A Semantic Metadata Enrichment Software Ecosystem based on Sentiment and Emotion Metadata Enrichments

Authors

  • Ronald Brisebois  Ecole de technologie supérieure, University of Quebec, Montreal, Quebec, Canada
  • Alain Abran  Ecole de technologie supérieure, University of Quebec, Montreal, Quebec, Canada
  • Apollinaire Nadembega  Network Research Lab., University of Montreal, Montreal, Quebec, Canada
  • Philippe Ntechobo  Ecole Polytechnique de Montréal, Montreal, Quebec, Canada

Keywords:

Emotion Analysis, Natural Language Processing, Semantic Metadata Enrichment, Sentiment Analysis, Text And Data Mining

Abstract

Information retrieval and analysis is frequently used to extract meaningful knowledge from the unstructured web and long texts. As existing computer search engines struggle to understand the meaning of natural language, semantically sentiment and emotion enriched metadata may improve search engine capabilities and user finding. A semantic metadata enrichment software ecosystem (SMESE) has been proposed in our previous research. This paper presents an enhanced version of this ecosystem with a sentiment and emotion metadata enrichments algorithm. This paper proposes a model and an algorithm enhancing search engines finding contents according to the user interests, through text analysis approaches for sentiment and emotion analysis. It presents the design, implementation and evaluation of an engine harvesting and enriching metadata related to sentiment and emotion analysis. It includes the SSEA (Semantic Sentiment and Emotion Analysis) semantic model and algorithm that discover and enrich sentiment and emotion metadata hidden within the text or linked to multimedia structure. The performance of sentiment and emotion analysis enrichments is evaluated using a number of prototype simulations by comparing them to existing enriched metadata techniques. The results show that the algorithm SSEA enable greater understanding and finding of document or contents associated with sentiment and emotion enriched metadata.

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International Journal of Scientific Research in Science, Engineering and Technology

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2017-04-23

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[1]
Ronald Brisebois, Alain Abran, Apollinaire Nadembega, Philippe Ntechobo "A Semantic Metadata Enrichment Software Ecosystem based on Sentiment and Emotion Metadata Enrichments" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 2, pp.625-641, March-April-2017.