Abstract
This work presents a recommender system of economic news articles. Its objectives are threefold: (i) managing the vocabulary of the economic news domain to improve the system based on the seamlessly intervention of the documentalist (ii) automatically multi-classify the economic new articles and users profiles based on the domain vocabulary, and (iii) recommend the articles by comparing the multi-classification of the articles and profiles of the users. While several solutions exist to recommend news, multi-classify document and compare representations of items and profiles. They are not automatically adaptable to provide a mutual answer to previous points. Even more, existing approaches lacks substantial correlation with the human and in particular with the documentalist perspective.
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Notes
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Number of items correctly considered as relevant to the actual number of relevant articles.
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References
Middleton, S.E., Shadbolt, N.R., De Roure, D.C.: Ontological user profiling in recommender systems. ACM Trans. Inf. Syst. 22(1), 54–88 (2004)
IJntema, W., Goossen, F., Frasincar, F., Hogenboom, F.: Ontology-based news recommendation. In: Proceedings of the 2010 EDBT/ICDT Workshops, EDBT ’10, pp. 16:1–16:6. ACM, New York (2010)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: an open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, CSCW ’94, pp. 175–186. ACM, New York (1994)
Billsus, D., Pazzani, M.J.: A personal news agent that talks, learns and explains. In: Proceedings of the Third Annual Conference on Autonomous Agents, AGENTS ’99, pp. 268–275. ACM, New York (1999)
Balabanović, M., Shoham, Y.: Fab: content-based, collaborative recommendation. Commun. ACM 40(3), 66–72 (1997)
Lops, P., de Gemmis, M., Semeraro, G.: Content-based recommender systems: state of the art and trends. In: Recommender Systems Handbook, pp. 73–105. Springer, Berlin (2011)
Rao, K., Talwar, V.: Application domain and functional classification of recommender systems—a survey. DESIDOC J Libr Inf Technol 28(3), 17–35 (2008)
Kondert, F., Schandl, T., Blumauer, A.: Do controlled vocabularies matter? Survey results, pp. 17–35 (2011)
Cimiano, P.: Ontology Learning and Population from Text: Algorithms, Evaluation and Applications. Springer, Secaucus (2006)
Salton, G., Buckley, C.: Term-weighting approaches in automatic text retrieval. Inf. Process. Manage. 24(5), 513–523 (1988)
Frantzi, K., Ananiadou, S., Mima, H.: Automatic recognition of multi-word terms: the c-value/nc-value method (2000)
Pantel, P., Lin, D.: A statistical corpus-based term extractor. In: Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence, AI ’01, pp. 36–46. Springer, London (2001)
Tsoumakas, G., Katakis, I.: Multi-label classification: an overview. Int J Data Warehouse. Min. 2007, 1–13 (2007)
Bi, W., Kwok, J.T.: Multilabel classification on tree- and dag-structured hierarchies. In: ICML, pp. 17–24 (2011)
Garrido, A.L., Gomez, O., Ilarri, S., Mena, E.: An experience developing a semantic annotation system in a media group. In: Lecture Notes in Computer Science, vol. 7337, pp. 333–338. Springer, Berlin (2012)
Vogrincic, S., Bosnic, Z.: Ontology-based multi-label classification of economic articles. Comput. Sci. Inf. Syst. 8(1), 101–119 (2011)
Tsoumakas, G., Katakis, I., Vlahavas, I.: Effective and efficient multilabel classification in domains with large number of labels. In: ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD08), pp. 30–44 (2008)
Vens, C., Struyf, J., Schietgat, L., Džeroski, S., Blockeel, H.: Decision trees for hierarchical multi-label classification. Mach. Learn. 73(2), 185–214 (2008)
Holden, N., Freitas, A.: Hierarchical classification of g-protein-coupled receptors with a pso/aco algorithm. In: IEEE Swarm Intelligence Symposium (SIS 06) (2006)
Johnson, I., Abcassis, J., Charnomordic, B., Destercke, S., Thomopoulos, R.: Making ontology-based knowledge and decision trees interact: an approach to enrich knowledge and increase expert confidence in data-driven models. In: Lecture Notes in Computer Science, vol. 6291, pp. 304–316. Springer, Berlin (2010)
Elsayed, A.E., El-Beltagy, S.R., Rafea, M., Hegazy, O.: Applying data mining for ontology building. 42nd Annual Conference on Statistics, Computer Science, and Operations Research (2007)
Cantador, I., Bellogn, A., Castells, P.: News@hand: a semantic web approach to recommending news. In: Adaptive Hypermedia and Adaptive Web-Based Systems, Lecture Notes in Computer Science, vol. 5149, pp. 279–283. Springer, Berlin (2008)
Kelly, D., Teevan, J.: Implicit feedback for inferring user preference: a bibliography. SIGIR Forum 37(2), 18–28 (2003)
Kellar, M., Watters, C., Duffy, J., Shepherd, M.: Effect of task on time spent reading as an implicit measure of interest. Proc. Am. Soc. Info. Sci. Technol. 41(1), 168–175 (2004)
Kelly, D., Belkin, N.J.: Reading time, scrolling and interaction: Exploring implicit sources of user preferences for relevance feedback. In: Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’01, pp. 408–409. ACM, New York (2001)
Jawaheer, G., Szomszor, M., Kostkova, P.: Comparison of implicit and explicit feedback from an online music recommendation service. In: Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems, HetRec ’10, pp. 47–51. ACM, New York (2010)
Joachims, T., Granka, L., Pan, B., Hembrooke, H., Radlinski, F., Gay, G.: Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search. ACM Trans. Inf. Syst. 25(2), 7 (Apr 2007)
Salton, G.: The SMART retrieval system—experiments in automatic document processing (1971)
Ahn, J.W., Brusilovsky, P., Grady, J., He, D., Syn, S.Y.: Open user profiles for adaptive news systems: help or harm? p. 11. ACM Press, New York (2007)
Getahun, F., Tekli, J., Chbeir, R., Viviani, M., Yetongnon, K.: Relating RSS news/items. In: Web Engineering, No. 5648 in Lecture Notes in Computer Science, pp. 442–452. Springer, Berlin (Jan 2009)
Voorhees, E.M.: Query expansion using lexical-semantic relations. In: SIGIR 94, pp. 61–69. Springer, London (Jan 1994)
Fellbaum, C.: WordNet: an electronic lexical database. MIT Press, Cambridge (1998)
Werner, D., Silva, N., Bertaux, A., Cruz, C.: Using DL-reasoner for hierarchical multilabel classification applied to economical e-news. In: Accepted for Publication in Proceedings of the Science and Information (SAI) Conference, London (Aug 2014)
Lewis, D.D., Gale, W.A.: A sequential algorithm for training text classifiers. In: SIGIR 94, pp. 3–12. Springer, London (Jan 1994)
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Werner, D., Hassan, T., Bertaux, A., Cruz, C., Silva, N. (2015). Semantic-Based Recommender System with Human Feeling Relevance Measure. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems in Science and Information 2014. SAI 2014. Studies in Computational Intelligence, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-14654-6_11
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