Personalized Recommendation and Explanation by using Keyphrases Automatically extracted from Scientific Literature

Dario De Nart, Carlo Tasso, Felice Ferrara

2013

Abstract

Recommender systems are commonly used for discovering potentially relevant papers in huge collections of scientific documents. In this paper we propose a concept-based recommender system where relevant concepts are automatically extracted from scientific resources in order to both model user interests and generate recommendations. Differently from other work in the literature, our concept-based recommender system does not depend on specific domain ontologies and, on the other hand, is based on an unsupervised, domain independent keyphrase extraction algorithm that identifies relevant concepts included in a scientific paper. This semantic-oriented approach allows the user to easily inspect and modify his user model and to effectively justify the proposed recommendations by showing the main concepts included in the suggested papers.

References

  1. Bogers, T. and Van den Bosch, A. (2008). Recommending scientific articles using citeulike. In Proceedings of the 2008 ACM conference on Recommender systems, pages 287-290, New York, NY, USA. ACM.
  2. Bollacker, K. D., Lawrence, S., and Giles, C. L. (2000). Discovering relevant scientific literature on the web. Intelligent Systems and their Applications, IEEE, 15(2):42-47.
  3. Chandrasekaran, K., Gauch, S., Lakkaraju, P., and Luong, H. P. (2008). Concept-based document recommendations for citeseer authors. In Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH 7808, pages 83-92, Berlin, Heidelberg. Springer-Verlag.
  4. Ferrara, F. and Tasso, C. (2013). Extracting keyphrases from web pages. In Agosti, M., Esposito, F., Ferilli, S., and Ferro, N., editors, Digital Libraries and Archives, volume 354 of Communications in Computer and Information Science, pages 93-104. Springer Berlin Heidelberg.
  5. Govindaraju, V. and Ramanathan, K. (2012). Similar document search and recommendation. Journal of Emerging Technologies in Web Intelligence, 4(1):84-93.
  6. Huynh, T., Hoang, K., Do, L., Tran, H., Luong, H. P., and Gauch, S. (2012). Scientific publication recommendations based on collaborative citation networks. In Smari, W. W. and Fox, G. C., editors, CTS, pages 316- 321. IEEE.
  7. Jiang, Y., Jia, A., Feng, Y., and Zhao, D. (2012). Recommending academic papers via users' reading purposes. In Proceedings of the sixth ACM conference on Recommender systems, RecSys 7812, pages 241-244, New York, NY, USA. ACM.
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Paper Citation


in Harvard Style

De Nart D., Tasso C. and Ferrara F. (2013). Personalized Recommendation and Explanation by using Keyphrases Automatically extracted from Scientific Literature . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013) ISBN 978-989-8565-75-4, pages 96-103. DOI: 10.5220/0004539000960103


in Bibtex Style

@conference{kdir13,
author={Dario De Nart and Carlo Tasso and Felice Ferrara},
title={Personalized Recommendation and Explanation by using Keyphrases Automatically extracted from Scientific Literature},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)},
year={2013},
pages={96-103},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004539000960103},
isbn={978-989-8565-75-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval and the International Conference on Knowledge Management and Information Sharing - Volume 1: KDIR, (IC3K 2013)
TI - Personalized Recommendation and Explanation by using Keyphrases Automatically extracted from Scientific Literature
SN - 978-989-8565-75-4
AU - De Nart D.
AU - Tasso C.
AU - Ferrara F.
PY - 2013
SP - 96
EP - 103
DO - 10.5220/0004539000960103