Abstract
Keywords extraction can be regarded as a process of ranking the words in a given document (set) according to their importance to this document (set). Previous graph-based methods usually consider only one kind of relation between words, such as co-occurrence, ignoring the fact that words in a text interact with each other via multiple relations, which collaborate to decide the importance of words. Although some recently published methods use more than one relation type, they fail to consider the interactions between relations. Therefore, we propose a new approach for keywords extraction by constructing a multi-relational network from texts, which evaluates the various relations at the same time. Experiments shows that our approach is competitive compared with some typical methods.
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Lei, K., Tang, H., Zeng, Y. (2013). Keywords Extraction via Multi-relational Network Construction. In: Nagamalai, D., Kumar, A., Annamalai, A. (eds) Advances in Computational Science, Engineering and Information Technology. Advances in Intelligent Systems and Computing, vol 225. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00951-3_4
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DOI: https://doi.org/10.1007/978-3-319-00951-3_4
Publisher Name: Springer, Heidelberg
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