2011 · 136 citations · 25 references
ComputingComputer ScienceInformation SystemsInformation RetrievalTime Series AnalysisWeb AnalyticsQuery ProcessingRelevance FeedbackRetrieval ModelsSearch Log AnalysisSearch SystemsWeb SearchLog Data AnalysisQuery Log AnalysisRelevance JudgmentsSearch Engine Query LogsSearch Engine User BehaviorSearch Query LogsTemporal Search BehaviorUser Search Behavior
Web search is strongly influenced by time, as queries and the documents they retrieve evolve, with some queries spiking in popularity while others remain stable, and the relevance of documents shifting as user intent changes. This study investigates how queries, their associated documents, and user intent evolve over a 10‑week period. The authors analyze query log data, a daily web crawl, and periodic human relevance judgments to capture these dynamics. They find that specific features of query popularity, coupled with changes in result content, reliably signal shifts in user intent.
Web search is strongly influenced by time. The queries people issue change over time, with some queries occasionally spiking in popularity (e.g., earthquake) and others remaining relatively constant (e.g., youtube). The documents indexed by the search engine also change, with some documents always being about a particular query (e.g., the Wikipedia page on earthquakes is about the query earthquake) and others being about the query only at a particular point in time (e.g., the New York Times is only about earthquakes following a major seismic activity). The relationship between documents and queries can also change as people's intent changes (e.g., people sought different content for the query earthquake before the Haitian earthquake than they did after). In this paper, we explore how queries, their associated documents, and the query intent change over the course of 10 weeks by analyzing query log data, a daily Web crawl, and periodic human relevance judgments. We identify several interesting features by which changes to query popularity can be classified, and show that presence of these features, when accompanied by changes in result content, can be a good indicator of change in query intent.
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