Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains vii, 36 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 33-36).

Thesis (Ph. D.)--University of Texas at Austin, 2003. / Supervisor: Raymond Mooney. Vita. Includes bibliographical references. Available also from UMI Company.

Thesis (M.S.)--California Polytechnic State University, 2009. / Title from PDF title page; viewed on August 27, 2009. "June 2009." "In partial fulfillment of the requirements for the degree [of] Master of Science in Computer Science." "Presented to the faculty of California Polytechnic State University, San Luis Obispo." Major professor: Franz J. Kurfess, Ph.D. Includes bibliographical references (p. 55-61).

Thesis (Ph.D.)--Murdoch University, 2008. / Thesis submitted to the Faculty of Creative Technologies and Media. Includes bibliographical references (leaves 205-223).

Thesis (M.Sc.)--University of Alberta, 2010. / Title from PDF file main screen (viewed on July 29, 2010). A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science, Department of Computing Science, University of Alberta. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Ohio State University, 2007. / Full text release at OhioLINK's ETD Center delayed at author's request

We present a system to determine content similarity of documents. More specifically, our goal is to identify book chapters that are translations of the same original chapter; this task requires identification of not only the different topics in the documents but also the particular flow of these topics. We experiment with different representations employing n-grams of lexical chains and test these representations on a corpus of approximately 1000 chapters gathered from books with multiple parallel translations. Our representations include the cosine similarity of attribute vectors of n-grams of lexical chains, the cosine similarity of tf*idf-weighted keywords, and the cosine similarity of unweighted lexical chains (unigrams of lexical chains) as well as multiplicative combinations of the similarity measures produced by these approaches. Our results identify fourgrams of unordered lexical chains as a particularly useful representation for text similarity evaluation.

This thesis presents a technology to complement taxation-based policy proposals aimed at addressing the digital copyright problem. Theapproach presented facilitates identification of intellectual propertyusing expression fingerprints. Copyright law protects expression of content. Recognizing literaryworks for copyright protection requires identification of theexpression of their content. The expression fingerprints described inthis thesis use a novel set of linguistic features that capture boththe content presented in documents and the manner of expression usedin conveying this content. These fingerprints consist of bothsyntactic and semantic elements of language. Examples of thesyntactic elements of expression include structures of embedding andembedded verb phrases. The semantic elements of expression consist ofhigh-level, broad semantic categories. Syntactic and semantic elements of expression enable generation ofmodels that correctly identify books and their paraphrases 82% of thetime, providing a significant (approximately 18%) improvement over modelsthat use tfidf-weighted keywords. The performance of models builtwith these features is also better than models created with standardfeatures used in stylometry (e.g., function words), which yield anaccuracy of 62%.In the non-digital world, copyright holders collect revenues bycontrolling distribution of their works. Current approaches to thedigital copyright problem attempt to provide copyright holders withthe same kind of control over distribution by employing Digital RightsManagement (DRM) systems. However, DRM systems also enable copyrightholders to control and limit fair use, to inhibit others' speech, andto collect private information about individual users of digitalworks.Digital tracking technologies enable alternate solutions to thedigital copyright problem; some of these solutions can protectcreative incentives of copyright holders in the absence of controlover distribution of works. Expression fingerprints facilitatedigital tracking even when literary works are DRM- and watermark-free,and even when they are paraphrased. As such, they enable meteringpopularity of works and make practicable solutions that encouragelarge-scale dissemination and unrestricted use of digital works andthat protect the revenues of copyright holders, for example throughtaxation-based revenue collection and distribution systems, withoutimposing limits on distribution.

In the past decades, organizations had to face numerous challenges due to intensifying globalization and internationalization, shorter innovation cycles and growing IT support for business. Business process management is seen as a comprehensive approach to align business strategy, organization, controlling, and business activities to react flexibly to market changes. For this purpose, business process models are increasingly utilized to document and redesign relevant parts of the organization's business operations. Since companies tend to have a growing number of business process models stored in a process model repository, analysis techniques are required that assess the quality of these process models in an automatic fashion. While available techniques can easily check the formal content of a process model, there are only a few techniques available that analyze the natural language content of a process model. Therefore, techniques are required that address linguistic issues caused by the actual use of natural language. In order to close this gap, this doctoral thesis explicitly targets inconsistencies caused by natural language and investigates the potential of automatically detecting and resolving them under a linguistic perspective. In particular, this doctoral thesis provides the following contributions. First, it defines a classification framework that structures existing work on process model analysis and refactoring. Second, it introduces the notion of atomicity, which implements a strict consistency condition between the formal content and the textual content of a process model. Based on an explorative investigation, we reveal several reoccurring violation patterns are not compliant with the notion of atomicity. Third, this thesis proposes an automatic refactoring technique that formalizes the identified patterns to transform a non-atomic process models into an atomic one. Fourth, this thesis defines an automatic technique for detecting and refactoring synonyms and homonyms in process models, which is eventually useful to unify the terminology used in an organization. Fifth and finally, this thesis proposes a recommendation-based refactoring approach that addresses process models suffering from incompleteness and leading to several possible interpretations. The efficiency and usefulness of the proposed techniques is further evaluated by real-world process model repositories from various industries. (author's abstract)