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.
Papers published on a yearly basis
Papers
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TL;DR: A product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at improving the usability of the numerous reviews, and develops a probabilistic aspect ranking algorithm to infer the importance of aspects.
Abstract: Numerous consumer reviews of products are now available on the Internet. Consumer reviews contain rich and valuable knowledge for both firms and users. However, the reviews are often disorganized, leading to difficulties in information navigation and knowledge acquisition. This article proposes a product aspect ranking framework, which automatically identifies the important aspects of products from online consumer reviews, aiming at improving the usability of the numerous reviews. The important product aspects are identified based on two observations: 1) the important aspects are usually commented on by a large number of consumers and 2) consumer opinions on the important aspects greatly influence their overall opinions on the product. In particular, given the consumer reviews of a product, we first identify product aspects by a shallow dependency parser and determine consumer opinions on these aspects via a sentiment classifier. We then develop a probabilistic aspect ranking algorithm to infer the importance of aspects by simultaneously considering aspect frequency and the influence of consumer opinions given to each aspect over their overall opinions. The experimental results on a review corpus of 21 popular products in eight domains demonstrate the effectiveness of the proposed approach. Moreover, we apply product aspect ranking to two real-world applications, i.e., document-level sentiment classification and extractive review summarization, and achieve significant performance improvements, which demonstrate the capacity of product aspect ranking in facilitating real-world applications.
126 citations
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TL;DR: A new approach based on the principle of combinatorial optimization with ranking-entropy and the least squares for determining attribute weight is given and a decision making procedure based on combined ranking value is given to select the best alternative(s).
126 citations
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31 Mar 1999TL;DR: In this paper, the authors present a system for performing online data queries, which is a distributed computer system with a plurality of server nodes each fully redundant and capable of processing a user query request.
Abstract: Disclosed is a system for performing online data queries. The system for performing online data queries is a distributed computer system with a plurality of server nodes each fully redundant and capable of processing a user query request. Each server node includes a data query cache and other caches that may be used in performing data queries. The data query, as well as request allocation, is performed in accordance with an adaptive partitioning technique with a bias towards an initial partitioning scheme. Generic objects are created and used to represent business listings upon which the user may perform queries. Various data processing and integration techniques are included which enhance data queries. An update technique is used for synchronizing data updates as needed in updating the plurality of server nodes. A multi-media data transfer technique is used to transfer non-text or multi-media data between various components of the online query tool. Optimizations for searching, such as the common term optimization, are included for those commonly performed data queries. Also disclosed is a system for targeting advertisements that are displayed to a user of the system.
126 citations
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TL;DR: In this article, the reputation of information providers is determined self-consistently and a ranking method based on the reputation is proposed to rank information providers according to the reputation, which is based on a ranking algorithm.
Abstract: With the explosive growth of accessible information, expecially on the Internet, evaluation-based filtering has become a crucial task. Various systems have been devised aiming to sort through large volumes of information and select what is likely to be more relevant. In this letter we analyse a new ranking method, where the reputation of information providers is determined self-consistently.
125 citations
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22 Aug 2001TL;DR: In this paper, a method, system, and computer program product for performing searching that generates improved queries, retrieves meaningful and relevant information, and presents the retrieved information to the user in a useful and comprehensive manner is described.
Abstract: A method, system, and computer program product for performing searching that generates improved queries, retrieves meaningful and relevant information, and presents the retrieved information to the user in a useful and comprehensive manner is described. The method of searching comprises the steps of: receiving from a user a search query requesting information, retrieving at least one recommendation relating to the search query, generating an expanded query based on the received query, performing a search using the expanded query to retrieve documents, and generating themes relating to the retrieved documents. The at least one recommendation relating to the search query is retrieved from a recommendation database. The recommendation database is generated by performing the steps of: performing data mining using users search query logs, user search patterns, and user profile information to generate a plurality of recommendations relating to search query strings, generating a data structure including the recommendations relating to search query strings, and generating a text index based on information in the data structure.
125 citations