DESCRIPTION
General purpose search engines, such as Google and Yahoo!, provide an easy machnism for users to discover information on the Web.Despite their obvious advantages, they have a number of significant limitations, because thay cannot reach or analyze a significant part of the information tha is available.
Distributed Information Retrieval systems, emplying collection fusion algorithms, offer a solution to the above problem, by allowing users to submit queries to multiple information sources simultaneously through a single interface, offering a much wider coverage of the available information.
This thesis deals with two of the main issues of designing and implementing efficient and effective Destributed Information Retrieval systems: source selection and result merging.The former deals with the ability of the system to select the most appropriate information source to delegate thw user query and the latter aims to produce the best possible final document list by merging to individual retrieved documents lists from the selected sources.
The new algorithms that are presented in this thesis are designed to function effectively in settings where information sources provide no cooperation at all, thus making them applicable in the widest possible set of environments and domains. The source selection algorithm that is put forth provides a novel modeling of information sources as regions in a space created by the documents that they contain. It provides a full theoretical framework ofr addressing thw source selection problem, while at tha same time effectively captures real-world observations anf widely accepted notions in Informatio Retrieval. Extensive expreiments demonstrate that it is able to obtain a prformance that is at least as good as other state-of- the-art approaces and more often better.
The novel result merging algorithms that are presented are based on the supposition that search engines return only ranked lists of documents, without relevance scores, a scenario which is standard practice in current retrieval systems.They are both able to address a lack of information very effectively, demonstrating significant performace gains over other state-of-the-art approaches. Additionally, the second algorithm unites the two general directions that the results merging problem has been approached in research, combning their advantages while minimizing their drawbacks.