorithms
05:15 - 09:42 - Akin
09:43 - 13:20 - Axon & Training Data: DBLP
13:21 - 18:09 - NX and Axon
18:10 - 19:36 - What's next?
19:36 - 36:43 - QnA
• Follow us on social:
Twitter: https://twitter.com/CodeBEAMio
LinkedIn: https://www.linkedin.com/company/27159258
• Looking for a unique learning experience?
Attend the next Code Sync conference near you!
See what's coming up at: https://codesync.global
• SUBSCRIBE TO OUR CHANNEL
https://www.youtube.com/channel/UC47eUBNO8KBH_V8AfowOWOw
See what's coming up at: https://codesync.global
Authors:
Yutao Zhang (Tsinghua University); Fanjin Zhang (Tsinghua University); Peiran Yao (Tsinghua University); Jie Tang (Tsinghua University)
More on http:...
Authors:
Yutao Zhang (Tsinghua University); Fanjin Zhang (Tsinghua University); Peiran Yao (Tsinghua University); Jie Tang (Tsinghua University)
More on http://www.kdd.org/kdd2018/
Authors:
Yutao Zhang (Tsinghua University); Fanjin Zhang (Tsinghua University); Peiran Yao (Tsinghua University); Jie Tang (Tsinghua University)
More on http://www.kdd.org/kdd2018/
Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose ga...
Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score.
Uploaded with Clowdr https://clowdr.org/
Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score.
Uploaded with Clowdr https://clowdr.org/
Scientific endeavor revolves around scientists. Yet data about scientists are notoriously inaccurate due to the challenging and ubiquitous problem of author nam...
Scientific endeavor revolves around scientists. Yet data about scientists are notoriously inaccurate due to the challenging and ubiquitous problem of author name disambiguation. Here, we propose a new disambiguation framework based on BERT, which can automatically select the most useful features for disambiguation and achieved a decent performance. Visit our poster at SciNLP!
Scientific endeavor revolves around scientists. Yet data about scientists are notoriously inaccurate due to the challenging and ubiquitous problem of author name disambiguation. Here, we propose a new disambiguation framework based on BERT, which can automatically select the most useful features for disambiguation and achieved a decent performance. Visit our poster at SciNLP!
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021...
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job.
We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity.
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job.
We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity.
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).
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).
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
This video was recorded at Code BEAM America 2021 - https://codesync.global/conferences/code-beam-sf-2021/
And Yet Akin: Name Disambiguation in Elixir | Vanessa Lee - Senior Software Engineer at Interfolio
ABSTRACT
Synonymity and homonymity make name disambiguation difficult. To ease this difficulty, I combined two unmaintained Elixir string comparison libraries and added preprocessing and a double metaphone algorithm. The result is a comprehensive map of scores for pattern identification and machine learning. This talk will address the pre-processing, algorithms, and scoring as well as the strengths and limitations. A live demonstration of scoring will allow us to identify patterns. We end with a discussion of how to gain further benefits from the scores.
OBJECTIVES:
To introduce the problem of name disambiguation and string comparison by looking at two existing string comparison libraries before addressing the process of combining them into a single repository. I hope attendees will leave understanding the problem as well as the strengths, limitations, and possibilities of the new library and how it can be used to address the challenges of name disambiguation.
AUDIENCE:
Beginner to intermediate programmers.
• Timecodes
00:00 - 03:54 - Intro
03:55 - 05:14 - String Comparison Algorithms
05:15 - 09:42 - Akin
09:43 - 13:20 - Axon & Training Data: DBLP
13:21 - 18:09 - NX and Axon
18:10 - 19:36 - What's next?
19:36 - 36:43 - QnA
• Follow us on social:
Twitter: https://twitter.com/CodeBEAMio
LinkedIn: https://www.linkedin.com/company/27159258
• Looking for a unique learning experience?
Attend the next Code Sync conference near you!
See what's coming up at: https://codesync.global
• SUBSCRIBE TO OUR CHANNEL
https://www.youtube.com/channel/UC47eUBNO8KBH_V8AfowOWOw
See what's coming up at: https://codesync.global
Authors:
Yutao Zhang (Tsinghua University); Fanjin Zhang (Tsinghua University); Peiran Yao (Tsinghua University); Jie Tang (Tsinghua University)
More on http://www.kdd.org/kdd2018/
Name disambiguation is a complex but highly relevant challenge whenever analysing real-world user data, such as data from version control systems. We propose gambit, a rule-based disambiguation tool that only relies on name and email information. We evaluate its performance against two commonly used algorithms with similar characteristics, on manually disambiguated ground-truth data from the Gnome GTK project. Our results show that gambit significantly outperforms both algorithms in terms of precision as well as F1 score.
