Search results for "semantic similarity"

showing 10 items of 38 documents

Towards semantic-based RSS merging

2009

Merging information can be of key importance in several XML-based applications. For instance, merging the RSS news from different sources and providers can be beneficial for end-users (journalists, economists, etc.) in various scenarios. In this work, we address this issue and mainly explore the relatedness relationships between RSS entities/ elements. To validate our approach, we also provide a set of experimental tests showing satisfactory results. © 2009 Springer-Verlag Berlin Heidelberg

Information retrievalComputer sciencecomputer.internet_protocolRSSINF/01 - INFORMATICAComputerApplications_COMPUTERSINOTHERSYSTEMScomputer.file_formatSet (abstract data type)Semantic similarityArtificial IntelligenceKey (cryptography)Document Object ModelcomputerXML
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A Semantic Layer on Semi-structured Data Sources for Intuitive Chatbots

2009

The main limits of chatbot technology are related to the building of their knowledge representation and to their rigid information retrieval and dialogue capabilities, usually based on simple "pattern matching rules". The analysis of distributional properties of words in a texts corpus allows the creation of semantic spaces where represent and compare natural language elements. This space can be interpreted as a "conceptual" space where the axes represent the latent primitive concepts of the analyzed corpus. The presented work aims at exploiting the properties of a data-driven semantic/conceptual space built using semi-structured data sources freely available on the web, like Wikipedia. Thi…

Information retrievalKnowledge representation and reasoningbusiness.industryComputer scienceComputer Science::Information Retrievalcomputer.software_genreChatbotsemantic spaces chatbotSemantic similarityExplicit semantic analysisEncyclopediaSemi-structured dataPattern matchingArtificial intelligencebusinesscomputerNatural language processingNatural language
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Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach

2021

Concept maps are significant tools able to support several tasks in the educational area such as curriculum design, knowledge organization and modeling, students' assessment and many others. They are also successfully used in learning activities in which students have to represent domain knowledge according to teacher's assignment. In this context, the development of Learning Analytics approaches would benefit of methods that automatically compare concept maps. Detecting concept maps similarities is relevant to identify how the same concepts are used in different knowledge representations. Algorithms for comparing graphs have been extensively studied in the literature, but they do not appea…

Information retrievalLearning AnalyticKnowledge representation and reasoningComputer scienceConcept mapKnowledge organizationLearning analyticsContext (language use)SemanticsLearning AnalyticsConcept MapConcept MapsDeep LearningInfersentSimilarity (psychology)Semantic Similarity MeasuresDomain knowledgeNatural Language Processing
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Introduction to semantic knowledge base: Linguistic module

2013

Following paper presents main concepts of Semantic Knowledge Base in particular linguistic module. The main assumption is to develop solution that would be easily adoptable by various languages. The module design will be presented in Association Oriented Model to maintain inner compatibility of the Knowledgebase.

Knowledge representation and reasoningDeep linguistic processingComputer sciencebusiness.industryOpen Knowledge Base Connectivitycomputer.software_genreSemantic networkLinguisticsKnowledge-based systemsSemantic similaritySemantic computingSemantic Web StackArtificial intelligencebusinesscomputerNatural language processing2013 6th International Conference on Human System Interactions (HSI)
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Convergence of Web 2.0 and Semantic Web: A Semantic Tagging and Searching System for Creating and Searching Blogs

2007

The work presented in this paper aims to combine Latent Semantic Analysis methodology, common sense and traditional knowledge representation in order to improve the dialogue capabilities of a conversational agent. In our approach the agent brain is characterized by two areas: a "rational area", composed by a structured, rule-based knowledge base, and an "associative area", obtained through a data- driven semantic space. Concepts are mapped in this space and their mutual geometric distance is related to their conceptual similarity. The geometric distance between concepts implicitly defines a sub-symbolic relationship net, which can be seen as a new "sub- symbolic semantic layer" automaticall…

Latent semantic analysisbusiness.industryComputer sciencecomputer.software_genreFeature (linguistics)Knowledge baseSemantic similaritySoftware agentSimilarity (psychology)OntologyUpper ontologyArtificial intelligencebusinesscomputerNatural language processingInternational Conference on Semantic Computing (ICSC 2007)
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Constructions-and-frames analysis of translations

2013

Translation can generally be seen as a task in which the meaning of the original should be preserved as far as possible. This paper formulates the preservation of meaning in terms of theprimacy of the framehypothesis: ideally, the frame of the original is matched by the frame of the translation. I investigate one factor overriding this principle in translations between English and German through the examination of two grammatical constructions, one in English, one in German, which are not commonly available in the other language. Picking a construction comparable in function in the target language leads to frame shifts. In addition to highlighting the interplay between construction and fram…

