Exploring context-sensitive Query Reformulation in a biomedical digital library

Erin Hea Jin Kim, Jung Sun Oh, Min Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


We propose a novel semantic query expansion technique that enables inference of contextual information in queries and user information. In the present study, we detect and map bio entities such as gene, protein, and disease in a query to concept tuples, and incorporate user context data based on the PubMed query logs and user profile into the algorithm. In objective evaluation, we can see a concept tuple aided with UMLS concepts adds semantic information to the initial query. In subjective evaluation, we find that in a context enabled search environment, where context terms that the users are interested in are combined into their initial search terms, users tend to assign higher relevance scores to the retrieval results by these queries.

Original languageEnglish
Title of host publicationDigital Libraries
Subtitle of host publicationProviding Quality Information - 17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Proceedings
EditorsRobert B. Allen, Jane Hunter, Marcia L. Zeng
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319279732
Publication statusPublished - 2015
Event17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015 - Seoul, Korea, Republic of
Duration: 2015 Dec 92015 Dec 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015
Country/TerritoryKorea, Republic of

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2012S1A3A2033291) and (in part) by the Yonsei University Future-leading Research Initiative of 2015.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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