Topic
Ranking (information retrieval)
About: Ranking (information retrieval) is a research topic. Over the lifetime, 21109 publications have been published within this topic receiving 435130 citations.
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122 citations
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TL;DR: It is argued that ranking cultures are embedded in the meshes of mutually constitutive agencies that frustrate the authors' attempts at causal explanation and are better served by strategies of ‘descriptive assemblage’.
Abstract: Algorithms, as constitutive elements of online platforms, are increasingly shaping everyday sociability. Developing suitable empirical approaches to render them accountable and to study their socia...
122 citations
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19 Aug 2011TL;DR: In this article, a search service provides query suggestions responsive to a query suggestion request from a client device, and determines if a prediction criterion is met, in response to which the search system provides search results to the client device.
Abstract: Methods, systems, and apparatus, including computer program products, for processing search query suggestions. In one aspect, a search service provides query suggestions responsive to a query suggestion request from a client device, and determines if a prediction criterion is met. The prediction criterion is independent of a user selection of a query suggestion provided in response to one or more query suggestion requests. In response to determining that the prediction criterion is met, the search system provides search results to the client device. The search results are responsive to one of the query suggestions provided in response to the query suggestion request or one or more previous query suggestion requests.
121 citations
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19 Jul 2009TL;DR: This research automatically creates query suggestions using term relevance feedback techniques to help users formulate queries, and shows that subjects used more query suggestions than term suggestions and saved more documents with these suggestions, even though there were no significant differences in performance.
Abstract: Query formulation is one of the most difficult and important aspects of information seeking and retrieval. Two techniques, term relevance feedback and query suggestion, provide methods to help users formulate queries, but each is limited in different ways. In this research we combine these two techniques by automatically creating query suggestions using term relevance feedback techniques. To evaluate our approach, we conducted an interactive information retrieval study with 55 subjects and 20 topics. Each subject completed four topics, half with a term suggestion system and half with a query suggestion system. We also investigated the source of the suggestions: approximately half of all subjects were provided with system-generated suggestions, while half were provided with user-generated suggestions. Results show that subjects used more query suggestions than term suggestions and saved more documents with these suggestions, even though there were no significant differences in performance. Subjects preferred the query suggestion system and rated it higher along a number of dimensions including its ability to help them think of new approaches to searching. Qualitative data provided insight into subjects' usage and ratings, and indicated that subjects often used the suggestions even when they did not click on them.
121 citations
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12 Sep 1997
TL;DR: In this article, a method of selecting the likely most relevant database collections for document searching based on an ad hoc query where each of the databases includes a plurality of documents is presented.
Abstract: A method of selecting the likely most relevant database collections for document searching based on an ad hoc query where each of the databases includes a plurality of documents. Iterative collection selection processing of the databases is performed to obtain consistent relative-ranking collection selection results for each iteration. The method uses a collection selection query and performs the repetitive steps of determining an inverse collection frequency and a document frequency for each database; determining a ranking value for each database; selecting a subset of the set of databases based on predetermined criteria dependant on the ranking value for each the database. The method provides for automated and manual descriptions, boolean selection terms combined with soft terms, and uses term proximity, capitalization, phraseology and other information in establishing a relevance ranking of the collections with respect to the ad hoc query.
121 citations