A taxonomy of web search

By Andrei Z. Broder. SIGF, 2002

2,095 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

View Paper: https://www.semanticscholar.org/paper/c3ab9b6d22989c4004ff4a714c3f31545c7a13ae

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Citations in the corpus

Mining long-term search history to improve search accuracy (2006, background): “Usually, the purposes of recurring queries are navigational rather than informational or transactional [2].”
Understanding user goals in web search (2004, methodology): “From E-Sex to E-Commerce: Web Search Changes.”
Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007, methodology): “TABLE 1. Query types and their corresponding search tasks/target pages (based on Broder, 2002 ), in addition with search tasks and target page types (according to Craswell & Hawking, 2004).”
Query Expansion Techniques for Information Retrieval: a Survey (2017, neutral): “Most web queries fall under the three fundamental categories [49,137] :”
Why we twitter: understanding microblogging usage and communities (2007, background): “According to Broder [5], the three main categories of search queries are navigational, informational and transactional.”
Novelty and diversity in information retrieval evaluation (2008, background): “This intent may correspond to any of the standard Web query types [7]: navigational (seeking a home page), informational (seeking information on power supplies), or transactional (seeking a form to track a package).”
A large-scale evaluation and analysis of personalized search strategies (2007, background): “Contrarily, for the query “Google”, which is a typical navigational query as defined in [3, 17], almost all of the users are consistently selecting results to redirect to Google’s homepage, and therefore none of the personalized strategies could provide significant benefits to users.”
What are you looking for?: an eye-tracking study of information usage in web search (2007, background): “Two or three broad classes of Web search tasks have been identified in the literature [1, 22] and used in various studies on Web search [12, 15, 17].”
Named entity recognition in query (2009, background): “Query classification falls into two groups: (1) classification according to search intent, such as informational, navigational or transactional [7, 21, 16]; (2) classification according to semantics of query, such as “Shopping” or “Living” [24, 1].”
A dynamic bayesian network click model for web search ranking (2009, background): “A query is said to be navigational when the user intent is to reach a particular site [3].”
Web site design with the patron in mind: A step-by-step guide for libraries (2006, neutral): “informational, or transactional [1] .”
A survey of Web clustering engines (2009, background): “However, they can fail in addressing informational queries (in which the user has an information need to satisfy), which account for the majority of Web searches (see Broder [2002] and Rose and Levinson [2004] for a taxonomy of Web queries).”
Query chains: learning to rank from implicit feedback (2005, background): “Thirty six undergraduate student volunteers were instructed to search for the answers to ﬁve navigational and ﬁve informational queries [5].”
A personalized search engine based on Web‐snippet hierarchical clustering (2005, methodology): “This feature turns out to be particularly effective when the users submit informative [5], polysemous, or poor queries.”
Test Collection Based Evaluation of Information Retrieval Systems (2010, background): “Broder pointed out that many web queries were different from the classic information seeking view of search [34].”
Tailoring click models to user goals (2009, background): “On the other hand, the authors were aware of two general categories of query terms in existing literatures [2, 15].”
The perfect search engine is not enough: a study of orienteering behavior in directed search (2004, background): “Even when researchers supplement query log analysis with user surveys [6], these studies are still limited to searches that involve search engines, omitting many search activities (61% of the search activities in the study presented here did not involve keyword search).”