RusNLP: Semantic Search Engine for Russian NLP Conference Papers

Irina Nikishina, Amir Bakarov, Andrey Kutuzov

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.