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A Proportionality-based Approach to Search Result Diversification

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Release : 2014
Genre : Database searching
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis A Proportionality-based Approach to Search Result Diversification by : Van B. Dang

Download or read book A Proportionality-based Approach to Search Result Diversification written by Van B. Dang. This book was released on 2014. Available in PDF, EPUB and Kindle. Book excerpt: Search result diversification addresses the problem of queries with unclear information needs. The aim of using diversification techniques is to find a ranking of documents that covers multiple possible interpretations, aspects, or topics for a given query. By explicitly providing diversity in search results, this approach can increase the likelihood that users will find documents relevant to their specific intent, thereby improving effectiveness. This dissertation introduces a new perspective on diversity: diversity by proportionality. We consider a result list more diverse, with respect to some set of topics related to the query, when the ratio between the number of relevant documents it provides for each of these topics matches more closely with the topic popularity distribution. Consequently, we derive an effectiveness measure based on proportionality and propose a new framework for optimizing proportionality in search results, which we show to be more effective than existing techniques. Diversification would be impractical without the ability to automatically infer the set of topics associated with the user queries. Therefore, we study cluster-based techniques for generating these topics from publicly available data sources. Based on the challenges that we observe with topic generation, we present a simplified term-based representation for query topics. Specifically, we propose to identify for each query a single set of terms that describes its topics. This set is provided to a diversification technique which in effect treats each of the terms as a topic to determine coverage in the search results. We call this approach term level diversification and we show that it can promote diversity with respect to the topics underlying the input terms. This simplifies the task of finding a set of query topics, which has proven difficult, to finding only a set of terms. We also present a technique as well as several data sources for generating these terms effectively.

Search Result Diversification

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Author :
Release : 2015-02-27
Genre : Computers
Kind : eBook
Book Rating : 002/5 ( reviews)

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Book Synopsis Search Result Diversification by : Santos Rodrygo L T

Download or read book Search Result Diversification written by Santos Rodrygo L T. This book was released on 2015-02-27. Available in PDF, EPUB and Kindle. Book excerpt: This primer reviews the published literature on search result diversification. In particular, it discusses the motivations for diversifying the search results for an ambiguous query and provides a formal definition of the search result diversification problem. In addition, it describes the most successful approaches in the literature for producing and evaluating diversity in multiple search domains.

Database Systems for Advanced Applications

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Release : 2018-05-11
Genre : Computers
Kind : eBook
Book Rating : 588/5 ( reviews)

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Book Synopsis Database Systems for Advanced Applications by : Jian Pei

Download or read book Database Systems for Advanced Applications written by Jian Pei. This book was released on 2018-05-11. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 10827 and LNCS 10828 constitutes the refereed proceedings of the 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018, held in Gold Coast, QLD, Australia, in May 2018. The 83 full papers, 21 short papers, 6 industry papers, and 8 demo papers were carefully selected from a total of 360 submissions. The papers are organized around the following topics: network embedding; recommendation; graph and network processing; social network analytics; sequence and temporal data processing; trajectory and streaming data; RDF and knowledge graphs; text and data mining; medical data mining; security and privacy; search and information retrieval; query processing and optimizations; data quality and crowdsourcing; learning models; multimedia data processing; and distributed computing.

Graph Structures for Knowledge Representation and Reasoning

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Release : 2016-01-02
Genre : Computers
Kind : eBook
Book Rating : 028/5 ( reviews)

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Book Synopsis Graph Structures for Knowledge Representation and Reasoning by : Madalina Croitoru

Download or read book Graph Structures for Knowledge Representation and Reasoning written by Madalina Croitoru. This book was released on 2016-01-02. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Graph Structures for Knowledge Representation and Reasoning, GKR 2015, held in Buenos Aires, Argentina, in July 2015, associated with IJCAI 2015, the 24th International Joint Conference on Artificial Intelligence. The 9 revised full papers presented were carefully reviewed and selected from 10 submissions. The papers feature current research involved in the development and application of graph-based knowledge representation formalisms and reasoning techniques. They address the following topics: argumentation; conceptual graphs; RDF; and representations of constraint satisfaction problems.

Advances in Information Retrieval

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Release : 2020-04-10
Genre : Computers
Kind : eBook
Book Rating : 428/5 ( reviews)

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Book Synopsis Advances in Information Retrieval by : Joemon M. Jose

Download or read book Advances in Information Retrieval written by Joemon M. Jose. This book was released on 2020-04-10. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set LNCS 12035 and 12036 constitutes the refereed proceedings of the 42nd European Conference on IR Research, ECIR 2020, held in Lisbon, Portugal, in April 2020.* The 55 full papers presented together with 8 reproducibility papers, 46 short papers, 10 demonstration papers, 12 invited CLEF papers, 7 doctoral consortium papers, 4 workshop papers, and 3 tutorials were carefully reviewed and selected from 457 submissions. They were organized in topical sections named: Part I: deep learning I; entities; evaluation; recommendation; information extraction; deep learning II; retrieval; multimedia; deep learning III; queries; IR – general; question answering, prediction, and bias; and deep learning IV. Part II: reproducibility papers; short papers; demonstration papers; CLEF organizers lab track; doctoral consortium papers; workshops; and tutorials. *Due to the COVID-19 pandemic, this conference was held virtually.

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