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.
|Title of host publication||Digital Libraries|
|Subtitle of host publication||Providing Quality Information - 17th International Conference on Asia-Pacific Digital Libraries, ICADL 2015, Proceedings|
|Editors||Robert B. Allen, Jane Hunter, Marcia L. Zeng|
|Number of pages||13|
|Publication status||Published - 2015|
|Event||17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015 - Seoul, Korea, Republic of|
Duration: 2015 Dec 9 → 2015 Dec 12
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||17th International Conference on Digital Libraries: Providing Quality Information, ICADL 2015|
|Country||Korea, Republic of|
|Period||15/12/9 → 15/12/12|
Bibliographical noteFunding 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.
© Springer International Publishing Switzerland 2015.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)