Information Retrieval Based on Word Semantic Clustering
Chia-Yang Chang, Yan-Ting Lin, Shie-Jue Lee, Chih‐Chin Lai · 2018
Information retrieval is an important topic in the modern age. With the advance of Internet, it is more and more easy to retrieve other people's writings or publications. However, how to retrieve desirable information efficiently is a challenging work. Traditional methods like vector space model or bag-of-words are short of providing a good solution due to the incapability of handling the semantics of words satisfactorily. In this paper, we propose a new method for information retrieval. We use Word2vec to transform the words into word vectors which are able to represent the semantic relationship among different words. By considering the semantic of words and clustering the word vectors into concepts, information retrieval can be done effectively.