关键词: 虚假评论, 聚类, 语言结构, 情感极性, 遗传算法

Abstract: With the development of electronic commerce, assessing the trustworthiness of reviews is becoming a key issue. Heuristic strategies or traditional supervised learning methods cannot effectively solve this task. There must be some differences on language structure and sentiment polarity between deceptive reviews and truthful ones. This paper defines the features related to the review text and uses genetic algorithm for the features selection of language structure and sentiment polarity. Then, this paper uses the selected features and combines two non-supervision clustering algorithms to identify deceptive reviews. The experimental results verify the effectiveness of the proposed methods.

Key words: deceptive reviews, clustering, language structure, sentiment polarity, genetic algorithm