By Jan Borchers (auth.), Wolfgang Nejdl, Judy Kay, Pearl Pu, Eelco Herder (eds.)
This booklet constitutes the refereed court cases of the fifth overseas convention on Adaptive Hypermedia and Adaptive Web-Based structures, AH 2008, held in Hannover, Germany in July 2008.
The 24 revised complete papers and 26 revised brief papers provided including abstracts of three keynotes, four demo papers, and eleven doctoral consortium posters have been conscientiously reviewed and chosen from 185 papers submitted. The papers concentrate on pioneering theories, innovations, and leading edge applied sciences to supply dynamic personalization, version, and contextualization of hypermedia assets and services.
Read Online or Download Adaptive Hypermedia and Adaptive Web-Based Systems: 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings PDF
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Extra info for Adaptive Hypermedia and Adaptive Web-Based Systems: 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings
The previous methods exploit statistics of the users’ rating data to compute item weights. The last method we present here computes weights using description of the items. In the movie recommendation data set, which we are going to use for our experiments, movies are tagged with movie genres. Hence, we make the assumption that the larger the number of common tags, here genres, the higher is the dependency. The weight of the predictive item i for a prediction of the ratings of the target item j is given by: T = wji # comon tags of items i and j #tags Genre weighting is related to the methods presented in  where item description information is used to selectively choose the items to be used in the user-to-user correlation.
Visualizing personal relations in online communities. , Smyth, B. ) AH 2006. LNCS, vol. 4018, pp. 223–233. Springer, Heidelberg (2006) 5. : Social information ﬁltering: Algorithms for automating “word of mouth”. In: Proceedings of ACM CHI 1995 Conference on Human Factors in Computing Systems, vol. 1, pp. 210–217 (1995) 6. : Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction 12(4), 331–370 (2002) 7. : Open corpus adaptive educational hypermedia. , Nejdl, W.
355–359. Springer, Heidelberg (2007) 13. org/ 14. : Evaluating collaborative ﬁltering recommender systems. ACM Trans. Inf. Syst. 22(1), 5–53 (2004) 15. com/ ˇ 16. : Theoretical and empirical analysis of relieﬀ and rrelieﬀ. Mach. Learn. edu Abstract. The rapidly growing amount of heterogeneous semi-structured data available on the Web is creating a need for simple and universal access methods. For this purpose, we propose exploiting the notion of UNSpecified Ontology (UNSO), where the data objects are described using a list of attributes and their values.