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篇目详细内容 |
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【篇名】 |
Can prior knowledge help graph-based methods for keyword extraction? |
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【刊名】 |
Frontiers of Electrical and Electronic Engineering |
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【刊名缩写】 |
Front. Electr. Electron. Eng. |
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【ISSN】 |
2095-2732 |
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【EISSN】 |
2095-2740 |
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【DOI】 |
10.1007/s11460-011-0174-7 |
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【出版社】 |
Higher Education Press and Springer-Verlag Berlin
Heidelberg |
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【出版年】 |
2012 |
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【卷期】 |
7
卷2期 |
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【页码】 |
242-253
页,共
12
页 |
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【作者】 |
Zhiyuan LIU;
Maosong SUN;
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【关键词】 |
？？keyword ？？extraction; ？？prior？？ knowledge; PageRank; DiffusionRank |
【摘要】 |
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Graph-based methods are one of the widely used unsupervised approaches for keyword extraction. In this approach, words are linked according to their co-occurrences within the document. Afterwards, graph-based ranking algorithms are used to rank words and those with the highest scores are selected as keywords. Although graph-based methods are effective for keyword extraction, they rank words merely based on word graph topology. In fact, we have various prior knowledge to identify how likely the words are keywords. The knowledge of words may be frequency-based, position-based, or semantic-based. In this paper, we propose to incorporate prior knowledge with graph-based methods for keyword extraction and investigate the contributions of the prior knowledge. Experiments reveal that prior knowledge can significantly improve the performance of graph-based keyword extraction. Moreover, by combining prior knowledge with neighborhood knowledge, in experiments we achieve the best results compared to previous graph-based methods. |
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