TY - JOUR AU - Falkner, Andreas AU - Felfernig, Alexander AU - Haag, Albert PY - 2011/10/31 Y2 - 2024/03/28 TI - Recommendation Technologies for Configurable Products JF - AI Magazine JA - AIMag VL - 32 IS - 3 SE - Articles DO - 10.1609/aimag.v32i3.2369 UR - https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/2369 SP - 99-108 AB - State of the art recommender systems support users in the selection of items from a predefined assortment (for example, movies, books, and songs). In contrast to an explicit definition of each individual item, configurable products such as computers, financial service portfolios, and cars are repreĀ¬sented in the form of a configuration knowledge base that describes the properties of allowed instances. Although the knowledge representation used is different compared to non-confiĀ¬gurable products, the decision support requirements remain the same: users have to be supported in finding a solution that fits their wishes and needs. In this article we show how recommendation technologies can be applied for supporting the configuration of products. In addition to existing approaches we discuss relevant issues for future research. ER -