Earticle

초록

영어

With the tremendous amount of research publications online, finding relevant ones for a particular research topic can be an overwhelming task. As a solution, papers recommender systems have been proposed to help researchers find their interested papers or related papers to their fields. Most of existing papers recommendation approaches are based on paper collections, citations and user profile which is not always available (not all users are registered with their profiles). The existing approaches assume that users have already published papers and registered in their systems. Consequently, this neglects new researcher without published papers or profiles. In this paper, we propose an academic researcher papers recommendation approach that is based on the paper’s topics and paper’s main ideas. The approach requires as input only a single research paper and extracts its topics as short queries and main ideas’ sentences as long queries which are then submitted to existing online repositories that contains research papers to retrieve similar papers for recommendation. Four query extraction and one paper recommendation methods are proposed. Conducted experiments show that the proposed method presents good improvement.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1. Paper’s Topics Extraction
  2.2. Research Paper Recommendation
 3. Academic Research Papers Recommendation for Non-profiled Users
  3.1. Candidate Queries Rxtraction
  3.2. Selecting Final Queries or Queries Weighting
  3.3 Papers recommendation
 4. Evaluation of the proposed method
  4.1 Topics Extraction Evaluation
  4.2. Paper Recommendation Evaluation
 5. Conclusion
 References

키워드

저자

• Damien Hanyurwimfura [ Key Laboratory for Embedded and Network Computing of Hunan Province, the College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, China, College of Science and Technology, University of Rwanda, Kigali, Rwanda ]
• Liao Bo [ Key Laboratory for Embedded and Network Computing of Hunan Province, the College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, China ]
• Vincent Havyarimana [ Key Laboratory for Embedded and Network Computing of Hunan Province, the College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, China ]
• Dennis Njagi [ College of Information Science and Engineering, Central South University, China ]
• Faustin Kagorora [ Key Laboratory for Embedded and Network Computing of Hunan Province, the College of Computer Science and Electronics Engineering, Hunan University, Changsha, 410082, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605