Facilitating networks of information.

Area of Science:

• Information Science
• Computer Science
• Knowledge Management

Background:

• Organizations possess valuable expertise distributed among individuals.
• Efficiently locating subject matter experts is crucial for timely information retrieval and decision-making.
• Existing methods for expert identification may be manual or lack systematic approaches.

Purpose of the Study:

• To develop and evaluate an automated approach for identifying and locating appropriate information sources (experts) within an organization.
• To create a system that matches information requests to individuals based on their expertise profiles.
• To enhance knowledge sharing and accessibility by connecting information seekers with the right experts.

Main Methods:

• Characterizing individual expertise using weighted profiles derived from documents detailing their activities.
• Developing a matching algorithm to compare information requests against expert profiles.
• Implementing a system to identify and present the best-matched expert for a given query.

Main Results:

• Successfully demonstrated an approach to automatically identify subject matter experts based on their documented activities.
• The developed system effectively matches information requests to individuals with the most relevant expertise.
• The system provides the identification and location of the appropriate person as a source of information.

Conclusions:

• The proposed method offers an effective way to automate expert identification and knowledge retrieval.
• Weighted expertise profiles derived from activity documents are a viable basis for matching information needs.
• This approach can significantly improve the efficiency of accessing specialized knowledge within organizations.