In this paper, a competition-based connectionist model for diagnostic problem-solving is adapted to information retrieval. In this model, we treat documents as \disorders" an...
Abstract The explosion of content in distributed information retrieval (IR) systems requires new mechanisms to attain timely and accurate retrieval of unstructured text. In this pa...
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Relevance feedback is a powerful technique for content-based image retrieval. Many parameter estimation approaches have been proposed for relevance feedback. However, most of them ...
Focusing on the context of XML retrieval, in this paper we propose a general methodology for managing structured queries (involving both content and structure) within any given st...