%0 Journal Article %1 WANG2008283 %A Wang, Yiwen %A Stash, Natalia %A Aroyo, Lora %A Gorgels, Peter %A Rutledge, Lloyd %A Schreiber, Guus %D 2008 %J Journal of Web Semantics %K art-recommender recommender semantic-web %N 4 %P 283-290 %R https://doi.org/10.1016/j.websem.2008.09.002 %T Recommendations based on semantically enriched museum collections %U https://www.sciencedirect.com/science/article/pii/S1570826808000681 %V 6 %X This article presents the CHIP demonstrator11http://www.chip-project.org/demo/. for providing personalized access to digital museum collections. It consists of three main components: Art Recommender, Tour Wizard, and Mobile Tour Guide. Based on the semantically enriched Rijksmuseum Amsterdam22http://www.rijksmuseum.nl. collection, we show how Semantic Web technologies can be deployed to (partially) solve three important challenges for recommender systems applied in an open Web context: (1) to deal with the complexity of various types of relationships for recommendation inferencing, where we take a content-based approach to recommend both artworks and art-history topics; (2) to cope with the typical user modeling problems, such as cold-start for first-time users, sparsity in terms of user ratings, and the efficiency of user feedback collection; and (3) to support the presentation of recommendations by combining different views like a historical timeline, museum map and faceted browser. Following a user-centered design cycle, we have performed two evaluations with users to test the effectiveness of the recommendation strategy and to compare the different ways for building an optimal user profile for efficient recommendations. The CHIP demonstrator received the Semantic Web Challenge Award (third prize) in 2007, Busan, Korea.

@article{WANG2008283, abstract = {This article presents the CHIP demonstrator11http://www.chip-project.org/demo/. for providing personalized access to digital museum collections. It consists of three main components: Art Recommender, Tour Wizard, and Mobile Tour Guide. Based on the semantically enriched Rijksmuseum Amsterdam22http://www.rijksmuseum.nl. collection, we show how Semantic Web technologies can be deployed to (partially) solve three important challenges for recommender systems applied in an open Web context: (1) to deal with the complexity of various types of relationships for recommendation inferencing, where we take a content-based approach to recommend both artworks and art-history topics; (2) to cope with the typical user modeling problems, such as cold-start for first-time users, sparsity in terms of user ratings, and the efficiency of user feedback collection; and (3) to support the presentation of recommendations by combining different views like a historical timeline, museum map and faceted browser. Following a user-centered design cycle, we have performed two evaluations with users to test the effectiveness of the recommendation strategy and to compare the different ways for building an optimal user profile for efficient recommendations. The CHIP demonstrator received the Semantic Web Challenge Award (third prize) in 2007, Busan, Korea.}, added-at = {2023-06-11T20:05:14.000+0200}, author = {Wang, Yiwen and Stash, Natalia and Aroyo, Lora and Gorgels, Peter and Rutledge, Lloyd and Schreiber, Guus}, biburl = {https://www.bibsonomy.org/bibtex/27a70d895b3b7e52c0768f2280a641b59/brusilovsky}, description = {Recommendations based on semantically enriched museum collections - ScienceDirect}, doi = {https://doi.org/10.1016/j.websem.2008.09.002}, interhash = {cd6f7802383230d5f28578002d724ca2}, intrahash = {7a70d895b3b7e52c0768f2280a641b59}, issn = {1570-8268}, journal = {Journal of Web Semantics}, keywords = {art-recommender recommender semantic-web}, note = {Semantic Web Challenge 2006/2007}, number = 4, pages = {283-290}, timestamp = {2023-06-11T20:05:14.000+0200}, title = {Recommendations based on semantically enriched museum collections}, url = {https://www.sciencedirect.com/science/article/pii/S1570826808000681}, volume = 6, year = 2008 }