Extending Retrieval with Stepping Stones and Pathways

This project researches an alternative interpretation of user queries and presentation of the results. Instead of returning a ranked list of documents, the result of a query is a connected network of chains of evidence. Each chain is made of a sequence of additional concepts (stepping stones). Each concept in the sequence is logically connected to the next and previous one, and the chains provide a rationale (a pathway) for the connection between the two original concepts. To increase the user’s understanding of the chain, it is desirable that the stepping stones be justified by concrete documents, along with the connections (relationships) among those documents.

[1]  W. Scott Spangler,et al.  Clustering hypertext with applications to web searching , 2000, HYPERTEXT '00.

[2]  Neil R. Smalheiser,et al.  Information discovery from complementary literatures: categorizing viruses as potential weapons , 2001 .

[3]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1999, SODA '98.

[4]  Berthier A. Ribeiro-Neto,et al.  Link-based and content-based evidential information in a belief network model , 2000, SIGIR '00.

[5]  Edward A. Fox,et al.  Combination of Multiple Searches , 1993, TREC.

[6]  Don R. Swanson,et al.  Two medical literatures that are logically but not bibliographically connected , 1987, J. Am. Soc. Inf. Sci..

[7]  Michael D. Gordon,et al.  Literature-based discovery by lexical statistics , 1999 .

[8]  Venu Dasigi Information fusion experiments for text classification , 1998, 1998 IEEE Information Technology Conference, Information Environment for the Future (Cat. No.98EX228).

[9]  Don R. Swanson,et al.  Complementary structures in disjoint science literatures , 1991, SIGIR '91.

[10]  Susan T. Dumais,et al.  Using latent semantic indexing for literature based discovery , 1998 .

[11]  Marc Weeber,et al.  Using concepts in literature-based discovery: simulating Swanson's Raynaud-fish oil and migraine-magnesium discoveries , 2001 .

[12]  W. Bruce Croft,et al.  Relevance feedback and inference networks , 1993, SIGIR.

[13]  Monika Henzinger,et al.  Finding Related Pages in the World Wide Web , 1999, Comput. Networks.