Knowledge Pattern Search (KPS)

 Summary

One drawback for current search engines is that they usually sort documents based on the popularity of the documents, therefore they are not suitable to the applications that require looking for new, interesting and unique information which are not popular, for example, the anomaly detection application. Information mining, which typically uncover trends in activity, links, and hidden patterns/relationships is an integral part of knowledge management. One of drawbacks in current information mining is that the mining results are not used in the search, which is a most-frequently used form of knowledge application .

A Knowledge Pattern Search (KPS) architecture combines search and mining: 1) Indexes embedded in collaborative agents are generated from learning and mining knowledge patterns from historical data; 2) Using semantic machine understanding makes it possible to search for new, interesting and unique information rather than popular information.