Abstract: An information retrieval system processes user input queries, and identifies query feedback, including ranking the query feedback, to facilitate the user in re-formatting a new query. A knowledge base, which comprises a plurality of nodes depicting terminological concepts, is arranged to reflect conceptual proximity among the nodes. The information retrieval system processes the queries, identifies topics related to the query as well as query feedback terms, and then links both the topics and feedback terms to nodes of the knowledge base with corresponding terminological concepts. At least one focal node is selected from the knowledge base based on the topics to determine a conceptual proximity between the focal node and the query feedback nodes. The query feedback terms are ranked based on conceptual proximity to the focal node. A content processing system that identifies themes from a corpus of documents for use in query feedback processing is also disclosed.

Abstract: An information retrieval system generates query feedback terminology for an input query based on a corpus of documents and the input query. Potential query feedback terms are identified through the corpus of documents for use as query feedback in the information retrieval system. To process a query, which includes at least one query term, co-occurrence signatures for “N” query feedback terms are generated. An N×N matrix of the co-occurrence signatures depict patterns of semantic distance and conceptual proximity among the “N” query feedback terms. The N×N matrix is processed to reduce the number of the entries in the signature to an N×M matrix while preserving the co-occurrence distance characteristics among the signatures. Query feedback terms with co-occurrence signatures, which compare with co-occurrence signatures of the query term in a predetermined manner, are selected as query feedback.

Abstract: An information retrieval system generates hierarchical query feedback to a user to facilitate the user in reformulating the query. The information retrieval system, which supports both text and theme queries, includes a knowledge base comprising a plurality of nodes of terminology, arranged hierarchically, that reflect associations among the terminology. For the hierarchical query feedback terms, the information retrieval system selects terminology that broadens and narrows the query terms by selecting parent nodes and child nodes, respectively, of the nodes for terminology that corresponds to the terms of the query. The information retrieval system also selects terminology that is generally related to the query terms by selecting nodes of the knowledge base that are cross linked to the nodes for terminology that corresponds to the terms of the query.