I have previously described what I termed the various generations of solutions to the common challenge of workers finding connecting with or finding co-workers within an enterprise. My most recent post described the fourth generation solution – which enables users to search and connect using much more than simple administrative terms (name, email, address, etc.) for the search.
Over my next couple of posts, I will provide a write-up of a proof of concept implementation I’ve assembled that meets a lot of the need for this with what I believe to be relatively minimal investment.
The follow represent the goals I’ve set for myself in this proof of concept:
- Demonstrate the usefulness of a people search based on attributes of workers other than purely administrative data – things like their skills, competencies, work, interests, etc.
- Demonstrate the feasibility of discerning the skills, competencies, work and/or interests through a means that does not depend on maintenance of data by the worker (which, from my experience, is not long-term maintainable).
- More specifically, provide a test bed to explore different algorithms for discovering keywords important keywords for people.
- Demonstrate the feasibility of discovering keywords using only data that is generally “publicly visible” within an enterprise.
- Provide a path for integrating manually-maintained skills data (if that were to be collected), or any other data (possibly including tags applied by co-workers as seen in IBM’s Dog Ear project).
- Provide a compelling user experience that draws people in and gives people a visual presentation of what another person is “about” (what describes them).
- Provide a solution that provides, at minimum, the equivalent of a 3rd generation solution (in other words you can find that worker based on their administrative data).
Also, I wanted to say that part of the inspiration for this proof of concept came from a session I attended at Enterprise Search Summit 2007 as presented by Trent Parkhill. In his session, he described a mechanism where submissions to a company’s repository would be tagged with the names of participants in the project that produced the document as a deliverable. Then, when users were searching for content, there was a secondary search that produced a list of people associated with the terms and / or documents found by the user’s search. I’ve kind of turned that around and treated the people as being tagged by the keywords of the items they produce.
In my next post, I will describe the overall design of my proof of concept.