Tag Recommendation in Social Networks with the ‎Help of Optimized Text Summarization and ‎Fuzzification

Hashtags,i.e., terms that are prefixed by a # symbol, are vastly used in social media like Twitter, Instagram, etc. Hashtags present rich sentiment information about people's favorite topics and would make a text more accessible and popular. This paper proposed a model of the hashtag recommendation problem using an automatic summarizer using deep neural and Fuzzy logic system,as also some semantic text mining models. The final summarized text is based on Restricted Boltzmann Machine (RBM),and with the help of Extreme learning machines (ELM), improves the training data, then a fuzzy rule-based method on the sentences is done to build the final result.The experiments on two public data sets improved that the proposed model outperforms the related approaches and is more efficient improvement than previous methods.

Tag Recommendation in Social Networks with the ‎Help of Optimized Text Summarization and ‎Fuzzification Keywords:

Hashtag recommendation , Text summarization , Fuzzy , Neural network