Bargaining is a frequent activity in the shopping process, and it becomes a trend in electronic trading. In order to facilitate the on-line automatic bargaining activity, we develop three algorithms on the multi-agent system in this thesis. The first algorithm is the pattern generalization algorithm used for generalizing common patterns from transaction records. The second one is the pattern matching algorithm used on-line for identifying possible bargaining patterns from the pattern bases. To deal with the situation that there is no matched pattern, we design the dynamic price issuing algorithm using the utility theory to determine the seller¡¦s price and the timing a deal should be closed. We conducted a series of field experiments to evaluate the proposed algorithms on different seller¡¦s risk perspectives and compared the performance with conventional bargaining methods. The results show that the proposed methods obtain encouraging performance. The major contribution of this research is the initiation efforts on developing data mining algorithms for facilitating the price bargaining process for e-commerce.

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Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 164-170).

Thesis (M.S.)--California Polytechnic State University, 2009. / Mode of access: Internet. Title from PDF title page; viewed on December 1, 2009. Major professor: Dr. Lily Laiho. "Presented to the faculty of California Polytechnic State University, San Luis Obispo, California." "In partial fulfillment of the requirements for the degree of Master of Science in Biomedical Engineering." "June 2009." Includes bibliographical references (p. 29-30).

Thesis (Ph. D.)--University of Hong Kong, 2001. / Includes bibliographical references (leaves 140-150).

Thesis (Ph. D.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains xiii, 192 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 160-169).

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (p. 79-98).

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 127-132).

published_or_final_version / Statistics and Actuarial Science / Doctoral / Doctor of Philosophy

In the actuarial literature, dependence structures in risk models have been extensively studied. The main theme of this thesis is to investigate some discrete-time risk models with claim numbers modeled by integer-valued time series processes. The first model is a common shock risk model with temporal dependence between the claim numbers in each individual class of business. Specifically the Poisson MA(1) process and Poisson AR(1) process are considered for the temporal dependence. To study the ruin probability, the equations associated with the adjustment coefficients are derived. Comparisons are also made to assess the impact of the dependence structures on the ruin probability. Another model involving both the correlated classes of business and the time series approach is then studied. Thinning dependence structure is adopted to model the dependence among classes of business. The Poisson MA(1) and Poisson AR(1) processes are used to describe the claim-number processes. Adjustment coefficients and ruin probabilities are examined. Finally a discrete-time risk model with the claim number following a Poisson ARCH process is proposed. In this model, the mean of the current claim number depends on the previous observations. Within this framework, the equation for finding the adjustment coefficient is derived. Numerical studies are also carried out to examine the effect of the Poisson ARCH dependence structure on several risk measures including ruin probability, Value at Risk, and conditional tail expectation. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy