TY - JOUR AU - Smyth, Barry AU - Freyne, Jill AU - Coyle, Maurice AU - Briggs, Peter PY - 2011/06/05 Y2 - 2024/03/29 TI - Recommendation as Collaboration in Web Search JF - AI Magazine JA - AIMag VL - 32 IS - 3 SE - Articles DO - 10.1609/aimag.v32i3.2362 UR - https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/2362 SP - 35-45 AB - Recommender systems now play an important role in online information discovery, complementing traditional approaches such as search and navigation, with a more proactive approach to discovery that is informed by the users interests and preferences. To date recommender systems have been deployed within a variety of e-commerce domains, covering a range of products such as books, music, movies, and have proven to be a successful way to convert browsers into buyers. Recommendation technologies have a potentially much greater role to play in information discovery however and in this article we consider recent research that takes a fresh look at web search as a fertile platform for recommender systems research as users demand a new generation of search engines that are less susceptible to manipulation and more responsive to searcher needs and preferences. ER -