• Koznov, D., Pliskin, M.
    Computer-supported collaborative learning with mind-maps
    Communications in Computer and Information Science 17 CCIS, pp. 478-489,
  • Artem Trofimov
    In: Benczúr A. et al. (eds) New Trends in Databases and Information Systems. ADBIS 2018. Communications in Computer and Information Science, vol 909. Springer, Cham,
  • Ulyantsev V., Melnik M.
    Proceedings of International Conference on Algorithms for Computational Biology. - 2015. - 141-153,
  • Igor Kuralenok, Natalia Starikova, Aleksandr Khvorov, and Julian Serdyuk

    The 27th ACM International Conference on Information and Knowledge Management (CIKM ’18), October 22–26, 2018, Torino, Italy. ACM, New York, NY, USA, 10 pages

  • Proceedings of the 2019 miniKanren and Relational Programming Workshop,
  • Rustam Azimov, Semyon Grigorev
    GRADES-NDA '18 Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA),
  • Yuliya Susanina
    Context-free path querying (CFPQ) widely used for graph-structured data analysis in different areas. It is crucial to develop highly efficient algorithms for CFPQ since the size of the input data is typically large. We show how to reduce GFPQ evaluation to solving systems of matrix equations over R --- a problem for which there exist high-performance solutions. Also, we demonstrate the applicability of our approach to real-world data analysis.
    Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data,
  • Arseniy Terekhov, Artyom Khoroshev, Rustam Azimov, Semyon Grigorev

    A recent study showed that the applicability of context-free path querying (CFPQ) algorithms with relational query semantics integrated with graph databases is limited because of low performance and high memory consumption of existing solutions. In this work, we implement a matrix-based CFPQ algorithm by using appropriate high-performance libraries for linear algebra and integrate it with RedisGraph graph database. Also, we introduce a new CFPQ algorithm with single-path query semantics that allows us to extract one found path for each pair of nodes. Finally, we provide the evaluation of our algorithms for both semantics which shows that matrix-based CFPQ implementation for Redis-Graph database is performant enough for real-world data analysis.

    GRADES-NDA'20: Proceedings of the 3rd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA),
  • Semyon Grigorev, Anastasiya Ragozina

    There are several solutions for CFPQ, but how to provide structural representation of query result which is practical for answer processing and debugging is still an open problem. In this paper we propose a graph parsing technique which allows one to build such representation with respect to given grammar in polynomial time and space for arbitrary context-free grammar and graph. Proposed algorithm is based on generalized LL parsing algorithm, while previous solutions are based mostly on CYK or Earley algorithms, which reduces time complexity in some cases.

    Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia (CEE-SECR '17),
  • Valery Isaev
  • I. Sosin, D. Kudenko, A. Shpilman
  • Dmitry Boulytchev, Eugene Vigdorchik
    Workshop on Multiparadigm Programming with Object-Oriented Languages,
  • Daniil Chivilikhin, Igor Buzhinsky, Vladimir Ulyantsev, Andrey Stankevich, Anatoly Shalyto, Valeriy Vyatkin
  • Daniil Chivilikhin, Vladimir Ulyantsev, Anatoly Shalyto, Valeriy Vyatkin

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