Thesis (MPhil)--University of Stellenbosch, 2008. / Bibliography. Also available via the Internet.

Thesis (Ph.D.)--City University of Hong Kong, 2009. / "Submitted to Department of Information Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 146-172)

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, December 2002. / Thesis advisor(s): Neil C. Rowe, Xavier Maruyama. Includes bibliographical references (p. 105-109). Also available online.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, June 2003. / Thesis advisor(s): J.D. Fulp, Brian D. Steckler. Includes bibliographical references (p. 83). Also available online.

published_or_final_version / Business / Doctoral / Doctor of Philosophy

Social media has been recognized as a potential platform for enhancing knowledge management (KM) on education due to its associated usefulness in encouraging active participation, collaboration, and relationship establishment. This thesis examines the incorporation of two popular social networking sites (SNSs), Blogs and Facebook, into the internship activities of two groups of students over six cohorts: 3 years of Blogs intern users (n = 47) and 3 years of Facebook intern users (n = 64). Behaviors, perceptions, KM processes and socio-emotional expressions of the intern users of Blogs and Facebook were analyzed and contrasted. A mixed research method was used to obtain quantitative and qualitative data through Blogs entries, Facebook posts, questionnaire and structured interviews. Results reveal that both Blogs and Facebook users engaged in regular use in writing, reading and commenting. Both groups of intern users perceived Blogs and Facebook to be useful as platforms for reflection, learning and communication. They also agreed that these two SNSs were able to facilitate emotional support and perceived support from peers through commenting. Qualitative analyses of Blogs entries and Facebook contents indicated that users of both Blogs and Facebook were able to engage in the processes of knowledge capture, knowledge sharing and dissemination, knowledge acquisition and knowledge application. Specifically, Blogs intern users had higher engagement on knowledge capture while Facebook intern users had higher engagement on knowledge sharing and dissemination. Users of both SNSs also actively engaged in emotional expressions and social support during their internship. Responses to open-ended questions suggested that participants had different preferences in using Blogs and Facebook. Blogs intern users put high values on the function of information recording and retrieving whereas Facebook intern users preferred the strong interaction features of Facebook. Overall, the study offers evidence on Facebook being appeared to be a better tool in facilitating KM processes and cultivating a knowledge sharing culture than blogs. It also demonstrates the potential similarities and differences of using Blogs and Facebook to enhance KM on education. / published_or_final_version / Library and Information Management / Master / Master of Science in Library and Information Management

A knowledge base, such as Yago or DBpedia, can be modeled as a large graph with nodes and edges annotated with class and relationship labels. Recent work has studied how to make use of these rich information sources. In particular, meta-paths, which represent sequences of node classes and edge types between two nodes in a knowledge base, have been proposed for such tasks as information retrieval, decision making, and product recommendation. Current methods assume meta-paths are found by domain experts. However, in a large and complex knowledge base, retrieving meta-paths manually can be tedious and difficult. We thus study how to discover meta-paths automatically. Specifically, users are asked to provide example pairs of nodes that exhibit high proximity. We then investigate how to generate meta-paths that can best explain the relationship between these node pairs. Since this problem is computationally intractable, we propose a greedy algorithm to select the most relevant meta-paths. We also present a data structure to enable efficient execution of this algorithm. We further incorporate hierarchical relationships among node classes in our solutions. Finally, we propose an effective similarity join algorithm in order to generate more node pairs using these meta-paths. Extensive experiments on real knowledge bases show that our approach captures important meta-paths in an efficient and scalable manner. / published_or_final_version / Computer Science / Master / Master of Philosophy

Not available / text

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