1. What is it?
OU Expert Search (OUES) is a document content based
indexing and search engine, and has a Google-like search interface, but OUES
finds people instead of documents. Given a search query topic such as
"java programming", OUES finds a ranked list of experts from
current OU employees who have expertise on the search query topic. Documents
supporting expertise are presented and expert list is integrated with the OU
2. Who's doing it?
There are many information retrieval groups in the world
are working on this now. In KMi, Dr. Jianhan Zhu, Dr. Dawei
Song, Prof. Marc Eisenstadt, Prof. Enrico Motta, and Prof.
Stefan Ruger are working on OUES. In TREC (Text REtrieval Conference) 2006 expert search task, KMi was
ranked top among all 23 internationally renowned research groups across all
major Information Retrieval measures.
How does it work?
OUES indexes documents on the OU intranet periodically for
expert search. Given a search query, OUES estimates the relevance of a
person' expertise on the query topic based on the relevance of documents to
the topic and the relevance of the person to the topic in these relevant
Why is it
Expert finding is very important in the distributed environment
like the OU where students and media liaisons are looking for experts over
the distance. But it is hard to construct a complete expertise database for
OU and such database gets out of date quickly. On the other hand, OUES can
provide speedy, most up to date, and accurate expertise information at zero
or very low cost.
What are the
People may prefer not to be found, but we can add a privacy
filter and ensure that this information is only accessible on the OU
6. Where is it going?
We are working on a smoothly integrated search system
consisting of OUES and current Ultraseek powered OU
intranet search. We are also working on integrating OUES with current OU
expertise database and domain knowledge.
What are the implications
for teaching and learning?
OUES can help teaching and learning by providing advanced
expertise search service. For example, (i) students
could use OUES to find subject experts (who have granted 'visibility'); (ii)
OU course designers can use OUES to assemble a group of experts to work on a
course; (iii) on-site experts can be identified to respond to
Prof. Marc Eisenstadt, Dr. Jianhan Zhu
Further reading and
- TREC: Text Retrieval Conference http://trec.nist.gov/
Enterprise Track Wiki site http://www.ins.cwi.nl/projects/trec-ent/wiki/index.php/Main_Page
Corpus used for Enterprise Search task http://research.microsoft.com/users/nickcr/w3c-summary.html
TREC official publications (2006 proceedings will appear soon) http://trec.nist.gov/pubs.html
Zhu's publication page: http://kmi.open.ac.uk/people/jianhan/publication.htm
10. OUES Screenshot: