Glossary
- Collaborative filtering:
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Given a ratings matrix R, representing the preferences of users U for items I, recommend to each user a list of items in descending order of their relevance for the user. The relevance scores are estimated based on ratings of similar users.
- Ratings matrix:
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Assume a set of users U and a set of items I in the recommender system. A user u ∈ U might provide her preference for an item i ∈ I in form of a rating denoted by rating (u, i), which typically takes values in (Adomavicius et al. 2011; Blei et al. 2003). The preferences of users for individual items are represented by a ratings matrix R, where the R u,i entry corresponds to rating (u, i).
- Recommendation:
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A suggestion or proposal to a user for an item, e.g., book, movie, video, news article, that is potentially interesting for the user.
- Recommender system:
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A system or engine that produces recommendations by predicting the...
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Recommended Reading
Shi Y, Larson M, Hanjalic A (2014) Collaborative filtering beyond the user-item matrix: a survey of the state of the art and future challenges. ACM Comput Surv 47(1):3:1–3:45
Stefanidis K, Ntoutsi E, Kondylakis H Information hunting: the many faces of recommendations for data exploration. ACM SIGMOD Blog. http://wp.sigmod.org/?p=1580
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Stefanidis, K., Ntoutsi, E., Kondylakis, H., Velegrakis, Y. (2017). Social-Based Collaborative Filtering. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_110171-1
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DOI: https://doi.org/10.1007/978-1-4614-7163-9_110171-1
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