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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25 Jul 2004TL;DR: It is shown that query traffic from particular topical categories differs both from the query stream as a whole and from other categories, which is relevant to the development of enhanced query disambiguation, routing, and caching algorithms.
Abstract: We review a query log of hundreds of millions of queries that constitute the total query traffic for an entire week of a general-purpose commercial web search service. Previously, query logs have been studied from a single, cumulative view. In contrast, our analysis shows changes in popularity and uniqueness of topically categorized queries across the hours of the day. We examine query traffic on an hourly basis by matching it against lists of queries that have been topically pre-categorized by human editors. This represents 13% of the query traffic. We show that query traffic from particular topical categories differs both from the query stream as a whole and from other categories. This analysis provides valuable insight for improving retrieval effectiveness and efficiency. It is also relevant to the development of enhanced query disambiguation, routing, and caching algorithms.
338 citations
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TL;DR: The Leiden Ranking is compared with other global university rankings, in particular the Academic Ranking of World Universities (commonly known as the Shanghai Ranking) and the Times Higher Education World University Rankings, and the comparison focuses on the methodological choices underlying the different rankings.
Abstract: The Leiden Ranking 2011/2012 is a ranking of universities based on bibliometric indicators of publication output, citation impact, and scientific collaboration. The ranking includes 500 major universities from 41 different countries. This paper provides an extensive discussion of the Leiden Ranking 2011/2012. The ranking is compared with other global university rankings, in particular the Academic Ranking of World Universities (commonly known as the Shanghai Ranking) and the Times Higher Education World University Rankings. Also, a detailed description is offered of the data collection methodology of the Leiden Ranking 2011/2012 and of the indicators used in the ranking. Various innovations in the Leiden Ranking 2011/2012 are presented. These innovations include (1) an indicator based on counting a university's highly cited publications, (2) indicators based on fractional rather than full counting of collaborative publications, (3) the possibility of excluding non-English language publications, and (4) the use of stability intervals. Finally, some comments are made on the interpretation of the ranking, and a number of limitations of the ranking are pointed out.
338 citations
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TL;DR: A firm can build more effective security strategies by identifying and ranking the severity of potential threats to its IS efforts.
Abstract: A firm can build more effective security strategies by identifying and ranking the severity of potential threats to its IS efforts.
335 citations
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27 Jun 2006TL;DR: This paper proposes several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.
Abstract: Geographic web search engines allow users to constrain and order search results in an intuitive manner by focusing a query on a particular geographic region. Geographic search technology, also called local search, has recently received significant interest from major search engine companies. Academic research in this area has focused primarily on techniques for extracting geographic knowledge from the web. In this paper, we study the problem of efficient query processing in scalable geographic search engines. Query processing is a major bottleneck in standard web search engines, and the main reason for the thousands of machines used by the major engines. Geographic search engine query processing is different in that it requires a combination of text and spatial data processing techniques. We propose several algorithms for efficient query processing in geographic search engines, integrate them into an existing web search query processor, and evaluate them on large sets of real data and query traces.
335 citations
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21 May 1997TL;DR: In this article, a knowledge base search and retrieval system, which includes factual knowledge base queries and concept knowledge base query, is disclosed, which stores associations among terminology/categories that have a lexical, semantical or usage association.
Abstract: A knowledge base search and retrieval system, which includes factual knowledge base queries and concept knowledge base queries, is disclosed. A knowledge base stores associations among terminology/categories that have a lexical, semantical or usage association. Document theme vectors identify the content of documents through themes as well as through classification of the documents in categories that reflects what the documents are primarily about. The factual knowledge base queries identify, in response to an input query, documents relevant to the input query through expansion of the query terms as well as through expansion of themes. The concept knowledge base query does not identify specific documents in response to a query, but specifies terminology that identifies the potential existence of documents in a particular area.
333 citations