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RusNLP: Semantic Search Engine for Russian NLP Conference Papers

  • Irina Nikishina
  • Amir Bakarov
  • Andrey Kutuzov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11179)

Abstract

We present RusNLP, a web service implementing semantic search engine and recommendation system over proceedings of three major Russian NLP conferences (Dialogue, AIST and AINL). The collected corpus spans across 12 years and contains about 400 academic papers in English. The presented web service allows searching for publications semantically similar to arbitrary user queries or to any given paper. Search results can be filtered by authors and their affiliations, conferences or years. They are also interlinked with the NLPub.ru service, making it easier to quickly capture the general focus of each paper. The search engine source code and the publications metadata are freely available for all interested researchers.

In the course of preparing the web service, we evaluated several well-known techniques for representing and comparing documents: TF-IDF, LDA, and Paragraph Vector. On our comparatively small corpus, TF-IDF yielded the best results and thus was chosen as the primary algorithm working under the hood of RusNLP.

Keywords

Information retrieval Semantic similarity Scientific literature search Document representations Academic communities 

Notes

Acknowledgments

We thank numerous VPNs and Tor Project. At the time of finalizing this paper, they were the only ways for Russian-based scholars to collaborate with the colleagues abroad, because of Internet censorship carried by the Russian governmental agency called Roskomnadzor. It accidentally managed to temporarily block a whole bunch of academic resources, including Softconf, Overleaf, etc.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.National Research University Higher School of EconomicsMoscowRussia
  2. 2.University of OsloOsloNorway

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