A tale of two (similar) cities: Inferring city similarity through geo-spatial query log analysis

KDIR 2011 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval

Volumn , Issue , 2011, Pages 179-189

  Seth, Rohan ^a   Covell, Michele ^a   Ravichandran, Deepak ^a   Sivakumar, D ^a   Baluja, Shumeet ^a  

^a GOOGLE INC   (United States)

Author keywords

Census data; Data mining; Large scale similarity measurement; Log analysis; Query logs; Search engine queries; Spatial data mining

Indexed keywords

CENSUS DATA; LOG ANALYSIS; QUERY LOGS; SCALE SIMILARITY; SPATIAL DATA MINING;

DATA MINING; POPULATION STATISTICS; SEARCH ENGINES;

INFORMATION RETRIEVAL;

EID: 84862162034     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Andrade, L. and Silva, M.J. (2006). "Relevance Ranking for Geographic IR." In Proc. ACM SIGIR Workshop on Geo.Information Retrieval
2. Backstrom, L., Kleinberg, J., Kumar, R., and Novak, J. (2008). "Spatial Variation in Search Engine Queries." In Proc. International Conference on World Wide Web pp. 357-366.
3. Y. Chen, T. Suel, and A. Markowetz (2006). "Efficient Query Processing in Geographic Web Search Engines." In Proc. ACM SIGMOD Int. Conference on Management of Data pp. 277-288.
4. th Annual Bay Area Discrete Mathematics Day. http://math.berkeley.edu/~datta/philtalk.pdf
5. Gan, Q., Attenberg, J., Markowetz, A., and Suel, T. (2008). "Analysis of Geographic Queries in a Search Engine Log." In Proc. ACM International Workshop on Location and the Web pp. 49-56.
6. Harik, G., Shazeer, N. (2004) "Method and Apparatus for Learning a Probabilistic Generative Model for Text," U.S. Patent 7231393.
7. Hassan, A., Jones, R. and Diaz, F. (2009). "A Case Study of using Geographic Cues to Predict Query News Intent." In Proc. ACM SIGSPATIAL International Conference on Advances in Geographic information Systems pp. 33-41.
8. Jansen, B.J., and Spink, A. (2006). "How are We Searching the World Wide Web? A Comparison of Nine Search Engine Transaction Logs." Info. Processing and Management 42 (1): 248-263.
9. Jones, R., Zhang, W.V., Rey, B., Jhala, P., and Stipp, E. (2008a). "Geographic Intention and Modification in Web Search," Int. J. Geographical Information Science. 22 (3): 229-246.
10. Jones, R., Hassan, A., and Diaz, F. (2008b). "Geographic Features in Web Search Retrieval." In Proc. International Workshop on Geographic Information Retrieval (Napa Valley, CA), pp. 57-58.
11. Salton. G. and McGill, M.J. (1983). Introduction to Modern Information Retrieval. McGraw-Hill. ISBN 0070544840.
12. Sanderson, T. and Kohler, J. (2004). "Analyzing Geographic Queries." In Proc. ACM SIGIR Wkshp on Geo. Info. Retrieval
13. Silverstein, C., Marais, H., Henzinger, M., and Moricz, M. (1999). "Analysis of a Very Large Web Search Engine Query Log." SIGIR Forum 33 (1): 6-12.
14. Yi, X., Raghavan, H., and Leggetter, C. (2009). "Discovering Users' Specific Geo Intention in Web Search." In Proc. International Conference on World Wide Web (Madrid, Spain), pp. 481-490.
15. Zhuang, Z., Brunk, C., and Giles, C.L. (2008a). "Modeling and Visualizing Geo-Sensitive Queries based on User Clicks." In Proc. ACM International Workshop on Location and the Web, pp. 73-76.
16. Zhuang, Z., Brunk, C., Mitra, P., and. Giles C.L (2008b). "Towards Click-Based Models of Geographic Interests in Web Search." In Proc. IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology pp. 293-299