Ranking Issues for Information Integration

Ranking of query/search answers, although introduced by early information retrieval systems, has become mandatory for Internet searches. When the answers of a query or search are varying in quality and are large in numbers, it is necessary to rank/order these answers based on some criteria. From a users' viewpoint, ranking is extremely useful especially when associated with the retrieval of a few (top-k) answers. Currently, the notion of ranking is being applied to database query answers (ordering based on user criteria) in order to retrieve top-k answers. One of the challenges is to push ranking computation into the query processing stage to make it efficient and eliminate post processing operations. In this paper, we argue that top-k answers and ranking will become mandatory as well for searches that involve integration of information from heterogeneous domains. However, it is not clear how ranking can be supported as sources are autonomous and support different characteristics and capabilities. We analyze possible alternatives for supporting ranking while answering queries in this context and propose potential approaches. The discussion is in the context of InfoMosaic. a framework proposed by the authors for information integration.