Apache TinkerPop: Home
Gremlin Query Language Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps.
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ã¯ã˜ã‚ã¾ã—ã¦ã€‚ABEJAã§Researcherをやらã›ã¦ã„ãŸã ã„ã¦ã„る白å·ã§ã™ã€‚ 先日ã€åŒ–åˆç‰©ã®ç‰©æ€§æŽ¨å®šã‚’Deep Learningã‚’ã¤ã‹ã£ã¦å¾“æ¥æ‰‹æ³•ã‚ˆã‚Š300,000å€é«˜é€Ÿã«å‡¦ç†ã™ã‚‹ã¨ã„ã†è«–æ–‡ãŒã§ã¾ã—ãŸï¼ˆ[1], [2]）。ã“ã®è«–æ–‡ã®æ‰‹æ³•ã¯ã€Graph Convolutionã¨ã„ã†ã‚°ãƒ©ãƒ•ä¸Šã«å®šç¾©ã•ã‚ŒãŸConvolution演算ãŒãƒ™ãƒ¼ã‚¹ã¨ãªã£ã¦ã„ã¾ã™ã€‚物性推定ã«é™ã‚‰ãšã€ã‚°ãƒ©ãƒ•è§£æžå…¨èˆ¬ã‚’ Deep Learning ã§ä¸Šæ‰‹ã«ã“ãªã›ã‚‹ã‚ˆã†ã«ãªã‚Œã°ã€Deep Learningã®ã‚¢ãƒ—リケーションã®å¹…ãŒãã£ã¨æ‹¡ãŒã‚Šã€ã•ã‚‰ãªã‚‹ã‚¤ãƒŽãƒ™ãƒ¼ã‚·ãƒ§ãƒ³ãŒèµ·ããã†ãªäºˆæ„ŸãŒã—ã¾ã™ã€‚ ICMLã‚„NIPSãªã©ã®æ©Ÿæ¢°å¦ç¿’ç³»ã®ä¸»è¦å›½éš›ä¼šè°ã§ã‚‚æ•°å¹´å‰ã‹ã‚‰Graph Convolutionã«ã¤ã„ã¦ã®è«–æ–‡ãŒã¡ã‚‰ã»ã‚‰å‡ºç¾ã—ã¯ã˜ã‚ã¦ãŠã‚Šã€ã¨ãã«æœ€è¿‘ãã®å‹¢ã„ãŒå¢—ã—ã¦ãã¦ã„ã‚‹å°è±¡ãŒã‚ã‚Šã¾ã™ã€‚個人的ã«ã‚‚最近（å‰ã‹ã‚‰ï¼Ÿï¼‰ã«ã‚ã‹ã«ã‚°ãƒ©ãƒ•ã¥ã„ã¦ã„
Vizceral Open Source
Previously we wrote about our traffic intuition tool, Flux. We have some announcements and updates to share about this project. First, we have renamed the project to Vizceral. More importantly, Vizceral is now open source! Open SourceVizceral transformed the way we understand and digest information about the state of traffic flowing into the Netflix control plane. We wanted to be able to intuit de
Caveman Graph -- from Wolfram MathWorld
The (connected) caveman graph is a graph arising in social network theory formed by modifying a set of isolated -cliques (or "caves") by removing one edge from each clique and using it to connect to a neighboring clique along a central cycle such that all cliques form a single unbroken loop (Watts 1999). A number of cavemen graphs formed in this manner from are illustrated above. Caveman graphs ar
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極度ã«å¤§ããªã‚°ãƒ©ãƒ•ã®å‡¦ç†ã¯ç¾åœ¨ã§ã‚‚ãªãŠé›£ã—ã„å•é¡Œã 。ã—ã‹ã—最近ã®ãƒ“ッグデータ技術ã®é€²æ©ã¯ï¼Œã“ã®ã‚ˆã†ãªã‚¿ã‚¹ã‚¯ã‚’より実用的ãªã‚‚ã®ã«ã—ã¦ã„ã‚‹ã€‚ãƒ‹ãƒ¥ãƒ¼ãƒ¨ãƒ¼ã‚¯ã‚’æ‹ ç‚¹ã«ã‚¯ãƒã‚¹ãƒ‡ãƒã‚¤ã‚¹ãªã‚³ãƒ³ãƒ†ãƒ³ãƒˆé…信を手掛ã‘ã¦ã„ã‚‹Tapadã¯ãƒ“ッグデータを活用ã—ã¦ï¼Œãƒ†ãƒ©ãƒã‚¤ãƒˆã‚µã‚¤ã‚ºã®ãƒ‡ãƒ¼ã‚¿ã«ã¾ã§æ‹¡å¼µå¯èƒ½ãªã‚°ãƒ©ãƒ•å‡¦ç†ã‚’，ビジãƒã‚¹ãƒ¢ãƒ‡ãƒ«ã®ä¸å¿ƒã¨ã™ã‚‹ã‚¹ã‚¿ãƒ¼ãƒˆã‚¢ãƒƒãƒ—ã 。 Facebookã‚„Twitterãªã©ã‚½ãƒ¼ã‚·ãƒ£ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã«ã¯ï¼Œã‚°ãƒ©ãƒ•è¡¨ç¾ã«é©ã—ãŸãƒ‡ãƒ¼ã‚¿ãŒå«ã¾ã‚Œã¦ã„る。一方ã§ã‚°ãƒ©ãƒ•ã¯ï¼ŒTapadã®ãƒ‡ãƒã‚¤ã‚¹ã‚°ãƒ©ãƒ•ã®ã‚ˆã†ã«ï¼Œã‚‚ã£ã¨ä¸æ˜Žç¢ºãªãƒ‡ãƒ¼ã‚¿ã®è¡¨ç¾ã«ä½¿ç”¨ã™ã‚‹ã“ã¨ã‚‚ã§ãる。Tapadã®å…±åŒå‰µè¨è€…ã§CTOã®Dag Lioddenæ°ã¯ï¼Œãƒ‡ãƒã‚¤ã‚¹ã®è¡¨ç¾æ–¹æ³•ã¨ã—ã¦ã‚°ãƒ©ãƒ•ãŒåˆç†çš„ã§ã‚ã‚‹ç†ç”±ã‚’，次ã®ã‚ˆã†ã«èª¬æ˜Žã™ã‚‹ã€‚ Tapadã§ã¯ãƒ‡ãƒã‚¤ã‚¹é–“ã®é–¢ä¿‚をモデル化ã™ã‚‹ãŸã‚ã«ï¼Œã‚°ãƒ©ãƒ•æŒ‡å‘ã®ã‚¢ãƒ—ãƒãƒ¼ãƒã‚’採用ã—ã¦ã„ã¾ã™ã€‚ã“ã®Device Graph上ã§
