We have built an HTTP based resource discovery system called Discover that provides a single point

Query Refinement is an essential information retrieval tool that interactively recommends new terms related to a particular query. This paper introduces concept recall, an experimental measure of an algorithm's ability to suggest terms humans have judged to be semantically related to an information need. This study uses precision improvement experiments to measure the ability of an algorithm to produce single term query modifications that predict a user's information need as partially encoded by the query. An oracle algorithm produces ideal query modifications, providing a meaningful context for interpreting precision improvement results. This study also introduces RMAP, a fast and practical query refinement algorithm that refines multiple term queries by dynamically combining precomputed suggestions for single term queries. RMAP achieves accuracy comparable to a much slower algorithm, although both RMAP and the slower algorithm lag behind the best possible term suggestions o ered by the oracle. We believe RMAP is fast enough to be integrated into present dayInternet search engines: RMAP computes 100 term suggestions for a 160,000 document collection in 15 ms on a low-end PC.

Locating and accessing information in a large distributed system is a difficult problem of growing importance. This paper reports on our experience building and using a prototype system for transparent, user-guided associative access to the contents of a large, distributed set of WAIS servers. Our system is based on content routing, an architecture that makes use of content labels for locating and accessing information in large distributed systems [12]. Our content router for WAIS servers is implemented as a Semantic File System that constructs content labels from WAIS source and catalog files. The content router guides locating documents by suggesting terms that frequently appear with a given query term in document headlines. Sufficiently narrowed queries are routed to WAIS servers and processed in parallel. We have successfully used our content router to locate documents on a large number of WAIS servers. Along with demonstrating the feasibility of distributed finding in a large netw...

This thesis presents a new architecture for information discovery based on a hierarchy of content routers that provide both browsing and search services to end users. Content routers catalog information servers, which may in turn be other content routers. The resulting hierarchy of content routers and leaf servers provides a rich set of services to end users for locating information, including query refinement and query routing. Query refinement helps a user improve a query fragment to describe the user's interests more precisely. Once a query has been refined and describes a manageable result set, query routing automatically forwards the query to relevant servers. These services make use of succinct descriptions of server contents called content labels. A unique contribution of this research is the demonstration of a scalable discovery architecture based on a hierarchical approach to routing.

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