Recommender Systems: Introduction and Challenges (original) (raw)

2015, Recommender Systems Handbook

Recommender Systems (RSs) are software tools and techniques that provide suggestions for items that are most likely of interest to a particular user [17, 41, 42]. The suggestions relate to various decision-making processes, such as what items to buy, what music to listen to, or what online news to read. "Item" is the general term used to denote what the system recommends to users. An RS normally focuses on a specific type of item (e.g., CDs or news) and, accordingly its design, its graphical user interface, and the core recommendation technique used to generate the recommendations are all customized to provide useful and effective suggestions for that specific type of item. RSs are primarily directed toward individuals who lack the sufficient personal experience or competence in order to evaluate the potentially overwhelming number of alternative items that a website, for example, may offer [42]. A prime example is a book recommender system that assists users in selecting a book to read. On the popular website, Amazon.com, the site employs an RS to personalize the online store for each customer [32]. Since recommendations are usually personalized, different users or user groups benefit from diverse, tailored suggestions. In addition, there are also non-personalized recommendations. These are much simpler to generate and are normally featured in magazines or newspapers. Typical examples