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SciPRec: Scientific Paper Recommendation

Scientific paper recommendation is nowadays an interesting research area that applies ideas from different domains. The increasing amount of rapidly published scientific papers poses a challenge for researchers to discover and keep track of important and relevant research results. Therefore, it is desirable to design recommender systems based on advanced techniques that deliver useful recommendations.
In this project we study, investigate and model machine learning approaches for scientific paper recommendation. Several challenges make this problem differ from a traditional recommender system problem such as the sparsity in users-items relation driven by the huge number of papers relative to the number of users. Scientific papers with their rich textual content over attributes make the problem relevant to other domains as well like natural language processing and information retrieval.

Project Members:

Current Bachelor (BT) / Master Theses (MT) / Projects (P)

  • (MT) Matrix factorization methods for paper recommendation (Ongoing)
  • (MT) Utilizing domain-related Taxonomy in scientific paper recommendation (Ongoing)
  • (P) LDA and probabilistic approaches in paper recommendation (Ongoing)

Finished Master Theses

  • Collaborative Filtering for Publication recommendation based on common and discriminative topics between users (Completed on August 2016)

Related Publications

  • Anas Alzoghbi, Victor Anthony Arrascue Ayala, Peter M Fischer, Georg Lausen:
    Learning-toRank in research paper CBF recommendation: Leveraging irrelevant papers.pdf ]
    In Proc. of the 3rd Workshop on New Trends in Content-Based Recommender Systems (CBRecSys 2016) co-located with ACM Conference on Recommender Systems (RecSys 2016). Boston, MA, USA, September 16, 2016
  • Anas Alzoghbi, Victor Anthony Arrascue Ayala, Peter M Fischer, Georg Lausen:
    PubRec: Recommending Publications Based On Publicly Available Meta-Data.pdf ]
    In Proc. of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB. Trier, Germany, October 7-9, 2015
  • Anas Alzoghbi, Peter M. Fischer, Anna Gossen, Peter Haase, Thomas Hornung, Beibei Hu, Georg Lausen, Christoph Pinkel, Michael Schmidt:
    Durchblick - A Conference Assistance System for Augmented Reality Devices.pdf ]
    In Proc. of the 11th Extended Semantic Web Conference: Posters & Demonstrations Track (ESWC 2014). Heraklion (Greece), May 2014

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