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  1. Proceedings of the first international workshop on Location and the web (LOCWEB '08)
  2. Modeling and visualizing geo-sensitive queries based on user clicks
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Location and the Web: (LocWeb 2008)
The locative web
A differential notion of place for local search
Determining geographic representations for arbitrary concepts at query time
Urban web crawling
LocalSavvy: aggregating local points of view about news issues
Discovering geographical-specific interests from web click data
Analysis of geographic queries in a search engine log
Core geographical concepts: case Finnish geo-ontology
Acquisition of a vernacular gazetteer from web sources
Annotating and visualizing location data in geospatial web applications
Computable social patterns from sparse sensor data
Modeling and visualizing geo-sensitive queries based on user clicks
Discovering co-located queries in geographic search logs
Geographic web usage estimation by monitoring DNS caches

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Modeling and visualizing geo-sensitive queries based on user clicks

Content Provider ACM Digital Library
Author Zhuang, Ziming Giles, C. Lee Brunk, Cliff
Abstract The number of search queries that are associated with geographical locations, either explicitly or implicitly, has been quadrupled in recent years. For such geo-sensitive queries, the ability to accurately infer users' geographical preference greatly enhances their search experience. By mining past user clicks and constructing a geographical click probability distribution model, we address two important issues in spatial Web search: how do we determine whether a search query is geo-sensitive, and how do we detect, disambiguate, and visualize the associated geographical location(s). We present our empirical study on a large-scale dataset with about 9,000 unique queries randomly drawn from the logs of a popular commercial search engine Yahoo! Search, and about 430 million user clicks on 1.6M unique Web pages over an eight-month period. Our classification method achieved recall of 0.98 and precision of 0.75 in identifying geo-sensitive search queries. We also present our preliminary findings in using geographical click probability distributions to cluster search results for queries with geographical ambiguities.
Starting Page 73
Ending Page 76
Page Count 4
File Format PDF
ISBN 9781605581606
DOI 10.1145/1367798.1367811
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-04-22
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Geographical query Classification Geo-sensitivity Geographic information retrieval
Content Type Text
Resource Type Article
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