Personalized Medical Information Filtering using Evidence Phrases
Mu. Annalakshmi, A. Padmapriya1
1Mu. Annalakshmi, Research Scholar, Department of Computer Science, Alagappa University, Karaikudi, India.
2Dr. A. Padmapriya, Associate Professor, Department of Computer Science, Alagappa University, Karaikudi, India.
Manuscript received on 12 August 2019 | Revised Manuscript received on 17 August 2019 | Manuscript published on 30 August 2019 | PP: 3299-3307 | Volume-8 Issue-10, August 2019 | Retrieval Number: J12120881019/2019©BEIESP | DOI: 10.35940/ijitee.J1212.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Finding the required information in the field of medicine from the World Wide Web has been a challenging task for the users since large number of medical research documents are added to it every day. Personalization of web search would help the professionals or beginners in medicinal field in retrieving the relevant information. The proposed method gathers the users’ browsing patterns from the browser and builds evidence phrases based on factors like visit count, bookmarks or downloads. These evidence phrases determine the rank of the websites in the search results. The proposed method is evaluated with the relevance data collected from allied medical professionals. Evaluation shows that the proposed method ranks the user preferred pages in the top of the search results. It helps the users from the field of medicine to find their information needs more quickly without surfing all the search results of the query.
Keywords: User Personalization, User Profiling, Evidence Phrases, Information Filtering, Relevance
Scope of the Article: Information Retrieval