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Title: Information refinement over multi-media question-answering applying ranking and Naïve Bayes classification
Authors: K. Kedhareswari, B. Sathya Bama
Journal: ARPN Journal of Engineering and Applied Sciences
Publisher: Khyber Medical College, Peshawar
Country: Pakistan
Year: 2015
Volume: 10
Issue: 18
Language: English
Keywords: mediaQuestion-Answering (QA)Naïve Bayes classifierStemming algorithmCommunity responses
Interactive answers are feat out to the users, which plays an important role to provide information. Usually, Question-Answering (QA) is provided only in plain text which may not be in a useful format presuming the customer. Image and videos if accompanied then it would be better to demonstrate the object or process. In this paper, textual response is accompanied by the appropriate media to recommend a method inspired by the response. Our system is classified into four components, (a) Rendering media picking, (b) Questioning propagation, (c) Information picking and (d) Initiate. Rendering media picking is used to select a variety of responses to the receiver. Extracting keywords from the source in question is widely used in the questioning propagation. Choose the correct answer and the result is used to retrieve by Information picking and Initiate. We use Stemming algorithm, Naïve Bayes classifier algorithm and ranking algorithms. We have increased the contribution of community responses also. Any user can get information immediately which is unconscious. In our perspective is to dispense with multiplex query. Questions are engender on the premise of the details, then we straight-up congregate picture and video in search engines.
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