Automatic query-based keyword and keyphrase extraction

Automatic query-based keyword and keyphrase extraction
International Symposium on Artificial Intelligence and Signal Processing ‪(AISP)‬
شیراز
تاریخ کنفرانس: 
چهارشنبه - ۰۳ آبان ۱۳۹۶ تا پنجشنبه - ۰۴ آبان ۱۳۹۶
مؤسسه برگزارکننده: 
چکیده

Extracting keywords and keyphrases mainly for identifying content of a document, has an importance role in text processing tasks such as text summarization, information retrieval, and query expansion.‎ In this research, we introduce a new keyword/keyphrase extraction approach in which both single and multi-document keyword/keyphrase extraction techniques are considered.‎ The proposed approach is specifically practical when a user is interested in additional data such as keywords/keyphrases related to a topic or query.‎ In the proposed approach, first a set of documents are retrieved based on user's query, then a single document keyword extraction method is applied to extract candidate keyword/keyphrases from each retrieved document.‎ Finally, a new re-scoring scheme is introduced to extract final keywords/keyphrases.‎ We have evaluated the proposed method based on the relationship between the final keyword/keyphrases with the initial user query, and based user's satisfaction.‎ Our experimental results show how much the extracted keywords/keyphrases are relevant and well matched with user's need.‎

استناد: 

Bayatmakou, Farnoush, Abbas Ahmadi, and Azadeh Mohebi.‎ 2017.‎ Automatic query-based keyword and keyphrase extraction. Article Presented at International Symposium on Artificial Intelligence and Signal Processing (AISP), Shiraz.‎

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