A graph-based recommender system for digital library

ABSTRACT

Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, user-user and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.

REFERENCES

• 1: Ahmad M. Ahmad Wasfi, Collecting user access patterns for building user profiles and collaborative filtering, Proceedings of the 4th international conference on Intelligent user interfaces, p.57-64, January 05-08, 1999, Los Angeles, California, United States [doi>10.1145/291080.291091]
• 2: Ricardo A. Baeza-Yates , Gaston H. Gonnet, Fast text searching for regular expressions or automaton searching on tries, Journal of the ACM (JACM), v.43 n.6, p.915-936, Nov. 1996 [doi>10.1145/235809.235810]
• 3: Marko Balabanović , Yoav Shoham, Fab: content-based, collaborative recommendation, Communications of the ACM, v.40 n.3, p.66-72, March 1997 [doi>10.1145/245108.245124]
• 4: Basu, C., Hirsh, H. Cohen, W., Nevill-Manning, C. Technical Paper Recommendation: A Study in Combining Multiple Information Sources. Journal of Artificial Intelligence Research, (2001). 231--252
• 5: Chumki Basu , Haym Hirsh , William Cohen, Recommendation as classification: using social and content-based information in recommendation, Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, p.714-720, July 1998, Madison, Wisconsin, United States
• 6: H. Chen , T. Ng, An algorithmic approach to concept exploration in a large knowledge network (automatic thesaurus consultation): symbolic branch-and-bound search vs. connectionist Hopfield net activation, Journal of the American Society for Information Science, v.46 n.5, p.348-369, June 1995 [doi>10.1002/(SICI)1097-4571(199506)46:5<348::AID-ASI6>3.0.CO;2-1]
• 7: Kenneth Ward Church, A stochastic parts program and noun phrase parser for unrestricted text, Proceedings of the second conference on Applied natural language processing, February 09-12, 1988, Austin, Texas [doi>10.3115/974235.974260]
• 8: Claypool, M., Gokhale, A., Miranda, T., Murnikov, P., Netes, D., Sartin, M., Combining Content-Based and Collaborative Filters in an Online Newspaper. in Proceedings of ACM SIGIR Workshop on Recommender Systems, (1999)
• 9: Condliff, M.K., Lewis, D., Madigan, D., Posse, Bayesian, C., Mixed-effects Models for Recommender Systems. in Proceedings of ACM SIGIR Workshop on Recommender Systems, (1999)
• 10: Dalton, J., Deshmane, A. Artificial neural networks. IEEE Potentials, 10 (2), (1991). 33--36
• 11: Gary Geisler , David McArthur , Sarah Giersch, Developing recommendation services for a digital library with uncertain and changing data, Proceedings of the 1st ACM/IEEE-CS joint conference on Digital libraries, p.199-200, January 2001, Roanoke, Virginia, United States [doi>10.1145/379437.379483]
• 12: Will Hill , Larry Stead , Mark Rosenstein , George Furnas, Recommending and evaluating choices in a virtual community of use, Proceedings of the SIGCHI conference on Human factors in computing systems, p.194-201, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223929]
• 13: Andrea L. Houston , Hsinchun Chen , Bruce R. Schatz , Susan M. Hubbard , Robin R. Sewell , Tobun D. Ng, Exploring the use of concept spaces to improve medical information retrieval, Decision Support Systems, v.30 n.2, p.171-186, Dec. 27 2000 [doi>10.1016/S0167-9236(00)00097-X]
• 14: Kevin Knight, Connectionist ideas and algorithms, Communications of the ACM, v.33 n.11, p.58-74, Nov. 1990 [doi>10.1145/92755.92764]
• 15: K. L. Kwok, Comparing representations in Chinese information retrieval, Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval, p.34-41, July 27-31, 1997, Philadelphia, Pennsylvania, United States
• 16: Udi Manber , Gene Myers, Suffix arrays: a new method for on-line string searches, SIAM Journal on Computing, v.22 n.5, p.935-948, Oct. 1993 [doi>10.1137/0222058]
• 17: Raymond J. Mooney , Loriene Roy, Content-based book recommending using learning for text categorization, Proceedings of the fifth ACM conference on Digital libraries, p.195-204, June 02-07, 2000, San Antonio, Texas, United States [doi>10.1145/336597.336662]
• 18: Ong, T., Chen, H., Updateable PAT-Tree approach to Chinese key phrase extraction using mutual information: a linguistic foundation for knowledge management. in Proceedings of the Second Asian Digital Library Conference, (Taipei, Taiwan, 1999), 63--84
• 19: Michael J. Pazzani, A Framework for Collaborative, Content-Based and Demographic Filtering, Artificial Intelligence Review, v.13 n.5-6, p.393-408, Dec. 1999 [doi>10.1023/A:1006544522159]
• 20: Paul Resnick , Hal R. Varian, Recommender systems, Communications of the ACM, v.40 n.3, p.56-58, March 1997 [doi>10.1145/245108.245121]
• 21: Gerard Salton, Automatic text processing: the transformation, analysis, and retrieval of information by computer, Addison-Wesley Longman Publishing Co., Inc., Boston, MA, 1989
• 22: Badrul M. Sarwar , Joseph A. Konstan , Al Borchers , Jon Herlocker , Brad Miller , John Riedl, Using filtering agents to improve prediction quality in the GroupLens research collaborative filtering system, Proceedings of the 1998 ACM conference on Computer supported cooperative work, p.345-354, November 14-18, 1998, Seattle, Washington, United States [doi>10.1145/289444.289509]
• 23: J. Ben Schafer , Joseph A. Konstan , John Riedl, E-Commerce Recommendation Applications, Data Mining and Knowledge Discovery, v.5 n.1-2, p.115-153, January-April 2001 [doi>10.1023/A:1009804230409]
• 24: Upendra Shardanand , Pattie Maes, Social information filtering: algorithms for automating “word of mouth”, Proceedings of the SIGCHI conference on Human factors in computing systems, p.210-217, May 07-11, 1995, Denver, Colorado, United States [doi>10.1145/223904.223931]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.7 Digital Libraries
          Subjects: Systems issues

General Terms:
Algorithms, Design, Experimentation

Keywords:
Hopfield net algorithm, chinese phrase extraction, collaborative filtering, content-based filtering, graph-based model, mutual information algorithm, recommender system