2016
DOI: 10.1016/j.scico.2015.06.008
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SMORE: Towards a semantic modeling for knowledge representation on social media

Abstract: This research presents SMORE, a semantic model for knowledge representation on social media. In order to provide recommendations, the model provides the elements for representing the content through the use of an ontological model and semantic techniques for the characterization and relationships between user profiles, products and social networks. In fact, with this model could be the basis of recommendation system based on social media data, and it could be exploited use by the recommendations on different p… Show more

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Cited by 22 publications
(11 citation statements)
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“…Afterwards, a semantic model was generated through the identified categories. This made it possible to understand the content through formal models and make them more efficient (Villanueva et al, 2015).…”
Section: Methodsmentioning
confidence: 99%
“…Afterwards, a semantic model was generated through the identified categories. This made it possible to understand the content through formal models and make them more efficient (Villanueva et al, 2015).…”
Section: Methodsmentioning
confidence: 99%
“…The world is increasingly being digitized and increasing amounts of data are generated from heterogeneous sources, reflecting the actions of industries, organizations and people for example, conducting online transactions [1], selling products, rating services [2] and collating users' opinions through social network platforms [3]. Understanding and utilizing data is a key to taking actions that could minimize business losses, detect market trends, increase product sales and give more options to industry decision makers to make choices with confidence [4].…”
Section: Overviewmentioning
confidence: 99%
“…Achieving this aim will bring about the following artefacts: (1) an approach using semantics and ontologies to integrate Big Data; (2) integration algorithms underpinning the approach; and (3) a prototype tool to test the feasibility of (1) and (2).…”
Section: Overviewmentioning
confidence: 99%
“…The other approach to give semantic descriptors as of now under scrutiny is machine learning. Fundamentally machine learning implies separating affiliation principles and practices to enable machines to finish particular assignments and additionally their human partners [8].…”
Section: E Ontology Based Knowledge Basementioning
confidence: 99%