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You searched for +publisher:"University of Cincinnati" +contributor:("Mazlack, Lawrence"). Showing records 1 – 3 of 3 total matches.

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University of Cincinnati

1. White, Ethan. Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps.

Degree: MS, Engineering and Applied Science: Computer Engineering, 2011, University of Cincinnati

Suicide has become a significantly prominent issue because high frequencies of occurrences make it one of the top three causes of death for young people in the United States. To prevent suicide attempts, it is important to identify suicidal tendencies in the behavior, speech, or writing of an individual as early as possible. This paper demonstrates one technique of analyzing written material to determine whether or not a person is in a suicidal state. Word frequencies were examined from both suicide and non-suicide documents and translated into inputs to a fuzzy cognitive map (FCM). The FCM determined whether the given input pattern was suicidal or non-suicidal. For the datasets examined, each set was correctly identified by the FCM as suicidal or non-suicidal. Advisors/Committee Members: Mazlack, Lawrence (Committee Chair).

Subjects/Keywords: Computer Engineering; fuzzy cognitive maps; causality; suicide

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

White, E. (2011). Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307323791

Chicago Manual of Style (16th Edition):

White, Ethan. “Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps.” 2011. Masters Thesis, University of Cincinnati. Accessed May 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307323791.

MLA Handbook (7th Edition):

White, Ethan. “Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps.” 2011. Web. 21 May 2019.

Vancouver:

White E. Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps. [Internet] [Masters thesis]. University of Cincinnati; 2011. [cited 2019 May 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307323791.

Council of Science Editors:

White E. Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps. [Masters Thesis]. University of Cincinnati; 2011. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1307323791


University of Cincinnati

2. GILMORE, ANDREW DAVID. An Exploratory Study of the Airline Ticket Purchasing Problem.

Degree: MS, Engineering : Computer Science, 2008, University of Cincinnati

This thesis is an exploratory study on airline ticket purchasing. Actual data are collected and studied with the goal of using a technique to purchase the lowest cost airline ticket given the information available. These data are studied in two ways: an algorithm based on the solution to the Secretary is applied and the trends of the data are reviewed. The Secretary Problem is where an employer is interviewing candidates for a secretarial position and the response to hire or reject a candidate must be made immediately after the interview. A sensible strategy to select the best candidate would be to interview and reject candidates without consideration to get an idea of the pool, and then at some point begin searching for the best candidate based on the initial pool. Generally, the first candidate found better than the initial pool is accepted. Buying an airline ticket can be in a way thought of as analogous to this: at each candidate ticket, one must deicide to accept and purchase the ticket or reject the current ticket price and wait for a potentially better ticket price. From the data, one can see that sudden drops in price make airfare purchasing a good candidate for the Secretary Problem. The application of a modified solution of the Secretary Problem to include heuristics noted by industry experts is successful at saving money over simply buying the first ticket offered to a given customer in about half of the collected routes, as the other cases exhibit a continuously increasing behavior. In the cases it is successful, the ticket is purchased about 1.5 to 2 weeks before departure, during a price valley. In summary, the modified Secretary Algorithm is successful as it saves money for some of the customers. Advisors/Committee Members: Mazlack, Lawrence (Committee Chair).

Subjects/Keywords: Computer Science; Secretary Problem; Airlines; Airefare; Cost Savings

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

GILMORE, A. D. (2008). An Exploratory Study of the Airline Ticket Purchasing Problem. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212635639

Chicago Manual of Style (16th Edition):

GILMORE, ANDREW DAVID. “An Exploratory Study of the Airline Ticket Purchasing Problem.” 2008. Masters Thesis, University of Cincinnati. Accessed May 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212635639.

MLA Handbook (7th Edition):

GILMORE, ANDREW DAVID. “An Exploratory Study of the Airline Ticket Purchasing Problem.” 2008. Web. 21 May 2019.

Vancouver:

GILMORE AD. An Exploratory Study of the Airline Ticket Purchasing Problem. [Internet] [Masters thesis]. University of Cincinnati; 2008. [cited 2019 May 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212635639.

Council of Science Editors:

GILMORE AD. An Exploratory Study of the Airline Ticket Purchasing Problem. [Masters Thesis]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1212635639


University of Cincinnati

3. Taylor, Julia Michelle. Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain.

Degree: PhD, Engineering : Computer Science and Engineering, 2008, University of Cincinnati

The dissertation presents a computational humor detector designed to look at any one of 200 short texts (100 jokes and 100 non-jokes) and to determine whether the text is a joke or not. This is accomplished on the basis of meaning recognition by the computer with the help of an ontology crafted from a children's dictionary, and any additional background knowledge necessary for text understanding. The research is underlaid by an advanced formal semantic theory of humor, and it constitutes the first known attempt to validate a theory of humor computationally. The results of the computational experiments are quite encouraging. With the advancement of computational technologies, increasingly more emphasis continues to be placed on systems that can handle natural language, whether it involves human-computer communication, or comprehension of written narratives, information on the Web, or human conversations. Humor occurs frequently in verbal communication. Thus, without humor detection no natural language computer system can be considered successful. For full computational understanding of natural language documents and for enabling intelligent conversational agents to handle humor, humor recognition is necessary or at the very least highly desirable. This exploratory research had to be constrained and its goals narrowed down for the purpose of implementability. The joke detector is therefore restricted to the recognition of short jokes. The domain is further restricted to jokes that are based on ambiguous words, where the detection of several meanings results in humor; and to jokes that are based on similar- or identical-sounding words, where the detection of correct pairs also leads to humor. Because of the meaning-based nature of the research, the system can be extended to other types of humor in text, without changes to the algorithm. The central hypothesis is that humor recognition of natural language texts is possible when the knowledge needed to comprehend the texts is available in a machine-understandable form. To test the hypothesis, a description logic ontology was built to represent knowledge manifested in natural language texts. The results show that when the information, necessary for humans to understand humor, is available to a machine, it successfully detects humor in text. Advisors/Committee Members: Mazlack, Lawrence J. (Committee Chair).

Subjects/Keywords: Artificial Intelligence; Computer Science; artificial intelligence; computational humor; natural language understanding

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Taylor, J. M. (2008). Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1226600183

Chicago Manual of Style (16th Edition):

Taylor, Julia Michelle. “Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain.” 2008. Doctoral Dissertation, University of Cincinnati. Accessed May 21, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1226600183.

MLA Handbook (7th Edition):

Taylor, Julia Michelle. “Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain.” 2008. Web. 21 May 2019.

Vancouver:

Taylor JM. Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain. [Internet] [Doctoral dissertation]. University of Cincinnati; 2008. [cited 2019 May 21]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1226600183.

Council of Science Editors:

Taylor JM. Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain. [Doctoral Dissertation]. University of Cincinnati; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1226600183

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