Keyphrase Extraction and Grouping Based on Association Rules

Keyphrases are important in capturing the content of a document and thus useful for many natural language processing tasks such as Information Retrieval, Document Classification, and Text Summarization. Keyphrase extraction aims to identify multi-word sequences from a collection of documents that more or less correspond to keyphrases. In this paper, we propose a new method for keyphrase extraction based on association rule mining. Redundant multi-word sequences or synonymous phrases inevitably make up a big part of the keyphrases extracted. With association rules, we can also reduce the redundancy by grouping the related keyphrases that have strong co-occurrence frequencies. We further apply our keyphrase extraction and grouping solution to Information Retrieval. By both distinguishing and grouping keyphrases, we are able to achieve improved performance for Information Retrieval.

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