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Whether searching, shopping, or socializing, Web users leave behind a great deal of data revealing their information needs, mindset, and approaches used, creating vast opportunities for Web service providers as well as a host of security and privacy concerns for consumers.The Handbook of Research on Web Log Analysis reflects on the multifaceted themes of Web use and presents various approaches to log analysis. This expansive collection reviews the history of Web log analysis and examines new...
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In this research, we investigate a methodology to classify automatically Web queries by topic and user intent. Taking a 20,000 plus Web query data set sectioned by topic, we manually classified each query using a three-level hierarchy of user intent. We note that significant differences in user intent across topics. Results show that user intent (informational, navigational, and transactional) varies by topic (15 to 24 percent depending on the category). We then use this manually classified...
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We analyzed transaction logs containing 51,473 queries posed by 18,113 users of Excite, a major Internet search service. We provide data on: (i) sessions — changes in queries during a session, number of pages viewed, and use of relevance feedback; (ii) queries — the number of search terms, and the use of logic and modifiers; and (iii) terms — their rank/frequency distribution and the most highly used search terms. We then shift the focus of analysis from the query to the user to gain insight...
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Query reformulation is a key user behavior during Web search. Our research goal is to develop predictive models of query reformulation during Web searching. This article reports results from a study in which we automatically classified the query-reformulation patterns for 964,780 Web searching sessions, composed of 1,523,072 queries, to predict the next query reformulation. We employed an n-gram modeling approach to describe the probability of users transitioning from one query-reformulation...
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Discussion of terms and how they are used in queries in information retrieval focuses on a transaction log analysis of queries posed on an Internet search service that isolated basic query structure syntactic patterns. Describes a linguistic model that classified Web queries and suggests implications for information retrieval system design. (Contains 9 references.) (Author/LRW)
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In this paper, we define and present a comprehensive classification of user intent for Web searching. The classification consists of three hierarchical levels of informational, navigational, and transactional intent. After deriving attributes of each, we then developed a software application that automatically classified queries using a Web search engine log of over a million and a half queries submitted by several hundred thousand users. Our findings show that more than 80% of Web queries...
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In this paper, we report ongoing efforts in a large scale research project to develop methods for profiling individual Web search engine users by leveraging data recorded in the transaction logs of search engines. Our research aim is to investigate how completely one can profile a Web searcher using log data. Taking a broad brush approach, we present an array of profiling attributes to illustrate the spectrum of user characteristics possible from log data. Specifically, we present ongoing...
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