Analysis of geographic queries in a search engine log

ABSTRACT

Geography is becoming increasingly important in web search. Search engines can often return better results to users by analyzing features such as user location or geographic terms in web pages and user queries. This is also of great commercial value as it enables location specific advertising and improved search for local businesses. As a result, major search companies have invested significant resources into geographic search technologies, also often called local search.

This paper studies geographic search queries, i.e., text queries such as "hotel new york" that employ geographical terms in an attempt to restrict results to a particular region or location. Our main motivation is to identify opportunities for improving geographical search and related technologies, and we perform an analysis of 36 million queries of the recently released AOL query trace. First, we identify typical properties of geographic search (geo) queries based on a manual examination of several thousand queries. Based on these observations, we build a classifier that separates the trace into geo and non-geo queries. We then investigate the properties of geo queries in more detail, and relate them to web sites and users associated with such queries. We also propose a new taxonomy for geographic search queries.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.1 Content Analysis and Indexing
          Subjects: Indexing methods

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Search process

General Terms:
Human Factors, Measurement

Keywords:
geographic search, local search, query log mining, web search