Download
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
PeopleFinder: Searching for People, not just for Documents PowerPoint Presentation
Download Presentation
PeopleFinder: Searching for People, not just for Documents

PeopleFinder: Searching for People, not just for Documents

63 Views Download Presentation
Download Presentation

PeopleFinder: Searching for People, not just for Documents

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. PeopleFinder: Searching for People, not just for Documents Technologies for Knowledge Sharing ICT-Centre CSIRO Alistair McLean, Anne-Marie Vercoustre, Mingfang Wu {firstname.lastname}@csiro.au Goal To find out experts in a company, on a given subject, and to be able to contact them. To provide evidence that they are appropriate experts. Although documents are a valuable resource, for many questions it is necessary to find the right person rather than the right document. Information Need Search Expert Details + Evidence A simple process of Web search

  2. Example: Searching for Experts in Virtual Environments Home page More evidences Corporate structure Ranked experts for “Virtual Environments”

  3. Benefits • People Finder provides automatic and rapid identification of experts: • Without manual maintenance of employee expertise list • Without any specialised user training • With contact details and place in the corporate organisation chart • With supporting evidence so the degree of expertise can be judged • Decisions are based on the documents that staff load onto the corporate Intranet and projects they are involved in; this automatically tracks expertise as staff develop. Approach People Finder leverages on structured and unstructured information: • Unstructured information: Intranet and extranet documents • Structured information: Corporate data (groups, projects description and memberships) • Expertise evidence is based on: • Documents that contain people’ names • Documents that are linked to project pages (not too far down) • weight on Home pages, project pages and related pages (weight decreases with distance)

  4. 3 3 P@ P@ 1 1 5 5 10 10 Evaluation Preliminary Finding • Test Collection (April 2003): • CSIRO-CMIS Intranet/Extranet (html) • List of staff, Home Pages • Groups, Projects, Project descriptions (XML) • Publications (XML) • Business development contact database (mails) • Leveraging on structure increases significantly the precision • Adding more structured documents does not always increase precision 0.405 0.315 0.257 0.172 Base 0.209 0.187 0.159 0.125 Web Web + XML data New 0.405 0.315 0.257 0.172 0.412 0.335 0.273 0.207 (%) (93.8) (68.4) (61.6) (37.6) (1.7%) (6.3%) (6.2%) (20.3%) P< (3.2E-5) (5.3E-6) (4.6E-7) (5.7E-5) P< (0.84) (0.31) (0.23) (0.0003) Comparison between two collections (with and without XML documents) by using the new system. Average precision for base system without structured data and new system over the Web collection.