Apache TinkerPop: Home
Gremlin Query Language Gremlin is the graph traversal language of Apache TinkerPop. Gremlin is a functional, data-flow language that enables users to succinctly express complex traversals on (or queries of) their application's property graph. Every Gremlin traversal is composed of a sequence of (potentially nested) steps.
New – Store and Process Graph Data using the DynamoDB Storage Backend for Titan | Amazon Web Services
AWS News Blog New – Store and Process Graph Data using the DynamoDB Storage Backend for Titan Graph databases elegantly and efficiently represent entities (generally known as vertices or nodes) and relationships (edges) that connect them. Here’s a very simple example of a graph: Bill and Candace have a daughter named Janet, and she has a son named Bob. This makes Candace Bob’s grandmother, and Bil
Performance Comparison - graph-tool: Efficent network analysis with python
Graph-tool performance comparison This page shows a succinct performance comparison between graph-tool and two other popular graph libraries with Python bindings, igraph and NetworkX. NetworkX is a pure-python implementation, whereas igraph is implemented in C. Here we select a few representative algorithms which are implemented in all three libraries, and test them on the same graph. The graph us
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グラフDBã®Neo4jã‚’1日触ã£ã¦ã¿ãŸ - Wantedly Engineer Blog
ã“ã‚“ã«ã¡ã¯ï¼Wantedlyã§12月ä¸ã«ã‚¤ãƒ³ã‚¿ãƒ¼ãƒ³ã‚·ãƒƒãƒ—ã‚’ã—ã¦ã„ãŸå¾Œè—¤ã§ã™ï¼Ž 今回，æ¥å‹™ã®ä¸€ç’°ã¨ã—ã¦ã‚°ãƒ©ãƒ•DBã§ã‚ã‚‹Neo4jã‚’1日触ã£ã¦ã¿ãŸã®ã§ï¼Œãã‚Œã«é–¢ã—ã¦ã¤ã‚‰ã¤ã‚‰æ›¸ã„ã¦ã¿ãŸã„ã¨æ€ã„ã¾ã™ï¼Ž Neo4jã£ã¦ï¼Ÿ Neo4jã¯ã‚°ãƒ©ãƒ•DB（データã®æ§‹é€ ãŒå…¨ã¦ã‚°ãƒ©ãƒ•æ§‹é€ ã§è¡¨ã•ã‚Œã‚‹DB）ã®1ã¤ã§ã™ï¼Ž Javaã§å®Ÿè£…ã•ã‚Œã¦ãŠã‚Šï¼Œã‚ªãƒ¼ãƒ—ンソースã¨ã—ã¦å…¬é–‹ãƒ»é–‹ç™ºãŒé€²ã‚られã¦ã„ã¾ã™ï¼Ž Neo4jå…¬å¼ ã‚°ãƒ©ãƒ•DBã®ä½ç½®ä»˜ã‘，åŠã³ãã®æ€§è³ªã«é–¢ã—ã¦ã¯æ¬¡ã®è¨˜äº‹ãŒåˆ†ã‹ã‚Šã‚„ã™ã„ã§ã—ょã†ã‹ï¼Ž SQLã‹NoSQLã‹ã¨ã„ã†åˆ†é¡žã ã¨å‹¿è«–NoSQLã«åˆ†é¡žã•ã‚Œã¾ã™ï¼ŽãŒï¼ŒKey-Value型やドã‚ュメント指å‘ã®ã‚‚ã®ã¨ã¯ã¾ãŸç•°ãªã‚Šã¾ã™ï¼Ž InfoQ グラフデータベースã€NOSQLã€Neo4j RDBã‚„Key-Valueåž‹ã®DBãªã©ï¼Œä»–ã®ã‚¿ã‚¤ãƒ—ã®DBã¨ã®æ¯”較ã«ã¤ã„ã¦ã¯å…¬å¼ãƒžãƒ‹ãƒ¥ã‚¢ãƒ«ã«ç°¡å˜ã«ã¾ã¨ã‚られã¦ã„ã¾ã™ï¼Ž 2.2. Compari
SNAP: Stanford Network Analysis Project
