%0 Thesis %1 Morrison:1994:ibs %A Morrison, Dan %C Gower Street, London, WC1E 6BT, UK %D 1994 %K Automatic Query Retrival, Text algorithms, generation, genetic iBrowse programming, %T Development of a Prototype Intelligent Browsing System, utilising Boolean Query Generation using Genetic Programming %X The need was identified for a generic Information Retrival tool. Genetic Programming was selected as most suitable paradigm for providing the necessary adaptive intelligence. This was combined with conventional Bollean query search techniques. Each Query is treated as a genetic individual and a population of these is eveolved so as to move through the search space of all possible queries efficeiently. The criteria that guide this search is termed relevance feedback. This information is derived from the suer through tne evaluation of a document set and forms the basis of the fitness funtion. The best query produced in this way can then be used to scan other documents, ordering these according to relevance. These processes can be lined to produce an application that can learn by experience, requires no explicit instructions and can be apllied to a wide variety of IR situations. The development work was divided into three stages: design and implementation of an experimental software platform, research into viable configurations using this platform, and construction of working models. Stage one formed the focus of this project. The project specification was thus to produce a software system that can act as a testbed during experimentation in teh second stage and as an early prototype of future applications. This was achieved, the souce code being written in C++ to run on a PC.

@mastersthesis{Morrison:1994:ibs, abstract = {The need was identified for a generic Information Retrival tool. Genetic Programming was selected as most suitable paradigm for providing the necessary adaptive intelligence. This was combined with conventional Bollean query search techniques. Each Query is treated as a genetic individual and a population of these is eveolved so as to move through the search space of all possible queries efficeiently. The criteria that guide this search is termed relevance feedback. This information is derived from the suer through tne evaluation of a document set and forms the basis of the fitness funtion. The best query produced in this way can then be used to scan other documents, ordering these according to relevance. These processes can be lined to produce an application that can learn by experience, requires no explicit instructions and can be apllied to a wide variety of IR situations. The development work was divided into three stages: design and implementation of an experimental software platform, research into viable configurations using this platform, and construction of working models. Stage one formed the focus of this project. The project specification was thus to produce a software system that can act as a testbed during experimentation in teh second stage and as an early prototype of future applications. This was achieved, the souce code being written in C++ to run on a PC.}, added-at = {2008-06-19T17:46:40.000+0200}, address = {Gower Street, London, WC1E 6BT, UK}, author = {Morrison, Dan}, biburl = {https://www.bibsonomy.org/bibtex/2cdab0b013672d2f315333e46f148889e/brazovayeye}, interhash = {cb7a91a59b443e9212a6beb002961bc5}, intrahash = {cdab0b013672d2f315333e46f148889e}, keywords = {Automatic Query Retrival, Text algorithms, generation, genetic iBrowse programming,}, month = {September}, notes = {Supervised by Chris Clack}, school = {University College, London}, size = {53 pages plus 40 pages of appendices}, timestamp = {2008-06-19T17:47:41.000+0200}, title = {Development of a Prototype Intelligent Browsing System, utilising Boolean Query Generation using Genetic Programming}, year = 1994 }