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dc.contributor.advisorRam, Sudhaen_US
dc.contributor.authorVenkatsubramanyan, Shailaja
dc.creatorVenkatsubramanyan, Shailajaen_US
dc.date.accessioned2013-04-25T10:33:31Zen
dc.date.available2013-04-25T10:33:31Zen
dc.date.issued1999en_US
dc.identifier.urihttp://hdl.handle.net/10150/284913en
dc.description.abstractThe Internet has made it possible for large amounts of data to be made available to users in a variety of areas. This has to lead to users being inundated with lots of information, making it difficult for them to locate data that would be of use to them. One domain that has not been immune to this problem is that of remote sensing. Remotely sensed data is available in abundance and can potentially be of use to many users. But it is difficult for users from different application domains to locate appropriate datasets and process them. Current search tools such as search engines are not adequate for remotely sensed data as most searches using these tools yield an inordinately large number of web sites, each of which has to be explored individually by the user and then the results manually collated. Besides, traditional search techniques are not embedded with the knowledge about the remote sensing domain. The goal of this research is to find out how users with varying backgrounds and levels of expertise can retrieve and access resources over the Internet. This dissertation describes a virtual enterprise model of intelligent agents that deals with the complexities of locating and retrieving remotely sensed data over the Internet. The methodology followed in this research includes (i) agent modeling, (ii) building agent cooperation techniques that would enable agents to understand terminology used at different sites and communicate with each other, (iii) optimizing communication flows between various agents, (iv) validating the model, and (v) verifying the prototype. The important contributions of this research include among others an agent model generalizable to problem domains other than remote sensing, a formally defined ontology (a collection of terms and relationships between those terms) for the remote sensing domain, and a prototype system that implements the model and the ontology.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectBusiness Administration, Management.en_US
dc.titleDiscovering distributed and heterogeneous resources on the Internet: A theoretical foundation for an ontology-driven intelligent agent model. Its design, implementation and validationen_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.leveldoctoralen_US
dc.identifier.proquest9946810en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineIndustrial Managementen_US
thesis.degree.namePh.D.en_US
dc.identifier.bibrecord.b39914549en_US
refterms.dateFOA2018-05-27T03:47:46Z
html.description.abstractThe Internet has made it possible for large amounts of data to be made available to users in a variety of areas. This has to lead to users being inundated with lots of information, making it difficult for them to locate data that would be of use to them. One domain that has not been immune to this problem is that of remote sensing. Remotely sensed data is available in abundance and can potentially be of use to many users. But it is difficult for users from different application domains to locate appropriate datasets and process them. Current search tools such as search engines are not adequate for remotely sensed data as most searches using these tools yield an inordinately large number of web sites, each of which has to be explored individually by the user and then the results manually collated. Besides, traditional search techniques are not embedded with the knowledge about the remote sensing domain. The goal of this research is to find out how users with varying backgrounds and levels of expertise can retrieve and access resources over the Internet. This dissertation describes a virtual enterprise model of intelligent agents that deals with the complexities of locating and retrieving remotely sensed data over the Internet. The methodology followed in this research includes (i) agent modeling, (ii) building agent cooperation techniques that would enable agents to understand terminology used at different sites and communicate with each other, (iii) optimizing communication flows between various agents, (iv) validating the model, and (v) verifying the prototype. The important contributions of this research include among others an agent model generalizable to problem domains other than remote sensing, a formally defined ontology (a collection of terms and relationships between those terms) for the remote sensing domain, and a prototype system that implements the model and the ontology.


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