Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2007. / Includes bibliographical references (p. 80-81).

Thesis (MSc (Computer science))--University of Pretoria, 2008. / Includes bibliographical references.

Thesis (Ph. D.)--Oregon State University, 1991. / Typescript (photocopy). Includes bibliographical references (leaves 187-193). Also available on the World Wide Web.

Thesis (Ph.D.)--University of Nebraska-Lincoln, 2005. / Title from title screen (sites viewed on Oct. 18, 2005). PDF text: 100 p. : col. ill. Includes bibliographical references (p. 95-100 of dissertation).

The internet advertising market is growing much faster than any other advertising vertical. The technology for serving advertising online goes more and more towards automated processes that analyze the page content and the user’s preferences and then matches the ads with these parameters. The task at hand was to research and find methods that could be suitable for matching web documents to ads automatically, build a prototype system, make an evaluation and suggest areas for further development. The goals of the system was high throughput, accurate ad matching and fast response times. A requirement on the system was that human input could only be done when adding ads into the system for the system to be scalable. The prototype system is based on the vector space model and a td-idf weighting scheme. The cosines coefficient was used in the system to quantify the similarity between a web document and an ad. A technique called stemming was also implemented in the system together with a clustering solution that aided the ad matching in cases where few matches could be done on the keywords attached to the ads. The system was built with a threaded structure to improve throughput and scalability. The tests results show that you accurately can match ads to a website’s content using the vector space model and the cosines-coefficient. The tests also show that the stemming has a positive effect on the ad matching accuracy.

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Progress in technology has resulted in new aids in the form of writing tools which make it easier for pupils to revise their texts. This interview study investigates how four teachers view paper-based and screen-based text processing in the younger years of school. It is still paper-based text revision that dominates in schools, and the teachers point out the shortage of digital tools and competence. The choice of processing method is affected by the aim, whether it concerns content or form. The result shows that digital tools can be of help for pupils with difficulties, but the interviewed teachers also emphasize the value of mastering handwriting, and they would like to see screen-based text processing as a complement to traditional paper-based text processing.

This study examines the effects of the computer-assisted text analysis program, WRITER'S WORKBENCH, on writing performance, levels of writing apprehension, students' writing processes and attitudes about using the computer and WORKBENCH for writing. A sample of 275 subjects enrolled in freshman composition were divided into an experimental group (N = 200) who used WORKBENCH in a mandatory computer lab component in addition to their composition course and a control group (N = 75) who received only the course, itself. Because random selection of participants was not possible, a Nonequivalent Control Group design was utilized. Holistic scoring of pre and posttest essays revealed a significant improvement in writing among both groups as a result of the treatments, but there was no significant difference in writing gains between the group using WORKBENCH and the group who did not (p = .942) . Similarly, though both groups demonstrated a small decrease in writing apprehension after instruction, there was no significant difference in the degree of decrease between the two groups (p = .201). Also, the data did not support a relationship between writing performance and apprehension. A 40 item questionnaire was given to the experimental group to determine: 1) attitudes about writing with a computer, 2) how students use WORKBENCH, and 3) students' attitudes about WORKBENCH. Some highlights of these findings are that narrow majorities enjoyed and were comfortable using the computer and WORKBENCH, but substantial minorities dissented or were uncertain. While 60% felt happier with their essays after using WORKBENCH and preferred using a computer to write, 89% of students felt word processing represented the greatest advantage and SPELL was the next most popular feature. Personal interviews conducted with 13 of the most and least apprehensive WORKBENCH users revealed that some students ignored the WORKBENCH analyses, and highly apprehensive students experienced more frustration with the computer, employed different writing processes, used WORKBENCH less often and less skillfully, and expressed more dissatisfaction with the computer.

Document representation is important for computer-based text processing. Good document representations must include at least the most salient concepts of the document. Documents exist in a multidimensional space that difficult the identification of what concepts to include. A current problem is to measure the effectiveness of the different strategies that have been proposed to accomplish this task. As a contribution towards this goal, this dissertation studied the visual inter-document relationship in a dimensionally reduced space. The same treatment was done on full text and on three document representations. Two of the representations were based on the assumption that the salient features in a document set follow the chi-distribution in the whole document set. The third document representation identified features through a novel method. A Coefficient of Variability was calculated by normalizing the Cartesian distance of the discriminating value in the relevant and the non-relevant document subsets. Also, the local dictionary method was used. Cosine similarity values measured the inter-document distance in the information space and formed a matrix to serve as input to the Multi-Dimensional Scale (MDS) procedure. A Precision-Recall procedure was averaged across all treatments to statistically compare them. Treatments were not found to be statistically the same and the null hypotheses were rejected.