Abstract
Personalization, aiming at supporting users individually, according to their individual needs and prerequisites, has been discussed in a number of domains including learning, search, or information retrieval. In the field of human–computer interaction, personalization also bears high potential as users might exhibit varying and strongly individual preferences and abilities related to interaction. For instance, there is a good amount of work on personalized or adaptive user interfaces (also under the notion of intelligent user interfaces). Personalized human–computer interaction, however, does not only subsume approaches to support the individual user, it also bears high potential if applied to collaborative settings, for example, through supporting the individuals in a group as well as the group itself (considering all of its special dynamics). In collaborative settings (remote or co-located), there generally is a number of additional challenges related to human-to-human collaboration in a group, such as group communication, awareness or territoriality, device or software tool selection, or selection of collaborators. Personalized Collaborative Systems thus attempt to tackle many of these challenges. For instance, there are collaborative systems that recommend tools, content, or team constellations. Such systems have been suggested in different domains and different collaborative settings and contexts. In most cases, these systems explicitly focus on a certain aspect of personalized collaboration support (such as team composition). This article provides a broader, concise overview of existing approaches to Personalized Collaborative Systems based on a systematic literature review considering the ACM Digital Library.
Highlights
Personalized Collaborative Systems (PCS) are a relatively young research field at the intersection between human–computer interaction (HCI), computer-supported cooperative work (CSCW), psychology, and sociology and more technically oriented fields, such as User Modeling, Recommender Systems, Machine Learning, and Data Mining
Query Results Running our query on December 12, 2019 on the ACM Digital Library (DL) yielded a corpus of 345 results containing 34 articles from journals and 310 from conference proceedings
We summarize our insights and findings obtained through the systematic analysis of the 36 papers that remained in our final data set
Summary
Personalized Collaborative Systems (PCS) are a relatively young research field at the intersection between human–computer interaction (HCI), computer-supported cooperative work (CSCW), psychology, and sociology and more technically oriented fields, such as User Modeling, Recommender Systems, Machine Learning, and Data Mining. This disciplinary breadth makes PCS highly interesting for several application and research domains, on the one hand, but harder to capture in its entirety, on the other hand. We aim at (i) providing a concise overview of PCS, (ii) establishing common ground and a shared understanding based on the intersection of work in different domains, and (iii) suggesting a general definition of PCS. We provide relevant definitions related to these fields to be referred to throughout this article
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