Recommending competent person in a digial ecosystem

Abstract

When participating in activities in a collaborative digital environment, people leave traces. Such traces in return can be used for recommending somebody regarding his/her competency on a given concept. Doing so improves further collaboration because knowing users' specialties ameliorates distributing tasks reasonably. In this article we propose a semantic model taking into account the concepts of activity, trace of interaction and competency. Applying Logistic Regression, we exploit this model to offer recommendation of a competent person in a digital ecosystem.

Using User Contextual Profile for Recommendation in Collaborations

“…Moreover, digital environments facilitate to implicitly gather contextual information. User activity traces could be easily recorded [18], which are associated with the user and the corresponding user group. Therefore, in a digital collaborative environment, users are related to user groups, their collaborators and their activity traces, which are their contextual information derived from their historical collaborations and will be used to calculate the contextual attributes in user contextual profile (TABLE 1, part: Contextual attributes).…”