The phrase "collaboration pattern" is correct and can be used in written English.
It refers to the way in which individuals or groups work together and cooperate to achieve a common goal. It can be used in various contexts, such as business, education, or research. Example: "The team's collaboration pattern was a key factor in their success, as they effectively utilized each member's strengths and communicated efficiently."
The figure also shows the network density without considering the paper with 18 authors, which in fact represents a collaboration pattern outlier.
The results suggest that each collaboration pattern motivates the need for collaboration and encourages the creation of social interaction intentions or situations among users.
For example, a research institute based in a specific country may wish to explore the existing collaboration pattern with a view to assess the potential for collaboration with organisations of other types and organisations based in other countries.
In this paper, we propose Collaboration Pattern Assistant, an information system which is built around the concept of collaboration patterns and is based on an innovative coupling of ontologies with an event driven architecture.
Regarding authors as samples, a mixture distribution means those samples come from different populations, namely the collaboration patterns of the authors with few collaborators and papers differ from those with many collaborators and papers.
By focusing on collaboration in dynamic environments, we explore the utilization of collaboration patterns as models for recurring high-value collaborative tasks, which can be intelligently identified, retrieved and enacted when needed.
Also, researchers that form mostly weak (or strong) ties in the social network may indicate different collaboration patterns, for example, a researcher who has many collaborators through single papers, i.e., that person has collaborated only once with many people.
From those data, we found similar transitivity and assortativity of collaboration patterns as well as the identical distribution type of collaborators per author and that of papers per author, namely a mixture of generalized Poisson and power-law distributions.
We will focus particularly on identifying, modelling, and automating collaboration patterns that increase the scale, user participation, efficiency, and automation of collaborative media creation and management activities.
Collaboration patterns are examined by analyzing the research field correlations.
Do men and women academic faculty vary in their research collaboration patterns and strategies?
