FML-based linguistic classification agent for social media application

Abstract

Fuzzy Markup Language (FML) presented by IEEE Computational Intelligence Society (CIS) has been an IEEE Standard since May 2016. It is an XML-based language for designer to easily construct the knowledge base and rule base of the developed fuzzy logic system. In this paper, we propose an FML-based linguistic classification agent and apply it to popular Chinese songs' classification in social media environment. In addition, the lyrics are retrieved from Youtube, Facebook or Google+, and then we adopt Natural Language Processing (NLP) mechanism to deal with the document preprocessing. First, the domain experts construct the classification ontology model and design related categories for the application domain. Moreover, the fuzzy concept sets are also adopted in the related categories. Then, the Chinese Knowledge Information Processing (CKIP) tool is utilized to deal with the Chinese documents of the songs. Finally, the FML-based knowledge base and rule base of the classification agent are constructed for inferring the related categories of the song. The Fujisoft robot PALRO receives the classified songs and plays the song for the desired users. Experimental results show the proposed classification agent can work correctly.