Thesis (Ed. D.)--West Virginia University, 2001. / Title from document title page. Document formatted into pages; contains vi, 133 p. Vita. Includes abstract. Includes bibliographical references (p. 125-131).

Zugl.: Karlsruhe, Univ., Diss., 2009 / Hergestellt on demand. - Zusätzliches Online-Angebot unter http://uvka.ubka.uni-karlsruhe.de/shop/isbn/978-3-86644-427-0

Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains iii, 49 p. Includes two sample banner ads: one animated and one content-specific. Vita. Includes abstract. Includes bibliographical references (p. 34-37).

Thesis (M.A.)--Sonoma State University, 2002. / Includes bibliographical references (leaves 35-36).

Tesis (Licenciado en Biblioteconomía)--Secretaría de Educación Pública, Dirección General de Educación Superior, Escuela Nacional de Biblioteconomía y Archivonomía, 2003. / Para disco compacto véase: DC/928. Incluye bibliografía: h. 143-151.

Tesis (Licenciado en Biblioteconomía)--Secretaría de Educación Pública, Dirección General de Educación Superior, Escuela Nacional de Biblioteconomía y Archivonomía, 2003. / Para obra impresa véase: 025.52/S2119c. Incluye bibliografía.

published_or_final_version / Computer Science and Information Systems / Master / Master of Philosophy

Artificial Intelligence Lab, Department of MIS, University of Arizona / As information technologies and applications become more overwhelming and diverse, persistent information overload problems have become ever more urgent.1 Fallout from this trend has most affected government, specifically criminaljustice information systems. The explosive growth in the digital information maintained in the data repositories of federal, state, and local criminal-justice entities and the spiraling need for cross-agency access to that information have made utilizing it both increasingly urgent and increasingly difficult. The Coplink system applies a concept spaceâ a statistics-based, algorithmic technique that identifies relationships between suspects, victims, and other pertinent dataâ to accelerate criminal investigations and enhance law enforcement efforts.

Artificial Intelligence Lab, Department of MIS, University of Arizona / As Internet services based on the World-Wide Web become more popular, information overload has become a pressing research problem. Difficulties with search on Internet will worsen as the amount of on-line information increases. A scalable approach to Internet search is critical to the success of Internet services and other current and future National Information Infrastructure (NII) applications. As part of the ongoing Illinois Digital Library Initiative project, this research proposes an intelligent personal spider (agent) approach to Internet searching. The approach, which is grounded on automatic textual analysis and general-purpose search algorithms, is expected to be an improvement over the current static and inefficient Internet searches. In this experiment, we implemented Internet personal spiders based on best first search and genetic algorithm techniques. These personal spiders can dynamically take a user's selected starting homepages and search for the most closely related homepages in the web, based on the links and keyword indexing. A plain, static CGI/HTML-based interface was developed earlier, followed by a recent enhancement of a graphical, dynamic Java-based interface. Preliminary evaluation results and two working prototypes (available for Web access) are presented. Although the examples and evaluations presented are mainly based on Internet applications, the applicability of the proposed techniques to the potentially more rewarding Intranet applications should be obvious. In particular, we believe the proposed agent design can be used to locate organization-wide information, to gather new, time-critical organizational information, and to support team-building and communication in Intranets.

Artificial Intelligence Lab, Department of MIS, University of Arizona / As part of the ongoing Illinois Digital Library Initiative project, this research proposes an intelligent agent approach to Web searching. In this experiment, we developed two Web personal spiders based on best first search and genetic algorithm techniques, respectively. These personal spiders can dynamically take a userâ s selected starting homepages and search for the most closely related homepages in the Web, based on the links and keyword indexing. A graphical, dynamic, Java-based interface was developed and is available for Web access. A system architecture for implementing such an agent-based spider is presented, followed by detailed discussions of benchmark testing and user evaluation results. In benchmark testing, although the genetic algorithm spider did not outperform the best first search spider, we found both results to be comparable and complementary. In user evaluation, the genetic algorithm spider obtained significantly higher recall value than that of the best first search spider. However, their precision values were not statistically different. The mutation process introduced in genetic algorithm allows users to find other potential relevant homepages that cannot be explored via a conventional local search process. In addition, we found the Java-based interface to be a necessary component for design of a truly interactive and dynamic Web agent.