Collaborative information retrieval (CIR)
The New Review of Information Behaviour Research
SearchTogether: an interface for collaborative web search
Proceedings of the 20th annual ACM symposium on User interface software and technology
A survey of collaborative web search practices
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Algorithmic mediation for collaborative exploratory search
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Collaborative Information Retrieval in an information-intensive domain
Information Processing and Management: an International Journal
Collaborative Search: Who, What, Where, When, Why, and How
Collaborative Search: Who, What, Where, When, Why, and How
Awareness in collaborative information seeking
Journal of the American Society for Information Science and Technology
Recommender Systems Handbook
3rd international workshop on collaborative information retrieval (CIR2011)
Proceedings of the 20th ACM international conference on Information and knowledge management
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Collaborative information retrieval is an emerging research field in charge of establishing techniques and methods to satisfy the shared information needs of groups of people that work together as a team, starting from the extension of the information seeking and retrieval process with the knowledge about the queries, the context, and the explicit collaboration habits among them. Unfortunately, in broad online communities that besides grow continuously (e.g., social networks, e-learning systems, or peer-to-peer networks) can be difficult the conformation of these groups, or all benefits can not be obtained, for the lack of transparency among users' seeking tasks in distributed environments. To address this issue, we propose in this work a recommender agent based on latent semantic indexing formalism to assist the users that search alone to find and join to groups with similar information needs. With this mechanism, a user can change easily her solo search intent to explicit collaborative search. We assume as hypothesis that both, the group and the new member will benefit. To validate our hypothesis we have designed an experiment with twelve groups of students in the context of search-driven software development.