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Bing-CF-IDF+: A Semantics-Driven News Recommender System

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Book cover Advanced Information Systems Engineering (CAiSE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11483))

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Abstract

With the ever growing amount of news on the Web, the need for automatically finding the relevant content increases. Semantics-driven news recommender systems suggest unread items to users by matching user profiles, which are based on information found in previously read articles, with emerging news. This paper proposes an extension to the state-of-the-art semantics-driven CF-IDF+ news recommender system, which uses identified news item concepts and their related concepts for constructing user profiles and processing unread news messages. Due to its domain specificity and reliance on knowledge bases, such a concept-based recommender neglects many highly frequent named entities found in news items, which contain relevant information about a news item’s content. Therefore, we extend the CF-IDF+ recommender by adding information found in named entities, through the employment of a Bing-based distance measure. Our Bing-CF-IDF+ recommender outperforms the classic TF-IDF and the concept-based CF-IDF and CF-IDF+ recommenders in terms of the \(F_1\)-score and the Kappa statistic.

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References

  1. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)

    Article  Google Scholar 

  2. Banerjee, S., Pedersen, T.: An adapted lesk algorithm for word sense disambiguation using wordnet. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 136–145. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45715-1_11

    Chapter  Google Scholar 

  3. Bing: Bing API 2.0. Whitepaper (2018). http://www.bing.com/developers/s/APIBasics.html

  4. Bouma, G.: Normalized (pointwise) mutual information in collocation extraction. In: Chiarcos, C., de Castilho, R.E., Stede, M. (eds.) Biennial GSCL Conference 2009 (GSCL 2009), pp. 31–40. Gunter Narr Verlag Tübingen (2009)

    Google Scholar 

  5. Burke, R.: Hybrid recommender systems: survey and experiments. User Model. User-Adapt. Interact. 12(4), 331–370 (2002)

    Article  Google Scholar 

  6. Capelle, M., Moerland, M., Frasincar, F., Hogenboom, F.: Semantics-based news recommendation. In: Akerkar, R., Bădică, C., Dan Burdescu, D. (eds.) 2nd International Conference on Web Intelligence, Mining and Semantics (WIMS 2012). ACM (2012)

    Google Scholar 

  7. Capelle, M., Moerland, M., Hogenboom, F., Frasincar, F., Vandic, D.: Bing-SF-IDF+: a hybrid semantics-driven news recommender. In: Wainwright, R.L., Corchado, J.M., Bechini, A., Hong, J. (eds.) 30th Symposium on Applied Computing (SAC 2015), Web Technologies Track, pp. 732–739. ACM (2015)

    Google Scholar 

  8. Cohen, J.: A coefficient of agreement for nominal scales. Educ. Psychol. Meas. 20(1), 37–46 (1960)

    Article  Google Scholar 

  9. de Koning, E., Hogenboom, F., Frasincar, F.: News recommendation with CF-IDF+. In: Krogstie, J., Reijers, H.A. (eds.) CAiSE 2018. LNCS, vol. 10816, pp. 170–184. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91563-0_11

    Chapter  Google Scholar 

  10. Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)

    Book  Google Scholar 

  11. Frasincar, F., Borsje, J., Levering, L.: A semantic web-based approach for building personalized news services. Int. J. E-Bus. Res. 5(3), 35–53 (2009)

    Article  Google Scholar 

  12. Goossen, F., IJntema, W., Frasincar, F., Hogenboom, F., Kaymak, U.: News personalization using the CF-IDF semantic recommender. In: Akerkar, R. (ed.) International Conference on Web Intelligence, Mining and Semantics (WIMS 2011). ACM (2011)

    Google Scholar 

  13. IJntema, W., Goossen, F., Frasincar, F., Hogenboom, F.: Ontology-based news recommendation. In: Daniel, F., et al. (eds.) International Workshop on Business intelligencE and the WEB (BEWEB 2010) at 13th International Conference on Extending Database Technology and Thirteenth International Conference on Database Theory (EDBT/ICDT 2010). ACM (2010)

    Google Scholar 

  14. Jannach, D., Resnick, P., Tuzhilin, A., Zanker, M.: Recommender systems - beyond matrix completion. Commun. ACM 59(11), 94–102 (2016)

    Article  Google Scholar 

  15. 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)

    Google Scholar 

  16. Jones, K.S.: A statistical interpretation of term specificity and its application in retrieval. J. Doc. 28(1), 11–21 (1972)

    Article  Google Scholar 

  17. Moerland, M., Hogenboom, F., Capelle, M., Frasincar, F.: Semantics-based news recommendation with SF-IDF+. In: Camacho, D., Akerkar, R., Rodríguez-Moreno, M.D. (eds.) 3rd International Conference on Web Intelligence, Mining and Semantics (WIMS 2013). ACM (2013)

    Google Scholar 

  18. Robal, T., Haav, H.-M., Kalja, A.: Making web users’ domain models explicit by applying ontologies. In: Hainaut, J.-L., et al. (eds.) ER 2007. LNCS, vol. 4802, pp. 170–179. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76292-8_20

    Chapter  Google Scholar 

  19. Robal, T., Kalja, A.: Conceptual web users’ actions prediction for ontology-based browsing recommendations. In: Papadopoulos, G.A., Wojtkowski, W., Wojtkowski, W.G., Wrycza, S., Zupancic, J. (eds.) ISD 2008, pp. 121–129. Springer, Boston (2010). https://doi.org/10.1007/b137171_13

    Chapter  Google Scholar 

  20. Robal, T., Kalja, A.: Applying user domain model to improve Web recommendations. In: Caplinskas, A., Dzemyda, G., Lupeikiene, A., Vasilecas, O. (eds.) Databases and Information Systems VII - Selected Papers from the Tenth International Baltic Conference (DB&IS 2012). Frontiers in Artificial Intelligence and Applications, vol. 249, pp. 118–131. IOS Press (2013)

    Google Scholar 

  21. Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manag. 24(5), 513–523 (1988)

    Article  Google Scholar 

  22. Sekine, S., Ranchhod, E. (eds.): Named Entities: Recognition, Clasification and Use. John Benjamins Publishing Company, Amsterdam (2009)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Erasmus University Rotterdam, Burgemeester Oudlaan 50, 3062 PA, Rotterdam, The Netherlands

    Emma Brocken, Aron Hartveld, Emma de Koning, Thomas van Noort, Frederik Hogenboom & Flavius Frasincar

  2. Tallinn University of Technology, Ehitajate tee 5, 19086, Tallinn, Estonia

    Tarmo Robal

Authors
  1. Emma Brocken
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  2. Aron Hartveld
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  3. Emma de Koning
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  4. Thomas van Noort
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  5. Frederik Hogenboom
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  6. Flavius Frasincar
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  7. Tarmo Robal
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Corresponding author

Correspondence to Flavius Frasincar .

Editor information

Editors and Affiliations

  1. University of Trento, Trento, Italy

    Paolo Giorgini

  2. University of St. Gallen, St. Gallen, Switzerland

    Barbara Weber

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Brocken, E. et al. (2019). Bing-CF-IDF+: A Semantics-Driven News Recommender System. In: Giorgini, P., Weber, B. (eds) Advanced Information Systems Engineering. CAiSE 2019. Lecture Notes in Computer Science(), vol 11483. Springer, Cham. https://doi.org/10.1007/978-3-030-21290-2_3

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  • DOI: https://doi.org/10.1007/978-3-030-21290-2_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21289-6

  • Online ISBN: 978-3-030-21290-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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