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With the rise of short-lived workgroups, extracting tacit knowledge from group interactions becomes crucial. Utilizing data from messaging, discussions, and document access in groupware systems, this project aims to uncover expertise, analyze group dynamics, and aid in sensemaking and attention management. By employing social network analysis, clustering, and classification methods, we seek to enhance collaboration and information sharing across various boundaries in organizations.
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Tacit Knowledge Mining John CannyComputer Science DivisionUC Berkeley
Motivation • People often collaborate across geographic, cultural and disciplinary boundaries. • Workgroups are more short-lived today. There is less time to learn each other’s skills sets, to develop trust, and a “voice” within the group. • On the other hand, there is a wealth of information available in groupware systems about people’s interactions with each other and with data.
An opportunity • We know that much of the useful knowledge in a group or organization is “tacit”. Can we recover and use tacit knowledge? • Human knowledge and knowhow is difficult and expensive to codify. • But the knowledge encoded in activity data may be less so. Examples: expertise discovery, group structure, document dependencies.
Platform: Lotus Notes for now • Data sources: • Direct messaging: sender, receiver, time, duration.. • Topical discussions or threaded email. • Document access (by links or directories) • Document search (by text queries) • Annotations on documents.
Analysis methods: • Social Networks. Centrality measures for estimating authority and prestige.
Analysis methods: • Clustering. Discovering tacit groups, and related sets of documents. • Classification. Use a knowledge hierarchy to classify documents, and compute expertise profiles.
What we want to assist: • Expertise discovery. Expertise profiles include authority in each area. • Document access. We compute document authorities and use them in ranking. • Group dynamics. Does the communication network contain any problematic structures?
What we want to assist: • Sensemaking, document context. Record the document creation process. Prioritize records. • Attention management. Infer a current task and adjust awareness of documents and other people according to their proximity to the task. • Perspectives. Organize annotations (when available) on a document according to the expertise of author and annotator.
