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  1. Proceedings of the first international workshop on Location and the web (LOCWEB '08)
  2. Discovering geographical-specific interests from web click data
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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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Discovering geographical-specific interests from web click data

Content Provider ACM Digital Library
Author Sheng, Chang Lee, Mong Li Hsu, Wynne
Abstract As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents that reflect the common interests of the geographical region of the web visitors. In this paper, we define the problem of mining geographical-specific interests patterns. We utilize the quadtree to model the influence distributions of different features, and design an algorithm called Flex-iPROBER to mine geographical-specific interests patterns that are significant in a local region. We further examine how these patterns can change over time and develop an algorithm called MineGIC to efficiently discover pattern changes. Experiment results demonstrate that the proposed algorithms are scalable and efficient. Patterns discovered from real world web click datasets reveal interesting patterns and show the evolution of the interests of people in those regions.
Starting Page 41
Ending Page 48
Page Count 8
File Format PDF
ISBN 9781605581606
DOI 10.1145/1367798.1367805
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-04-22
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Geographic-specific interest pattern Spatio-temporal data Influence model
Content Type Text
Resource Type Article
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