An Efficient Block Index Scheme with Segmentation for Spatio-Textual Similarity Join

Given two collections of objects that carry both spatial and textual information in the form of tags, a Spatio-Textual-based object Similarity 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 c...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:KSII transactions on Internet and information systems 2017, 11(7), , pp.3578-3593
Hauptverfasser: Xiang, Yiming, Zhuang, Yi, Jiang, Nan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Given two collections of objects that carry both spatial and textual information in the form of tags, a Spatio-Textual-based object Similarity 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. KCI Citation Count: 0
ISSN:1976-7277
1976-7277
DOI:10.3837/tiis.2017.07.015