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Word2vec
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#	Item
1	The 30th Annual Conference of the Japanese Society for Artificial Intelligence, 2016 1O2-2 word2vec を用いた発達過程における言語獲得の分析 Analysis of Word Acquisition in Development Process with word Add to Reading List Source URL: kaigi.org - Date: 2016-06-06 06:56:28
2	Joint word2vec Networks for Bilingual Semantic Representations Lior Wolf, Yair Hanani, Kfir Bar, and Nachum Dershowitz Tel Aviv University Abstract. We extend the word2vec framework to capture meaning Add to Reading List Source URL: www.cs.tau.ac.il - Date: 2014-09-22 13:50:34
3	9. KONFERENCA JEZIKOVNE TEHNOLOGIJE Informacijska družba - IS 2014 9th Language Technologies Conference Information Society - IS 2014 Add to Reading List Source URL: nl.ijs.si Language: English - Date: 2014-10-19 11:19:10 Natural language processing Artificial intelligence Artificial neural networks Computational linguistics Machine learning Learning Language modeling Word embedding Word2vec Language model Semantic similarity Latent semantic analysis
4	Linear Algebraic Structure of Word Senses, with Applications to Polysemy arXiv:1601.03764v1 [cs.CL] 14 JanSanjeev Arora Add to Reading List Source URL: arxiv.org Language: English - Date: 2016-01-17 20:31:07 Linguistics Mathematics Lexical semantics Semantics Artificial neural networks Natural language processing Word-sense disambiguation Word embedding Word2vec Sparse approximation Word-sense induction Discourse analysis
5	Decoding Fashion Contexts Using Word Embeddings Sagar Arora Deepak Warrier Myntra Designs, India Add to Reading List Source URL: kddfashion2016.mybluemix.net Language: English - Date: 2016-08-14 10:56:50 Algebra Mathematics Artificial neural networks Vector calculus Vectors Machine learning Word2vec Recommender system Euclidean vector Session Word embedding Style
6	The impact of different data sources on finding and ranking synonyms for a large-scale vocabulary Dialogue 2016 Add to Reading List Source URL: www.dialog-21.ru Language: English - Date: 2016-06-16 07:35:14 Lexicography Linguistics Computational linguistics Machine learning Semantic similarity Statistical distance Dictionary Bilingual dictionary Word2vec
7	Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Machine learning Word2vec Random walk Graph Mathematics Learning Application software
8	Detecting malicious behavior in network and endpoint logs is an extremely challenging task: large and complex data sets, highly dynamic innocuous behavior, and intelligent adversaries contribute to the difficulty. Even a Add to Reading List Source URL: mmds-data.org Language: English - Date: 2016-06-23 15:50:48 Machine learning Word2vec Random walk Graph Mathematics Learning Application software
9	That’s So Annoying!!!: A Lexical and Frame-Semantic Embedding Based Data Augmentation Approach to Automatic Categorization of Annoying Behaviors using #petpeeve Tweets ∗ William Yang Wang and Diyi Yang Language Techn Add to Reading List Source URL: www.emnlp2015.org Language: English - Date: 2015-12-05 04:39:08 Software Computing Linguistics Computational linguistics Artificial neural networks Cognitive science Applied linguistics Semantics Twitter Word2vec Word embedding Machine translation
10	Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning Yulia Tsvetkov♠ Manaal Faruqui♠ Wang Ling♣ Brian MacWhinney♠ Chris Dyer♣♠ ♠ Carnegie Mellon University ♣ G Add to Reading List Source URL: www.aclweb.org Language: English - Date: 2016-08-01 10:37:36 Machine learning Computational linguistics Artificial neural networks Natural language processing Graphical models Word embedding Word-sense disambiguation Word2vec Conditional random field Named-entity recognition Curriculum Support vector machine

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