We are inviting applications for postdoctoral positions in Network Analytics and Machine Learning. We have no open positions for undergraduate and graduate research assistants at this time, but any applications submitted will be considered for potential openings in the future. SNAP for C++: Stanford Network Analysis Platform Stanford Network Analysis Platform (SNAP) is a general purpose network an
Lowest common ancestor - Wikipedia
In this tree, the lowest common ancestor of the nodes x and y is marked in dark green. Other common ancestors are shown in light green. In graph theory and computer science, the lowest common ancestor (LCA) (also called least common ancestor) of two nodes v and w in a tree or directed acyclic graph (DAG) T is the lowest (i.e. deepest) node that has both v and w as descendants, where we define each
ALENEX'14 ã«è«–文採択 - iwiwiã®æ—¥è¨˜
国際å¦ä¼š ALENEX 2014 ã«è«–æ–‡ãŒæŽ¡æŠžã•ã‚Œã¾ã—ãŸï¼ŽALENEX (Meeting on Algorithm Engineering & Experiments) 㯠SIAM ã«ã‚ˆã£ã¦é–‹å‚¬ã•ã‚Œã‚‹å®Ÿé¨“系アルゴリズム(experimental algorithmics) を扱ã†æœ€ã‚‚有åãªä¼šè°ã® 1 ã¤ã§ï¼Œç†è«–系アルゴリズムã®ãƒˆãƒƒãƒ—å¦ä¼š SODA (Symposium on Discrete Algorithms) ã«ä½µè¨ã—ã¦é–‹å‚¬ã•ã‚Œã¾ã™ï¼Žç™ºè¡¨ã¯æ¥å¹´ã® 1 月ã«ã‚¢ãƒ¡ãƒªã‚«ã®ã‚ªãƒ¬ã‚´ãƒ³ã§ã™ï¼Ž 今回ã®è«–文㯠"Fast Shortest-path Distance Queries on Road Networks by Pruned Highway Labeling" ã¨ã„ã†ã‚¿ã‚¤ãƒˆãƒ«ã§ï¼Œç ”究室ã®å¾Œè¼©ã®æ²³ç”°å›ï¼ŒåŒæœŸã®å²©ç”°ï¼ŒNII ã®æ²³åŽŸæž—先生ã¨ã®å…±è‘—ã§ã™ï¼Žã‚¿ã‚¤ãƒˆãƒ«ã‹ã‚‰ã”察ã—ã®é€šã‚Šï¼ŒSIGMOD'
Small-world network - Wikipedia
A small-world network is a graph characterized by a high clustering coefficient and low distances. On an example of social network, high clustering implies the high probability that two friends of one person are friends themselves. The low distances, on the other hand, mean that there is a short chain of social connections between any two people (this effect is known as six degrees of separation).
Graph Databases, published by O'Reilly Media
O'Reilly Graph Databases The Definitive Book of Graph Databases. Download your FREE copy Discover how graph databases can help you manage and query highly connected data. With this practical book, you’ll learn how to design and implement a graph database that brings the power of graphs to bear on a broad range of problem domains. Whether you want to speed up your response to user queries or build
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GitHub - thinkaurelius/titan: Distributed Graph Database
LCA(Lowest Common Ancestor) - tomiflu's blog
Sigma.js
Graph canonization - Wikipedia)
Cut (graph theory) - Wikipedia
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