王明文,洪 欢,江爱文,左家莉. 基于词重要性的信息检索图模型[J]. 中文信息学报, 2016, 30(4): 134-141.
WANG Mingwen, HONG Huan, JIANG Aiwen, ZUO Jiali. An Information Retrieval Graph Model Based on Term Importance. , 2016, 30(4): 134-141.
基于词重要性的信息检索图模型
王明文,洪 欢,江爱文,左家莉
江西师范大学 计算机信息工程学院,江西 南昌 330022
An Information Retrieval Graph Model Based on Term Importance
WANG Mingwen, HONG Huan, JIANG Aiwen, ZUO Jiali
School of Computer Information Engineering, Jiangxi Normal University, Nanchang, Jiangxi 330022, China
Abstract：In information retrieval modeling, to determine the importance of index terms of the documents is an important content. Those retrieval models which use a bag-of-word document representation are mostly based on the term independence assumption, and calculate the terms importance by the functions of TF and IDF, without considering about the relationship between terms. In this paper, we used a document representation based on graph-of-word to capture the dependencies between terms, and proposed a novel information graph retrieval model TI-IDF. According to the graph, we obtained the co-occurrence matrix and the probability transfer matrix of terms, then we determined the terms importance (TI) by using the Markov chain computing method, and used TI to replace traditional term frequency at indexing time. This model possesses a better robustness, we compared our model with traditional retrieval models on the international public datasets. Experimental results show that, the proposed model is consistently superior to BM25 and better than its extension models, TW-IDF and other models in most cases.
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2016, Vol. 30 
