Automatic Reference Tracking with On-Demand Relevance Filtering Based on User’s Interest

  • G. S. Mahalakshmi
  • S. Sendhilkumar
  • P. Karthik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4815)


Automatic tracking of references involves aggregating and synthesizing references through World Wide Web, thereby introducing greater efficiency and granularity to the task of finding publication information. This paper discusses the design and implementation of crawler-based reference tracking system, which has the advantage of online reference filtering. The system automatically analyses the semantic relevance of the reference article by harvesting keywords and their meanings, from title and abstract of the respective article. Indirectly this attempts to improve the performance of the reference database by reducing the articles that are actually being downloaded thereby improving the performance of the system. The number of levels for recursive downloads of reference articles are specified by the user. According to user’s interest the system tracks up the references required for the understanding of the seed article, stores them in the databases and projects the information by threshold based view filtering.


Clustering Information filtering Internet search Relevance feedback Retrieval models Reference tracking Citations 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • G. S. Mahalakshmi
    • 1
  • S. Sendhilkumar
    • 1
  • P. Karthik
    • 1
  1. 1.Department of Computer Science and Engineering, Anna University, Chennai, TamilnaduIndia

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