Word2vec

Results: 35



#Item
1The 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

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

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Source URL: kaigi.org

- Date: 2016-06-06 06:56:28
    2Joint 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

    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

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    Source URL: www.cs.tau.ac.il

    - Date: 2014-09-22 13:50:34
      39. KONFERENCA JEZIKOVNE TEHNOLOGIJE Informacijska družba - IS 2014 9th Language Technologies Conference Information Society - IS 2014

      9. KONFERENCA JEZIKOVNE TEHNOLOGIJE Informacijska družba - IS 2014 9th Language Technologies Conference Information Society - IS 2014

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      Source URL: nl.ijs.si

      Language: English - Date: 2014-10-19 11:19:10
      4Linear Algebraic Structure of Word Senses, with Applications to Polysemy arXiv:1601.03764v1 [cs.CL] 14 JanSanjeev Arora

      Linear Algebraic Structure of Word Senses, with Applications to Polysemy arXiv:1601.03764v1 [cs.CL] 14 JanSanjeev Arora

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      Source URL: arxiv.org

      Language: English - Date: 2016-01-17 20:31:07
      5Decoding Fashion Contexts Using Word Embeddings Sagar Arora Deepak Warrier  Myntra Designs, India

      Decoding Fashion Contexts Using Word Embeddings Sagar Arora Deepak Warrier Myntra Designs, India

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      Source URL: kddfashion2016.mybluemix.net

      Language: English - Date: 2016-08-14 10:56:50
      6The impact of different data sources on finding and ranking synonyms for a large-scale vocabulary Dialogue 2016

      The impact of different data sources on finding and ranking synonyms for a large-scale vocabulary Dialogue 2016

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      Source URL: www.dialog-21.ru

      Language: English - Date: 2016-06-16 07:35:14
      7Detecting 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

      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

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      Source URL: mmds-data.org

      Language: English - Date: 2016-06-23 15:50:48
      8Detecting 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

      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

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      Source URL: mmds-data.org

      Language: English - Date: 2016-06-23 15:50:48
      9That’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

      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

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      Source URL: www.emnlp2015.org

      Language: English - Date: 2015-12-05 04:39:08
      10Learning 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

      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

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      Source URL: www.aclweb.org

      Language: English - Date: 2016-08-01 10:37:36