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This paper presents a new solution for making existing web-databases accessible for semantic agents. Instead of adding semantic annotations to a page itself or publishing the content separately, the elements of a web-page are annotated and published in an external file, maybe even on an external site. A semantic agent can use these annotations like an instruction manual to find out how to interpret...
In this paper we present a framework that extracts meaningful knowledge from microposts shared in social platforms in order to build user profiles. This process involves different steps for the analysis of such microposts (extraction of keywords, named entities and their matching to ontological concepts) and their weighting. The concept weighting involves different scores, such as sentiment analysis...
Social bookmarking tools are rapidly emerging on the Web as it can be witnessed by the overwhelming number of participants. In such spaces, users annotate resources by means of any keyword or tag that they find relevant, giving raise to lightweight conceptual structures aka folksonomies. In this respect, needless to mention that ontologies can be of benefit for enhancing information retrieval metrics...
The semantic analysis and context awareness in data mining can intensively increase results precision. In this research different semantic relatedness functions called ??Measure of Semantic Relatedness (MSR)?? are discussed and compared. We found that the quality and accuracy of MSRs are different when applied in various contexts. Here we compared several MSR algorithms using different corpuses and...
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