NDLI: Hybrid index structures for location-based web search

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Hybrid index structures for location-based web search

Content Provider	ACM Digital Library
Author	Ma, Wei-Ying Zhou, Yinghua Xie, Xing Wang, Chuang Gong, Yuchang
Abstract	There is more and more commercial and research interest in location-based web search, i.e. finding web content whose topic is related to a particular place or region. In this type of search, location information should be indexed as well as text information. However, the index of conventional text search engine is set-oriented, while location information is two-dimensional and in Euclidean space. This brings new research problems on how to efficiently represent the location attributes of web pages and how to combine two types of indexes. In this paper, we propose to use a hybrid index structure, which integrates inverted files and R-trees, to handle both textual and location aware queries. Three different combining schemes are studied: (1) inverted file and R-tree double index, (2) first inverted file then R-tree, (3) first R-tree then inverted file. To validate the performance of proposed index structures, we design and implement a complete location-based web search engine which mainly consists of four parts: (1) an extractor which detects geographical scopes of web pages and represents geographical scopes as multiple MBRs based on geographical coordinates; (2) an indexer which builds hybrid index structures to integrate text and location information; (3) a ranker which ranks results by geographical relevance as well as non-geographical relevance; (4) an interface which is friendly for users to input location-based search queries and to obtain geographical and textual relevant results. Experiments on large real-world web dataset show that both the second and the third structures are superior in query time and the second is slightly better than the third. Additionally, indexes based on R*-trees are proven to be more efficient than indexes based on grid structures.
Starting Page	155
Ending Page	162
Page Count	8
File Format	PDF
ISBN	1595931406
DOI	10.1145/1099554.1099584
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-10-31
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Location-based web search Geographical scope Geographical ranking Textual index Spatial index
Content Type	Text
Resource Type	Article

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