Understanding Cooperative Learning in Context-Aware Recommender Systems : A User-System Interaction Perspective
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
---|---|
Title of host publication | 38th International Conference on Information Systems (ICIS 2017) |
Subtitle of host publication | Transforming Society with Digital Innovation |
Publisher | Association for Information Systems |
Pages | 4059-4069 |
Volume | 6 |
ISBN (Print) | 9781510853690, 9780996683159 |
Publication status | Published - Dec 2017 |
Publication series
Name | ICIS: Transforming Society with Digital Innovation |
---|
Conference
Title | 38th International Conference on Information Systems (ICIS 2017) |
---|---|
Location | COEX, Convention and Exhibition Center |
Place | Korea, Republic of |
City | Seoul |
Period | 10 - 13 December 2017 |
Link(s)
Document Link | Links
|
---|---|
Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85126505310&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(d07f144e-25a6-47eb-92a8-a579a248f86d).html |
Abstract
Context-Aware Recommender Systems (CARSs) are becoming commonplace. Yet, there is a paucity of studies that investigates how such systems could affect usage behavior from a user-system interaction perspective. Building on the Social Interdependence Theory (SIT), we construct a research model that posits cooperative learning as a trait of users’ interactions with CARSs and outline a proposed empirical study for validating the hypothesized relationships in this model. Specifically, we draw on interdependencies in human-machine relationships to postulate positive interdependence as an antecedent of users’ promotive interaction with CARSs, which in turn, dictates the performance of such recommender systems. Furthermore, we introduce scrutability features as design interventions that can be harnessed by developers to mitigate the impact of users’ promotive interaction on the performance of CARSs.
Research Area(s)
- Context-aware, Cooperative learning, Human-machine relationships, Recommender systems, User-system interaction
Citation Format(s)
Understanding Cooperative Learning in Context-Aware Recommender Systems : A User-System Interaction Perspective. / Jiang, Na; Tan, Chee-Wee; Wang, Weiquan; Liu, Hefu; Gu, Jibao.
38th International Conference on Information Systems (ICIS 2017): Transforming Society with Digital Innovation. Vol. 6 Association for Information Systems, 2017. p. 4059-4069 (ICIS: Transforming Society with Digital Innovation).Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review