Search results for "Concept search"

showing 6 items of 6 documents

Visual Re-Ranking for Multi-Aspect Information Retrieval

2017

We present visual re-ranking, an interactive visualization technique for multi-aspect information retrieval. In multi-aspect search, the information need of the user consists of more than one aspect or query simultaneously. While visualization and interactive search user interface techniques for improving user interpretation of search results have been proposed, the current research lacks understanding on how useful these are for the user: whether they lead to quantifiable benefits in perceiving the result space and allow faster, and more precise retrieval. Our technique visualizes relevance and document density on a two-dimensional map with respect to the query phrases. Pointing to a locat…

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniWeb search queryConcept searchInformation retrievalSettore INF/01 - Informaticamulti-aspect searchComputer scienceinformation retrieval information visualization multi-aspect search multi-dimensional rankingInformationSystems_INFORMATIONSTORAGEANDRETRIEVALeducation020207 software engineeringta613202 engineering and technology113 Computer and information sciencesQuery expansionmulti-dimensional rankingWeb query classification020204 information systemsHuman–computer information retrieval0202 electrical engineering electronic engineering information engineeringRelevance (information retrieval)Visual Wordinformation visualizationinformation retrievalDocument retrieval
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A Novel Approach to Improve the Accuracy of Web Retrieval

2010

General purpose search engines utilize a very simple view on text documents: They consider them as bags of words. It results that after indexing, the semantics of documents is lost. In this paper, we introduce a novel approach to improve the accuracy of Web retrieval. We utilize the WordNet and WordNet SenseRelate All Words Software as main tools to preserve the semantics of the sentences of documents and user queries. Nouns and verbs in the WordNet are organized in the tree hierarchies. The word meanings are presented by numbers that reference to the nodes on the semantic tree. The meaning of each word in the sentence is calculated when the sentence is analyzed. The goal is to put each nou…

Information retrievalConcept searchComputer sciencebusiness.industryInformationSystems_INFORMATIONSTORAGEANDRETRIEVALSearch engine indexingWord processingWordNetcomputer.software_genreSemanticsComputingMethodologies_ARTIFICIALINTELLIGENCETree (data structure)NounComputingMethodologies_DOCUMENTANDTEXTPROCESSINGArtificial intelligencebusinesscomputerNatural language processingSentence2010 5th International Conference on Future Information Technology
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Extracting Semantic Knowledge from Unstructured Text Using Embedded Controlled Language

2016

Nowadays, most of the data on the Web is still in the form of unstructured text. Knowledge extraction from unstructured text is highly desirable but extremely challenging due to the inherent ambiguity of natural language. In this article, we present an architecture of an information extraction system based on the concept of Embedded Controlled Language that allows for extracting formal semantic knowledge from an unstructured text corpus. Moreover, the presented approach has a potential to support multilingual input and output.

Information retrievalConcept searchNoisy text analyticsbusiness.industryComputer scienceText simplification010401 analytical chemistryText graph02 engineering and technologycomputer.software_genre01 natural scienceslanguage.human_language0104 chemical sciencesInformation extractionControlled natural languageKnowledge extractionExplicit semantic analysis0202 electrical engineering electronic engineering information engineeringlanguage020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerNatural language processing2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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Learning to Rank Images for Complex Queries in Concept-based Search

2018

Concept-based image search is an emerging search paradigm that utilizes a set of concepts as intermediate semantic descriptors of images to bridge the semantic gap. Typically, a user query is rather complex and cannot be well described using a single concept. However, it is less effective to tackle such complex queries by simply aggregating the individual search results for the constituent concepts. In this paper, we propose to introduce the learning to rank techniques to concept-based image search for complex queries. With freely available social tagged images, we first build concept detectors by jointly leveraging the heterogeneous visual features. Then, to formulate the image relevance, …

Theoretical computer scienceCognitive Neuroscience02 engineering and technologyfactorization machineRanking (information retrieval)Set (abstract data type)Artificial Intelligence020204 information systems0202 electrical engineering electronic engineering information engineeringRelevance (information retrieval)tiedonhakukuvatMathematicslearning to rankta113InternetConcept searchRank (computer programming)kuvahakuComputer Science Applicationscomplex query020201 artificial intelligence & image processingLearning to rankPairwise comparisonconcept-based image searchSemantic gapNeurocomputing
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Semantic retrieval: an approach to representing, searching and summarising text documents

2011

Nowadays, the internet is the major source of information for millions of people. There are many search tools available on the net but finding appropriate text information is still difficult. The retrieval efficiency of the presently used systems cannot be significantly improved: ‘bag of words’ interpretation causes losing semantics of texts. We applied the functional approach to represent English text documents. It allows taking into account semantic relations between words when indexing documents and use ordinary English sentences as queries to a search engine. The proposed retrieval mechanisms return only highly relevant documents. They make it possible to generate content-aware summarie…

Information retrievalConcept searchbusiness.industryComputer scienceSearch engine indexingSemantic searchFunctional approachWord searchSemanticscomputer.software_genreBag-of-words modelVisual WordArtificial intelligencebusinesscomputerNatural language processingInternational Journal of Information Technology, Communications and Convergence
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IntentStreams

2015

The user's understanding of information needs and the information available in the data collection can evolve during an exploratory search session. Search systems tailored for well-defined narrow search tasks may be suboptimal for exploratory search where the user can sequentially refine the expressions of her information needs and explore alternative search directions. A major challenge for exploratory search systems design is how to support such behavior and expose the user to relevant yet novel information that can be difficult to discover by using conventional query formulation techniques. We introduce IntentStreams, a system for exploratory search that provides interactive query refine…

Computer scienceExploratory search02 engineering and technologycomputer.software_genreSearch engine020204 information systemsUser interface design0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesParallel browsingInformation exploration050107 human factorsSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalConcept searchWeb search querySettore INF/01 - Informaticabusiness.industrySearch analytics05 social sciencesSemantic searchUser interface designData miningUser interfacebusinesscomputerProceedings of the 20th International Conference on Intelligent User Interfaces
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