Search results for "Explicit semantic analysis"

showing 4 items of 4 documents

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)
researchProduct

Cognitive Linguistics as the Underlying Framework for Semantic Annotation

2012

In recent years many attempts have been made to design suitable sets of rules aimed at extracting the semantic meaning from plain text, and to achieve annotation, but very few approaches make extensive use of grammars. Current systems are mainly focused on extracting the semantic role of the entities described in the text. This approach has limitations: in such applications the semantic role is conceived merely as the meaning of the involved entities without considering their context. As an example, current semantic annotators often specify a date entity without any annotation regarding the kind of the date itself i.e. a birth date, a book publication date, and so on. Moreover, these system…

semantic annotation cognitive linguistics construction grammarSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer sciencebusiness.industrycomputer.software_genreSemantic role labelingSemantic similaritySemantic equivalenceExplicit semantic analysisSemantic computingSemantic analyticsSemantic technologyArtificial intelligenceSemantic Web StackbusinesscomputerNatural language processing2012 IEEE Sixth International Conference on Semantic Computing
researchProduct

A Semantic Similarity Measure for the SIMS Framework

2008

The amount of currently available digital information grows rapidly. Relevant information is often spread over different information sources. An efficient and flexible framework to allow users to satisfy ef- fectively their information needs is required. The work presented in this paper describes SIMS (Semantic Information Management System), a ref- erence architecture for a framework performing semantic annotation, search and retrieval of information from multiple sources. The work pre- sented in this paper focuses on a specific SIMS module, the SIMS Semantic Content Navigator, proposing an algorithm and the related implementa- tion to calculate a semantic similarity measure inside an OWL …

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniInformation retrievalComputer scienceInformation needsWeb Ontology Languageknowledge managementOntology (information science)Semantic gridSemantic similaritySemantic similarityExplicit semantic analysisSemantic computingOntologySemantic technologySemantic integrationontologySemantic Web StackcomputerInformation filtering systemcomputer.programming_language
researchProduct

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
researchProduct