On the reuse of past optimal queries

Raghavan, Vijay V.; Sever, Hayri

doi:10.1145/215206.215381

Cited by 97 publications

(81 citation statements)

References 11 publications

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“…This method thus tries to detect a user's "interests" through his/her submitted queries and locate similar queries (the query clusters) based on the similarities of the queries in the query logs [5]. The system can then either recommend the similar queries to users (query recommending systems) [5] or use them as expansion term candidates to the original query to augment the quality of the search results (query automatic expansion systems) [10]. Such an approach overcomes the limitation of human involvement and network overloading inherent in online live reference service.…”

Section: Collaborative Searchmentioning

confidence: 99%

“…A recent study on a billion-entry set of queries to AltaVista has shown that more than 85% queries contain less than three terms and the average length of queries is 2.35 [15]. Thus query terms can neither convey much information nor help to detect the semantics behind them since the same term might represent different semantic meanings, while on the other hand, different terms might refer to the same semantic meaning [10].…”

Section: Query Clustering Approachesmentioning

confidence: 99%

“…Raghavan and Sever [10] determine similarity between queries by calculating the overlap in documents returned by the queries. This is done by converting documents into term frequency vectors.…”

Section: Query Clustering Approachesmentioning

confidence: 99%

“…An alternative approach is to use the results (e.g. result URLs in Web search engines) to queries as the criteria to identify similar queries (results-based approach) [5] [10]. However one result might cover different topics, and thus queries with different semantic meanings might lead to the same result.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Collaborative Querying through a Hybrid Query Clustering Approach

Goh

Foo

et al. 2003

Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access

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Abstract.Harnessing previously issued queries to facilitate collaborative querying is an approach that can help users in digital libraries and other information systems better meet their information needs. Here, the kernel step is to identify and cluster similar queries by mining the query logs. However because of the short lengths of queries, it is relatively difficult to cluster queries effectively using on the terms used since they cannot convey enough information. This paper introduces a hybrid method to cluster queries by utilizing both the query terms and the results returned to queries. Experiments show that this method outperforms existing query clustering techniques.

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Section: Collaborative Searchmentioning

confidence: 99%

Section: Query Clustering Approachesmentioning

confidence: 99%

Section: Query Clustering Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Collaborative Querying through a Hybrid Query Clustering Approach

Goh

Foo

et al. 2003

Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access

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“…Raghavan and Sever [65] use a database of past queries that is matched with the current user query. If a significant similarity with a past query is found, the past results associated with the query are proposed to the user.…”

Section: Online Approachesmentioning

confidence: 99%

Personalized Search on the World Wide Web

Micarelli

Gasparetti

Sciarrone

et al.

Lecture Notes in Computer Science

144

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Abstract.With the exponential growth of the available information on the World Wide Web, a traditional search engine, even if based on sophisticated document indexing algorithms, has difficulty meeting efficiency and effectiveness performance demanded by users searching for relevant information. Users surfing the Web in search of resources to satisfy their information needs have less and less time and patience to formulate queries, wait for the results and sift through them. Consequently, it is vital in many applications -for example in an e-commerce Web site or in a scientific one -for the search system to find the right information very quickly. Personalized Web environments that build models of short-term and long-term user needs based on user actions, browsed documents or past queries are playing an increasingly crucial role: they form a winning combination, able to satisfy the user better than unpersonalized search engines based on traditional Information Retrieval (IR) techniques. Several important user personalization approaches and techniques developed for the Web search domain are illustrated in this chapter, along with examples of real systems currently being used on the Internet. IntroductionRecently, several search tools for the Web have been developed to tackle the information overload problem, that is, the over-abundance of resources that prevent the user from retrieving information solely by navigating through the hypertextual space. Some make use of effective personalization, adapting the results according to each user's information needs. This contrasts with traditional search engines that return the same result list for the same query, regardless of who submitted the query, in spite of the fact that different users usually have different needs. In order to incorporate personalization into full-scale Web search tools, we must study the behavior of the users as they interact with information sources.

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On the necessity of term dependence in a query space for weighted retrieval

Bollmann-Sdorra

Raghavan

1998

J. Am. Soc. Inf. Sci.

Self Cite

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In recent years, in the context of the vector space model, the view, held by many researchers, that documents, queries, terms, etc., are all elements of a common space has been challenged (Bollmann‐Sdorra & Raghavan, 1993). In particular, it was noted that term independence has to be investigated in the context of user preferences and it was shown, through counterexamples, that term independence can hold in the document space, but not in the query space and vice versa. In this article, we continue the investigation of query and document spaces with respect to the property of term independence. We prove, under realistic assumptions, that requiring term independence to hold in the query space is inconsistent with the goal of achieving better performance by means of weighted retrieval. The result that term independence in the query space is undesirable is obtained without making any assumption about whether or not the property of term independence holds in the document space. The results of this article reinforce our position that the properties of document and query spaces must be investigated separately, since the document and query spaces do not necessarily have the same properties.

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On the reuse of past optimal queries

Cited by 97 publications

References 11 publications

Collaborative Querying through a Hybrid Query Clustering Approach

Collaborative Querying through a Hybrid Query Clustering Approach

Personalized Search on the World Wide Web

On the necessity of term dependence in a query space for weighted retrieval

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