Spatio-temporal pseudo relevance feedback for scientific data retrieval

Shin'ichi Takeuchi, Komei Sugiura, Yuhei Akahoshi, Koji Zettsu

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


We consider the problem of searching scientific data from vast heterogeneous scientific data repositories. This problem is challenging because scientific data contain relatively little text information compared to other search targets such as web pages. On the other hand, the metadata in scientific data contain other characteristic information such as spatio-temporal information. Although using this information make it possible to improve the search performance, many widely adopted scientific data search engines use this information exclusively for narrowing down search results. In this paper, we propose a novel query generation method using spatial, temporal, and text information based on pseudo relevance feedback. The proposed method generates new spatio-temporal queries from the initial search results. By using these queries, the search results are reranked such that more related results obtain higher rank. The experimental results show that the proposed method outperforms a baseline method when search targets do not have rich text information.

Original languageEnglish
Pages (from-to)124-131
Number of pages8
JournalIEEJ Transactions on Electrical and Electronic Engineering
Issue number1
Publication statusPublished - 2017 Jan 1
Externally publishedYes


  • Pseudo relevance feedback
  • information retrieval
  • query generation
  • scientific data
  • spatio-temporal and text information

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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