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WebVectors: A Toolkit for Building Web Interfaces for Vector Semantic Models

Part of the Communications in Computer and Information Science book series (CCIS,volume 661)


The paper presents a free and open source toolkit which aim is to quickly deploy web services handling distributed vector models of semantics. It fills in the gap between training such models (many tools are already available for this) and dissemination of the results to general public. Our toolkit, WebVectors, provides all the necessary routines for organizing online access to querying trained models via modern web interface. We also describe two demo installations of the toolkit, featuring several efficient models for English, Russian and Norwegian.


  • Distributional semantics
  • Neural embeddings
  • Word2vec
  • Machine learning
  • Visualization

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  • DOI: 10.1007/978-3-319-52920-2_15
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    As of now, WebVectors supports models in generic Word2vec format (which is essentially a simple list of word vectors, in text or binary form) and gensim format (it is always binary and retains much more technical data, including output vectors).


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Correspondence to Elizaveta Kuzmenko .

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Kutuzov, A., Kuzmenko, E. (2017). WebVectors: A Toolkit for Building Web Interfaces for Vector Semantic Models. In: , et al. Analysis of Images, Social Networks and Texts. AIST 2016. Communications in Computer and Information Science, vol 661. Springer, Cham.

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