Uploaded with Clowdr https://clowdr.org/
Scientific endeavor revolves around scientists. Yet data about scientists are notoriously inaccurate due to the challenging and ubiquitous problem of author name disambiguation. Here, we propose a new disambiguation framework based on BERT, which can automatically select the most useful features for disambiguation and achieved a decent performance. Visit our poster at SciNLP!
Get your Free Spark NLP and Spark OCR Free Trial: https://www.johnsnowlabs.com/spark-nlp-try-free/
Register for NLP Summit 2021: https://www.nlpsummit.org/2021-events/
Watch all NLP Summit 2020 sessions: https://www.nlpsummit.org/
Disambiguation or Entity Linking is the assignment of a knowledge base identifier (Wikidata, Wikipedia) to a named entity. Our goal was to improve an MVP model by adding newly created knowledge while maintaining competitive F1 scores.
Taking an entity linking model from MVP into production in a spaCy-native pipeline architecture posed several data science and engineering challenges, such as hyperparameter estimation and knowledge enhancement, which we addressed by taking advantage of the engineering tools Docker and Kubernetes to semi-automate training as an on-demand job.
We also discuss some of our learnings and process improvements that were needed to strike a balance between data science goals and engineering constraints and present our current work on improving performance through BERT-embedding based contextual similarity.
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).
But its basis is much older. J. M ... As Mr ... magnificent ... (Barrie offensively referenced them as “Redskins” or of the Piccaninny tribe.) TigerLilly (an expressive RayeZaragoza) and her cohorts are given a specific First Nations tribal identity names ... 5–10.
The Leopards' 3.04-mile home course officially was given a name, the Coach Ray Shriver Cross CountryCourse. Similarly, last winter, the school changed the name of its annual indoor track meet at ...
Is Pitt among them? ... 5 — Election Day ... No ... Kickoff is 7.30 p.m. on ESPN ... 22 SMU (6-1, 3-0) on Nov. 2 ... Neither named Pitt ... 3 seed. Clemson is No. 8 ... 1 ... 2 ... He was named to the watch list for the Ray Guy Award given annually to the nation’s best punter.
The Sonora state prosecutors’ office identified the victim only by his given names, Kevin Ray ...Officials identified him only as José Guadalupe, withholding his family names.
New Mexico punter Aaron Rodriguez was named to the Ray Guy Award preseason watch list on Friday ...Named after former Southern Miss All-American and NFL All-Pro Ray Guy, the award is annually given to the best punter in college football ... kAmp=D@k^Am ... ....
The mention of the name Ray Chan in the credits of Deadpool & Wolverine has left fans with several questions. Chan was given an emotional tribute to the movie’s conclusion, piquing fans’ curiosity about his identity ...RIP Ray Chan.
Shane Ray, who has struggled to find a spot on an NFL roster since 2018, is now being given another opportunity by the Tennessee Titans. Ray’s college career at Missouri was nothing short of spectacular.
Eflin is likely to be the hottest Rays name in trade-deadline rumors during the next two weeks, given his high level of performance and rising salary ... But if the Rays don’t get an outfielder back in a deal, he seems the toughest player to replace.
But MLB sticks to the rule that every team has to be represented, so there will be at least one Ray included when the pitchers and reserves are named late Sunday afternoon ... Some of those Rays names ...
Raye continues her award-winning success over the last year by being named songwriter of the year at the awards, given to the best in British and Irish songwriting and screen composition ... Raye was ...
Berkheimer & Sons — was named ... “[My father] loved painting,” said Ray ... Berkheimer & Sons painting business has given way to BAPS and new businesses, all of the businesses are technically under the umbrella name — still — of R.F.
Pillion is the name given to the secondary padded seat for the passenger behind that of the main motorcycle rider ... But as Colin dives deeper into Ray’s world, he begins to question whether the life of a 24/7 submissive is really for him.
Pillion is the name given to the secondary padded seat for the passenger behind that of the main motorcycle rider ... But as Colin dives deeper into Ray’s world, he begins to question whether the life of a 24/7 submissive is really for him.
Albuquerque Journal
03 Aug 2024
Albuquerque Journal
03 Aug 2024