Content-Based Information Retrieval by Computation of Least Common Subsumers in a Probabilistic Description Logic

Due to the constantly growing number of information sources, intelligent information retrieval becomes a more and more important task. We model information sources by description logic (DL) terminologies. The commonalities of user-speci ed examples can be computed by the least common subsumer (LCS) operator. However, in some cases this operator delivers too general results. In this article we solve this problem by presenting a probabilistic extension of the LCS operator for a probabilistic description logic. By computing gradual commonalities between description logic concepts, this operator serves as a crucial means for content-based information retrieval for all kinds of information sources. We also describe an extension of our operator to consider unwanted information. The probabilistic LCS can be applied for information retrieval in a scenario of multiple information sources.