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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.

We describe the first system that provides query based associative access to the contents of distributed information servers. Queries describe desired object attributes, and are automatically forwarded to servers that contain relevant information. In typical distributed information systems there are so many objects that underconstrained queries can produce large result sets and extraordinary processing costs. To deal with this scaling problem we use content labels to permit users to learn about available resources and to quickly formulate queries with adequate discriminatory power. We present experimental data that show that certain content label attributes can be automatically chosen. We have implemented associative access to a distributed set of information servers in the content routing system. A content routing system is organized as a network of servers called content routers that present a single query based image of a distributed information system. Experiments motivated by our video access service show that substantial performance benefits result when content routers are removed from the client-server path once an object of interest is found.

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The popularity of information retrieval has led users to a new problem: finding which text databases (out of thousands of candidate choices) are the most relevant to a user. Answering a given query with a list of relevant databases is the text database discovery problem. The first part of this paper presents a practical method for attacking this problem based on estimating the result size of a query and a database. The method is termed GlOSS-Glossary of Servers Server. The second part of this paper evaluates GlOSS using four different semantics to answer a user's queries. Real users' queries were used in the experiments. We also describe several variations of GlOSS and compare their efficacy. In addition, we analyze the storage cost of our approach to the problem. 1 Introduction Information vendors such as Dialog and Mead Data Central provide content-indexed access to multiple databases. Dialog for instance has over three hundred databases. In addition, the advent of Archie, WAIS, Wor...

1 Introduction The Internet contains over one million hosts that provide file service and other information servers specializing in topics such as news, technical reports, biology, geography, and politics. The Internet's vast collection of servers can be viewed as a distributed database containing a wealth of information. Unfortunately, this information is relatively inaccessible because there is no mechanism for browsing and searching it associatively. The difficulty of providing associative access to a large number of distributed information servers lies primarily in problems of scale. The scale of the Internet, which is today only a fraction of its eventual size, is so great as to render infeasible any comprehensive indexing plan based on a single global index. In addition, the cost of distributing a query throughout the Internet is prohibitive. Finally, in very large scale systems, the number of results to a typical user query is incomprehensibly large. For these reasons, we expect that efficient associative access will require both content routing and query refinement. Content routing is the process of directing user queries to appropriate servers. Query refinement helps a user formulate meaningful queries. These query services can be implemented by a content routing system that will: