Abstract
Traditionally, content-based news recommendation is performed by means of the cosine similarity and the TF-IDF weighting scheme for terms occurring in news messages and user profiles. Semantics-driven variants like SF-IDF additionally take into account term meaning by exploiting synsets from semantic lexicons. However, semantics-based weighting techniques are not able to handle – often crucial – named entities, which are often not present in semantic lexicons. Hence, we extend SF-IDF by also employing named entity similarities using Bing page counts. Our proposed method, Bing-SF-IDF, outperforms TF-IDF and its semantics-driven variants in terms of F 1-scores and kappa statistics.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Alias-i: LingPipe 4.1.0 (2008), From: http://alias-i.com/lingpipe
Bing: Bing API 2.0 (2012), http://www.bing.com/developers/s/APIBasics.html
Bollegala, D., Matsuo, Y., Ishizuka, M.: Measuring Semantic Similarity between Words Using Web Search Engines. In: 16th Int. Conf. on World Wide Web (WWW 2007), pp. 757–766. ACM (2007)
Bouma, G.: Normalized (Pointwise) Mutual Information in Collocation Extraction. In: Chiarcos, C., de Castilho, R.E., Stede, M. (eds.) Biennial GSCL Conf. 2009 (GSCL 2009), pp. 31–40. Gunter Narr Verlag, Tübingen (2009)
Capelle, M., Moerland, M., Frasincar, F., Hogenboom, F.: Semantics-Based News Recommendation. In: 2nd Int. Conf. on Web Intelligence, Mining and Semantics (WIMS 2012). ACM (2012)
Cohen, J.: A Coefficient of Agreement for Nominal Scales. Educational and Psychological Measurement 20(1), 37–46 (1960)
Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V.: GATE: A Framework and Graphical Development Environment for Robust NLP Tools and Applications. In: 40th Anniversary Meeting of the Association for Computational Linguistics (ACL 2002), pp. 168–175. Association for Computational Linguistics (2002)
Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press (1998)
Frasincar, F., Borsje, J., Levering, L.: A Semantic Web-Based Approach for Building Personalized News Services. Int. J. E-Business Research 5(3), 35–53 (2009)
Jensen, A.S., Boss, N.S.: Textual Similarity: Comparing Texts in Order to Discover How Closely They Discuss the Same Topics. Bachelor’s Thesis, Technical University of Denmark (2008)
Jiang, J.J., Conrath, D.W.: Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. In: 10th Int. Conf. on Research in Computational Linguistics (ROCLING 1997), pp. 19–33 (1997)
Leacock, C., Chodorow, M.: Combining Local Context and WordNet Similarity for Word Sense Identification. In: WordNet: An Electronic Lexical Database, pp. 265–283. MIT Press (1998)
Lin, D.: An Information-Theoretic Definition of Similarity. In: 15th Int. Conf. on Machine Learning (ICML 1998), pp. 296–304. Morgan Kaufmann (1998)
Moens, M.-F.: Information Extraction: Algorithms and Prospects in a Retrieval Context. Springer (2006)
Resnik, P.: Using Information Content to Evaluate Semantic Similarity in a Taxonomy. In: 14th Int. Joint Conf. on Artificial Intelligence (IJCAI 1995), pp. 448–453. Morgan Kaufmann (1995)
Salton, G., Buckley, C.: Term-Weighting Approaches in Automatic Text Retrieval. Information Processing and Management 24(5), 513–523 (1988)
Toutanova, K., Klein, D., Manning, C.D., Singer, Y.: Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. In: Human Language Technology Conf. of the North American Chapter of the Association for Computational Linguistics (HLTNAACL 2003), pp. 252–259 (2003)
Wu, Z., Palmer, M.S.: Verb Semantics and Lexical Selection. In: 32nd Annual Meeting of the Association for Computational Linguistics (ACL 1994), pp. 133–138. Association for Computational Linguistics (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Hogenboom, F., Capelle, M., Moerland, M. (2014). News Recommendation Using Semantics with the Bing-SF-IDF Approach. In: Parsons, J., Chiu, D. (eds) Advances in Conceptual Modeling. ER 2013. Lecture Notes in Computer Science, vol 8697. Springer, Cham. https://doi.org/10.1007/978-3-319-14139-8_18
Download citation
DOI: https://doi.org/10.1007/978-3-319-14139-8_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-14138-1
Online ISBN: 978-3-319-14139-8
eBook Packages: Computer ScienceComputer Science (R0)