An overview on XML semantic disambiguation from unstructured text to semi-structured data

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dc.contributor.author Tekli, Joe
dc.date.accessioned 2017-01-27T07:54:11Z
dc.date.available 2017-01-27T07:54:11Z
dc.date.copyright 2016 en_US
dc.date.issued 2017-01-27
dc.identifier.issn 1041-4347 en_US
dc.identifier.uri http://hdl.handle.net/10725/5080
dc.description.abstract Since the last two decades, XML has gained momentum as the standard for web information management and complex data representation. Also, collaboratively built semi-structured information resources, such as Wikipedia, have become prevalent on the Web and can be inherently encoded in XML. Yet most methods for processing XML and semi-structured information handle mainly the syntactic properties of the data, while ignoring the semantics involved. To devise more intelligent applications, one needs to augment syntactic features with machine-readable semantic meaning. This can be achieved through the computational identification of the meaning of data in context, also known as (a.k.a.) automated semantic analysis and disambiguation, which is nowadays one of the main challenges at the core of the Semantic Web. This survey paper provides a concise and comprehensive review of the methods related to XML-based semi-structured semantic analysis and disambiguation. It is made of four logical parts. First, we briefly cover traditional word sense disambiguation methods for processing flat textual data. Second, we describe and categorize disambiguation techniques developed and extended to handle semi-structured and XML data. Third, we describe current and potential application scenarios that can benefit from XML semantic analysis, including: data clustering and semantic-aware indexing, data integration and selective dissemination, semantic-aware and temporal querying, web and mobile services matching and composition, blog and social semantic network analysis, and ontology learning. Fourth, we describe and discuss ongoing challenges and future directions, including: the quantification of semantic ambiguity, expanding XML disambiguation context, combining structure and content, using collaborative/social information sources, integrating explicit and implicit semantic analysis, emphasizing user involvement, and reducing computational complexity. en_US
dc.language.iso en en_US
dc.title An overview on XML semantic disambiguation from unstructured text to semi-structured data en_US
dc.type Article en_US
dc.description.version Published en_US
dc.title.subtitle background, applications, and ongoing challenges en_US
dc.author.school SOE en_US
dc.author.idnumber 201306321 en_US
dc.author.department Electrical And Computer Engineering en_US
dc.description.embargo N/A en_US
dc.relation.journal IEEE Transactions on Knowledge and Data Engineering en_US
dc.journal.volume 28 en_US
dc.journal.issue 6 en_US
dc.article.pages 1383-1407 en_US
dc.keywords Document Preparation en_US
dc.keywords Semantic Networks en_US
dc.keywords Document management en_US
dc.identifier.doi http://dx.doi.org/10.1006/bbrc.1994.188310.1109/TKDE.2016.2525768 en_US
dc.identifier.ctation Tekli, J. (2016). An overview on xml semantic disambiguation from unstructured text to semi-structured data: Background, applications, and ongoing challenges. IEEE Transactions on Knowledge and Data Engineering, 28(6), 1383-1407. en_US
dc.author.email joe.tekli@lau.edu.lb en_US
dc.identifier.tou http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php en_US
dc.identifier.url http://ieeexplore.ieee.org/abstract/document/7398037/ en_US
dc.author.affiliation Lebanese American University en_US

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