Sci-Search: Academic Search and Analysis System Based on Keyphrases

  • Svetlana Popova
  • Ivan Khodyrev
  • Artem Egorov
  • Stepan Logvin
  • Sergey Gulyaev
  • Maria Karpova
  • Dmitry Mouromtsev
Part of the Communications in Computer and Information Science book series (CCIS, volume 394)

Abstract

Structured data representation allows saving much time during relevant information search and gives a useful view on a domain. It allows researchers to find relevant publications faster and getting insights about tendencies and dynamics of a particular scientific domain as well as finding emerging topics. Sorted lists of search results provided by the popular search engines are not suitable for such a task. In this paper we demonstrate a demo version of a search engine working with abstracts of scientific articles and providing structured representation of information to the user. Keyphrases are used as the basis for processing algorithms and representation. Some algorithm details are described in the paper. A number of test requests and their results are discussed.

Keywords

Representing search results academic search engine keyphrase extraction clustering indexing informational retrieval 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Li, Q., Bot, R.S., Chen, X.: Incorporating Document Keyphrases. In: The 10th Americas Conference on Information Systems, New York (2004)Google Scholar
  2. 2.
    Gutwina, C., Paynterb, G., Wittenb, I., Nevill-Manningc, C., Frankb, E.: Improving browsing in digital libraries with keyphrase indexes. Journal of Decision Support Systems 27(1-2), 81–104 (1999)CrossRefGoogle Scholar
  3. 3.
    Bernardini, A., Carpineto, C.: Full-Subtopic Retrieval with Keyphrase-Based Search Results Clustering. In: Web Intelligence and Intelligent Agent Technologies (2009)Google Scholar
  4. 4.
    Zhang, D., Dong, Y.: Semantic, hierarchical, online clustering of web search results. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds.) APWeb 2004. LNCS, vol. 3007, pp. 69–78. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Zeng, H.J., He, Q.C., Chen, Z., Ma, W.Y., Ma, J.: Learning to cluster web search results. In: The 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 210–217 (2004)Google Scholar
  6. 6.
    Hulth, A.: Improved automatic keyword extraction given more linguistic knowledge. In: Conference on Empirical Methods in Natural Language Processing, pp. 216–223 (2003)Google Scholar
  7. 7.
    Mihalcea, R., Tarau, P.: TextRank: Bringing order into texts. In: Conference on Empirical Methods in Natural Language Processing, pp. 404–411 (2004)Google Scholar
  8. 8.
    Kim, S.N., Medelyan, O., Yen, M.: Automatic keyphrase extraction from scientific articles. Language Resources and Evaluation, Springer Kan & Timothy Baldwin (2012)Google Scholar
  9. 9.
    Xiaojun, W., Xiao, J.: Exploiting Neighborhood Knowledge for Single Document Summarization and Keyphrase Extraction ACM Transactions on Information Systems 28(2), Article 8 (2010)Google Scholar
  10. 10.
    Zesch, T., Gurevych, I.: Approximate Matching for Evaluating Keyphrase Extraction. In: International Conference RANLP 2009, Borovets, Bulgaria, pp. 484–489 (2009)Google Scholar
  11. 11.
    Popova, S., Khodyrev, I.: Ranking in keyphrase extraction problem: is it useful to use statistics of words occurrences? Proceedings of the Kazan University Journal (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Svetlana Popova
    • 1
    • 2
  • Ivan Khodyrev
    • 3
    • 4
  • Artem Egorov
    • 2
  • Stepan Logvin
    • 2
  • Sergey Gulyaev
    • 2
  • Maria Karpova
    • 2
  • Dmitry Mouromtsev
    • 5
  1. 1.Saint-Petersburg State UniversitySaint-PetersburgRussia
  2. 2.Saint-Petersburg State Polytechnic UniversitySaint-PetersburgRussia
  3. 3.Saint-Petersburg State Electrotechnical UniversitySaint-PetersburgRussia
  4. 4.VISmartSaint-PetersburgRussia
  5. 5.Saint Petersburg National Research University of Information Technologies, Mechanics and OpticsSaint-PetersburgRussia

Personalised recommendations