Efficient query processing in geographic web search engines

By Yen-Yu Chen, Torsten Suel, Alexander Markowetz. SIGMOD Conference, 2006

381 citations recorded by the source corpus.

Geographic web search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called local search, has recently received significant interest from major search engine companies. Academic research in this area has focused primarily on techniques for extracting geographic knowledge from the web. In this paper, we study the problem of efficient query processing in scalable geographic search engines. Query processing is a major bottleneck in standard web search engines, and the main reason for the thousands of machines used by the major engines. Geographic search engine query processing is different in that it requires a combination of text and spatial data processing techniques. We propose several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.

Subfields: Geography, Planning and Development, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b9ee6f13858589a723025279ec4dd3e738651af6

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In Geography, Planning and Development

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Citations in the corpus

Processing Spatial-Keyword (SK) Queries in Geographic Information Retrieval (GIR) Systems (2007, background): “In a recent work [ 3 ], the authors propose to maintain individual indices for spatial and textual data.”
Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects (2009, result): “Another study [5] addresses a problem similar to that of Zhou et al.”
Collective spatial keyword querying (2011, background): “This development gives prominence to spatial keyword queries [5, 6, 8, 10].”
Spatial Keyword Query Processing: An Experimental Evaluation (2013, methodology): “Similar to SFC-QUAD, the index [5] is not for BkQ and TkQ.”
IR-Tree: An Efficient Index for Geographic Document Search (2011, methodology): “As an example, in [5], the most recent work of Approach I, an inverted file is created to index words of documents and a grid index is created to index locations of documents.”