Published methods for distributed information retrieval generally rely on cooperation from search servers. But most real servers, particularly the tens of thousands available on the Web, are not engineered for such cooperation. This means that the majority of methods proposed, and evaluated in simulated environments of homogeneous cooperating servers, are never applied in practice.
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This thesis introduces new methods for server selection and results merging. The methods do not require search servers to cooperate, yet are as effective as the best methods which do. Two large experiments evaluate the new methods against many previously published methods. In contrast to previous experiments they simulate a Web-like environment, where servers employ varied retrieval algorithms and tend not to sub-partition documents from a single source.
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The server selection experiment uses pages from 956 real Web servers, three different retrieval systems and TREC ad hoc topics. Results show that a broker using queries to sample servers documents can perform selection over non-cooperating servers without loss of effectiveness. However, using the same queries to estimate the effectiveness of servers, in order to favour servers with high quality retrieval systems, did not consistently improve selection effectiveness.
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The results merging experiment uses documents from five TREC sub-collections, five different retrieval systems and TREC ad hoc topics. Results show that a broker using a reference set of collection statistics, rather than relying on cooperation to collate true statistics, can perform merging without loss of effectiveness. Since application of the reference statistics method requires that the broker download the documents to be merged, experiments were also conducted on effective merging based on partial documents. The new ranking method developed was not highly effective on partial documents, but showed some promise on fully downloaded documents.
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Using the new methods, an effective search broker can be built, capable of addressing any given set of available search servers, without their cooperation.
Identifer | oai:union.ndltd.org:ADTP/216716 |
Date | January 2001 |
Creators | Craswell, Nicholas Eric, Nick.Craswell@anu.edu.au |
Publisher | The Australian National University. Faculty of Engineering and Information Technology |
Source Sets | Australiasian Digital Theses Program |
Language | English |
Detected Language | English |
Rights | http://www.anu.edu.au/legal/copyright/copyrit.html), Copyright Nicholas Eric Craswell |
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