A Parallel Paper recommender system in Big Data Scholarly
Publish place: International Conference on New Research Findings in Electrical Engineering and Computer Science
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
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COMCONF01_694
تاریخ نمایه سازی: 8 آذر 1394
Abstract:
Nowadays, the quantity of data that is created is so huge. One area of the web that has seen continued growth is the online publication of research papers. Recommender systems were developed to help close the gap between information collection and analysis by filtering all of theavailable information to present what is most valuable to the user. Against this background, inthis work, we address the problem of paper recommendation in Big Data scholarly. We proposed an approximate approach for recommending papers to researchers based on local sensitivehashing by converting the citations of papers to signatures and compare these signatures against each other to detect similar papers according to their citations. A parallel and distributed aspects of the proposal is also discussed.
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Authors
Siroos Keshavarz
Department of Computer Engineering, Islamic Azad University, Safashahr Branch, Safashahr, Fars, Iran,
Ali Reza Honarvar
Department of Computer Engineering, Islamic Azad University, Safashahr Branch, Safashahr, Fars, Iran,