KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
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An Efficient Block Index Scheme with Segmentation for Spatio-Textual Similarity Join

  • Xiang, Yiming (College of Computer & Information Engineering, Zhejiang Gongshang University) ;
  • Zhuang, Yi (College of Computer & Information Engineering, Zhejiang Gongshang University) ;
  • Jiang, Nan (Hangzhou First People's Hospital)
  • Received : 2016.09.24
  • Accepted : 2017.03.29
  • Published : 2017.07.31
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Abstract

Given two collections of objects that carry both spatial and textual information in the form of tags, a $\text\underline{S}patio$-$\text\underline{T}extual$-based object $\text\underline{S}imilarity$ $\text\underline{JOIN}$ (ST-SJOIN) retrieves the pairs of objects that are textually similar and spatially close. In this paper, we have proposed a block index-based approach called BIST-JOIN to facilitate the efficient ST-SJOIN processing. In this approach, a dual-feature distance plane (DFDP) is first partitioned into some blocks based on four segmentation schemes, and the ST-SJOIN is then transformed into searching the object pairs falling in some affected blocks in the DFDP. Extensive experiments on real and synthetic datasets demonstrate that our proposed join method outperforms the state-of-the-art solutions.

Keywords

References

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