Linguistics and Languagebusiness.industryComputer sciencemedia_common.quotation_subjectcomputer.software_genreSemanticsLanguage and Linguisticslanguage.human_languageLinguisticsSyntax (logic)GermanMeaning (philosophy of language)Semantic similarityFactor (programming language)languageFrame (artificial intelligence)Artificial intelligencebusinessFunction (engineering)computerNatural language processingcomputer.programming_languagemedia_commonConstructions and Frames
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Semantic Word Error Rate for Sentence Similarity

2016

Sentence similarity measures have applications in several tasks, including: Machine Translation, Paraphrase Iden- tification, Speech Recognition, Question-answering and Text Summarization. However, measures designed for these tasks are aimed at assessing equivalence rather than resemblance, partly departing from human cognition of similarity. While this is reasonable for these activities, it hinders the applicability of sentence similarity measures to other tasks. We therefore propose a new sentence similarity measure specifically designed for resemblance evaluation, in order to cover these fields better. Experimental results are discussed.

Machine translationComputer scienceSpeech recognitionWord error rate02 engineering and technologycomputer.software_genreParaphrase030507 speech-language pathology & audiology03 medical and health sciencesSemantic similarityArtificial IntelligenceLSAWord Error Rate0202 electrical engineering electronic engineering information engineeringsentence resemblanceEquivalence (formal languages)Latent Semantic AnalysiSemantic Word Error Ratesentence similarity measureSWERbusiness.industryLatent semantic analysisSentence SimilaritySemantic ComputingCognitionAutomatic summarizationComputer Networks and Communicationword relatedne020201 artificial intelligence & image processingArtificial intelligence0305 other medical sciencebusinesscomputerNatural language processingWERInformation Systems2016 IEEE Tenth International Conference on Semantic Computing (ICSC)
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Customer recommendation based on profile matching and customized campaigns in on-line social networks

2019

We propose a general framework for the recommendation of possible customers (users) to advertisers (e.g., brands) based on the comparison between On-Line Social Network profiles. In particular, we associate suitable categories and subcategories to both user and brand profiles in the considered On-line Social Network. When categories involve posts and comments, the comparison is based on word embedding, and this allows to take into account the similarity between the topics of particular interest for a brand and the user preferences. Furthermore, user personal information, such as age, job or genre, are used for targeting specific advertising campaigns. Results on real Facebook dataset show t…

Matching (statistics)Word embeddingInformation retrievalSettore INF/01 - InformaticaSocial networkComputer sciencebusiness.industry02 engineering and technologyRecommender systemProfile matchingSocial advertisingRecommendation systemAdvertising campaignSemantic similaritySemantic similarity020204 information systemsSimilarity (psychology)0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingbusinessPersonally identifiable informationProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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A Survey on how to Cross-Reference Web Information Sources

2015

International audience; The goal of giving information a well-defined meaning is currently shared by different research communities. Once information has a well-defined meaning, it can be searched and retrieved more effectively. Therefore, this paper is a survey about the methods that compare different textual information sources in order to determine whether they address a similar information or not. The improvement of the studied methods will eventually lead to increase the efficiency of documentary research. In order to achieve this goal, the first category of methods focuses on semantic measure definitions. A second category of methods focuses on paraphrase identification techniques, an…

Measure (data warehouse)Information retrievalEvent (computing)Computer scienceSimilarity Definition02 engineering and technologyDocumentary ResearchParaphraseCross-referenceIdentification (information)[ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT]Semantic similaritySemantic Relatedness[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT]020204 information systemsSemantic Measures0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSemantic integrationMeaning (existential)Cross-Reference Web Information SourcesEvent ExtractionParaphrase Identification
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Semantics driven interaction using natural language in students tutoring

2007

The aim of this work is to introduce a semantic integration between an ontology and a chatbot in an Intelligent Tutoring Systems (ITS) to interact with students using natural language. The interaction process is driven by the use of a purposely defined ontology. In the ontology two types of conceptual relations are defined. Besides the usual relations, which are used to define the domain's structure, another type of relation is used to define the navigation schema inside the ontology according to the need of managing uncertainty. Uncertainty level is related to student knowledge level about the involved concepts. In this work we propose an ITS for the Java programming language called TutorJ…

Ontology Inference LayerComputer sciencecomputer.internet_protocolOntology (information science)Semanticscomputer.software_genreOWL-SIntelligent tutoring systemsLatent semantic analysisNatural language dialogueSemantic driven interactionSemantic navigationSemantic similaritySemantic computingSchema (psychology)Upper ontologySemantic integrationSemantic compressionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionisemantic navigationLatent semantic analysisbusiness.industryOntology-based data integrationKnowledge levelIntelligent Tutoring SystemsOntologylatent semantic analysisArtificial intelligencesemantic driven interactionbusinesscomputernatural language dialogueNatural language processing
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