Abstract
The traditional recommender systems are usually oriented to general situations in daily lives (e.g. recommend movies, books, music, news and etc.), but seldom cover the recommendation scenarios for the collaborative team environments. We have done an explorative study on collaborative filtering mechanism for collaborative team environments, which is some kind of multi-dimensional recommender systems problem with consideration of workflow context. This paper proposed 3-dimensional workflow space model, and investigated the new similarities measure between members in workflow space. Then, the new similarities measure is utilized into collaborative filtering for recommender systems in collaborative team environments. At last, the efficiency and usability of the proposed method are validated by experiments referring to a real-world collaborative team of a manufacturing enterprise.
Original language | English |
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Pages (from-to) | 7873-7881 |
Number of pages | 9 |
Journal | Expert Systems with Applications |
Volume | 36 |
Issue number | 4 |
DOIs | |
Publication status | Published - May 2009 |
Externally published | Yes |
Keywords
- Collaborative filtering
- Collaborative team
- Recommender system
- Workflow
ASJC Scopus subject areas
- General Engineering
- Computer Science Applications
- Artificial Intelligence