A Connection-Centric Survey of Recommender Systems Research
| dc.creator | Perugini, Saverio | |
| dc.creator | Goncalves, Marcos Andre | |
| dc.creator | Fox, Edward A. | |
| dc.date | 2002-05-22 | |
| dc.date | 2003-07-30 | |
| dc.date.accessioned | 2026-07-25T16:33:59Z | |
| dc.description | Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in recommender systems grew out of information retrieval and filtering, the topic has steadily advanced into a legitimate and challenging research area of its own. Recommender systems have traditionally been studied from a content-based filtering vs. collaborative design perspective. Recommendations, however, are not delivered within a vacuum, but rather cast within an informal community of users and social context. Therefore, ultimately all recommender systems make connections among people and thus should be surveyed from such a perspective. This viewpoint is under-emphasized in the recommender systems literature. We therefore take a connection-oriented viewpoint toward recommender systems research. We posit that recommendation has an inherently social element and is ultimately intended to connect people either directly as a result of explicit user modeling or indirectly through the discovery of relationships implicit in extant data. Thus, recommender systems are characterized by how they model users to bring people together: explicitly or implicitly. Finally, user modeling and the connection-centric viewpoint raise broadening and social issues--such as evaluation, targeting, and privacy and trust--which we also briefly address. | |
| dc.description | Based on the comments from reviewers, we have made modifications to our article, including the following: Shifted the focus of the survey completely to recommender system research rather than recommendation and personalization and subsequently changed the title to "A Connection-Centric Survey of Recommender Systems Research." Now only cite the most seminal works in this area and as a result have reduced the references significantly from over 200 to 120 | |
| dc.identifier | https://arxiv.org/abs/cs/0205059 | |
| dc.identifier | http://arxiv.org/abs/cs/0205059 | |
| dc.identifier.uri | https://dspace.dare.co.zw/handle/123456789/42314 | |
| dc.subject | Information Retrieval | |
| dc.subject | Human-Computer Interaction | |
| dc.subject | A.1;H.1.0;H.1.2;H.3.0;H.3.3;H.3.4;H.3.5;H.4.2;H.5.2;H.5.4 | |
| dc.title | A Connection-Centric Survey of Recommender Systems Research | |
| dc.type | text |