DC Field | Value | Language |
---|---|---|
dc.contributor.author | Segev, Aviv | ko |
dc.contributor.author | Leshno, Moshe | ko |
dc.contributor.author | Zviran, Moshe | ko |
dc.date.accessioned | 2013-03-06T14:20:06Z | - |
dc.date.available | 2013-03-06T14:20:06Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2007-12 | - |
dc.identifier.citation | JOURNAL OF INTELLIGENT INFORMATION SYSTEMS, v.29, no.3, pp.305 - 327 | - |
dc.identifier.issn | 0925-9902 | - |
dc.identifier.uri | http://hdl.handle.net/10203/87229 | - |
dc.description.abstract | Context recognition is an important component of the common sense knowledge problem, which is one of the key research areas in the field of Artificial Intelligence. The paper develops a model of context recognition using the Internet as a knowledge base. The use of the Internet as a database for context recognition gives a context recognition model immediate access to a nearly infinite amount of data in a multiplicity of fields. Context is represented here as any textual description that is most commonly selected by a set of subjects to describe a given situation. The model input is based on any aspect of the situation that can be translated into text (such as: voice recognition, image recognition, facial expression interpretation, and smell identification). The research model is based on the streaming in text format of information that represents situations-Internet chats, e-mails, Shakespeare plays, or article abstracts. The comparison of the results of the algorithm with the results of human subjects yielded a very high agreement and correlation. The results showed there was no significant difference in the determination of context between the algorithm and the human subjects. | - |
dc.language | English | - |
dc.publisher | SPRINGER | - |
dc.title | Context recognition using internet as a knowledge base | - |
dc.type | Article | - |
dc.identifier.wosid | 000251095300004 | - |
dc.identifier.scopusid | 2-s2.0-36448958723 | - |
dc.type.rims | ART | - |
dc.citation.volume | 29 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 305 | - |
dc.citation.endingpage | 327 | - |
dc.citation.publicationname | JOURNAL OF INTELLIGENT INFORMATION SYSTEMS | - |
dc.identifier.doi | 10.1007/s10844-006-0015-y | - |
dc.contributor.localauthor | Segev, Aviv | - |
dc.contributor.nonIdAuthor | Leshno, Moshe | - |
dc.contributor.nonIdAuthor | Zviran, Moshe | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | record classification | - |
dc.subject.keywordAuthor | retrieval models | - |
dc.subject.keywordAuthor | metadata | - |
dc.subject.keywordAuthor | information filtering | - |
dc.subject.keywordAuthor | text analysis | - |
dc.subject.keywordAuthor | knowledge retrieval | - |
dc.subject.keywordPlus | SPEECH-UNDERSTANDING SYSTEM | - |
dc.subject.keywordPlus | ONTOLOGY | - |
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