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论文类型：期刊论文

发表时间：2011-05-01

发表刊物：6th International Symposium on Management Engineering (ISME 2009)

收录刊物：SCIE、EI、CPCI-S、Scopus

卷号：7

期号：5B,SI

页面范围：2689-2698

ISSN号：1349-4198

关键字：Text representation; Graph structure; Maximum common subgraph; Classification

摘要：To represent the textual knowledge more expressively, a kind of semantic-based graph structure is proposed, in which more semantic and ordering information among terms as well as the structural information of the text are incorporated. Such model can be constructed by extracting representative terms from texts and their mutually semantic relationships. Afterward, it is represented as a graph, whose nodes are the selected terms and whose edges are the corresponding relationships respectively. Moreover, the weight is assigned to each edge so that the strength of relationship between two terms can be measured. Furthermore, for this weighted directed graph structure, a novel graph similarity algorithm is developed by extracting the maximum common subgraph between two concerned graphs, which can therefore be used to measure the distance between two graph structures, i.e., two texts, and further be applied to classification tasks. Finally, some experiments have been conducted with the Chinese benchmark corpus for validation. The experimental results have proved the better performance of the proposed textual knowledge representation model in terms of its precision and recall.