基于多属性加权的社会化问答社区关键词提取方法

Purpose/significance] Existing methods of extracting keywords can't be applied to the social Q&A community effectively, because they are not suitable for the characteristics of the social Q&A community which embodies short texts, colloquial contents and sparse data. They rarely think about the impact of users' attention on words. In view of the aforementioned problem, this paper presents a novel keywords extraction method based on multi-attributes weighted for the social Q&A community. [Method/process] This method improved the traditional TF-IDF algorithm by introducing the tuning function and the part of speech. Besides, it calculated the weight of words based on a linear weighting formula, which fused four attributes of user focus by dealing with numbers of users' answer, attention, browse, and comments. [Result/conclusion] Experiments show that this method can extract keywords from the social Q&A community more effectively.