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Use of Location-based Association Rules for Automatic Keyword Extraction Paul Dimple V.1,* 1Assistant Professor, Department of Computer Science, Dnyanprassarak Mandal's College and Research Centre, Assagao, Bardez, Mapusa-403507, Goa, India *Email id: dimplevp@rediffmail.com
Abstract We present an information extraction technique for extracting keywords from textual documents. The technique called Automatic Keyword Extraction using Location-based Association Rules (AKELAR) is an efficient approach for keyword extraction which integrates adjacency of location of words within a document to automatically select the most discriminative words without using a corpus. It consist of three major phases, namely, Text pre-processing phase for performing Tokenization; Stemming and Stop word Removal, Association Rule Extraction phase for applying the designed Frequent Item-set Extraction approach in generating the set of keywords and Visualization phase for carrying out the presentation of the set of keywords. AKELAR gives the flexibility to select either the set of keywords from a given document or the user-specified number of keywords. There is no restriction to the length of the keyword being extracted.Top Keywords Text pre-processing, Association rule, Frequent item-set extraction, Apriori algorithm, Maximal frequent item-set, Keyword extraction, Apriori algorithm, text document. Top | | | |
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