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SACAM A Model for Describing and Classifying Sentiment Analysis Methods

Abstract

In this paper we introduce SACAM — a model for describing and classifying sentiment analysis (SA) methods. The model focuses on the knowledge used during processing textual opinions. SACAM was designed to create informative descriptions of SA methods (or classes of SA methods) and is strongly integrated with its accompanying graphical notation suited for presenting the descriptions in diagrammatical form. The paper discusses applications of SACAM and shows directions of its further development.

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Details

Category:
Conference activity
Type:
materiały konferencyjne indeksowane w Web of Science
Title of issue:
Proceedings of the 9th International Conference on Agents and Artificial Intelligence strony 196 - 206
Language:
English
Publication year:
2017
Bibliographic description:
Waloszek A., Waloszek W..: SACAM A Model for Describing and Classifying Sentiment Analysis Methods, W: Proceedings of the 9th International Conference on Agents and Artificial Intelligence, 2017, ,.
DOI:
Digital Object Identifier (open in new tab) 10.5220/0006199901960206
Verified by:
Gdańsk University of Technology

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