Thesis--University of Pittsburgh. / Bibliography: p. 129-135.

Thesis--University of Pittsburgh. / Bibliography: p. 247-251.

Thesis--University of Pittsburgh. / Bibliography: p. 247-251.

Thesis--Columbia University. / Includes bibliographical references (leaves 220-222).

Keyword searching and controlled vocabularies such as Library of Congress subject headings (LCSH) proved to work well together in automated technologies and the two systems have been considered complimentary. When the Internet burst onto the information landscape, users embraced the simplicity of keyword searching of this resource while researchers and scholars seemed unable to agree on how best to make use of controlled vocabularies in this huge database. This research looked at a controlled vocabulary, LCSH, in the context of keyword searching of a full text database. The Internet and probably its most used search engine, Google, seemed to have set a standard that users have embraced: a keyword-searchable single search box on an uncluttered web page. Libraries have even introduced federated single search boxes to their web pages, another testimony to the influence of Google. UNT's Thesis and Dissertation digital database was used to compile quantitative data with the results input into an EXCEL spreadsheet. Both Library of Congress subject headings (LCSH) and author-assigned keywords were analyzed within selected dissertations and both systems were compared. When the LCSH terms from the dissertations were quantified, the results showed that from a total of 788 words contained in the 207 LCSH terms assigned to 70 dissertations, 246 of 31% did not appear in the title or abstract while only 8, or about 1% from the total of 788, did not appear in the full text. When the author-assigned keywords were quantified, the results showed that from a total of 552 words from304 author-assigned keywords in 86 dissertations, 50 or 9% did not appear in the title or abstract while only one word from the total of 552 or .18% did not appear in the full text. Qualitatively, the LCSH terms showed a hierarchical construction that was clearly designed for a print card catalog, seemingly unnecessary in a random access digital environment. While author-assigned keywords were important words and phrases, these words and phrases often appeared in the title, metadata, and full text of the dissertation, making them seemingly unnecessary in a keyword search environment as they added no additional access points. Authors cited in this research have tended to agree that controlled vocabularies such as LCSH are complicated to develop and implement and expensive to maintain. Most researchers have also tended to agree that LCSH needs to be simplified for large, full text databases such as the Internet. Some of the researchers have also called for some form of automation that seamlessly links LCSH to subject terms in a keyword search. This research tends to confirm that LCSH could benefit from simplification as well as automation and offers some suggestions for improvements in both areas.

The main focus of this master’s thesis concerns the relation between subject representation, power and gender. Classification systems and subject heading lists are products of their cultural and social context and some subjects and disciplines are given a greater value than others. Our aim in this thesis is twofold; to discuss and critically analyse the prevailing gender norms that are expressed trough classification systems and subject heading lists and to examine how they manage to represent gender studies as a multidisciplinary subject in theory as well as in practice. We are also discussing the particular problems with the representation of multidisciplinary subjects in general. The analysis is grounded in the field of gender studies, where feminist, masculinity and queer theory are included, and the area of critical classification theory. The classification systems and subject heading list that are discussed here are DDC, SAB, SAO, LCSH and KVINNSAM. In the case of DDC and SAB, the analysis concerns the hierarchal structure and principal arrangement of subjects. The focus in the analysis of SAO, LSCH and KVINNSAM is on the assigned subject headings and the lists’ possibilities to adequately represent gender studies. The result of this study shows that both the systems and the subject heading list have considerable problems with integrating and fully representing gender studies as a multidisciplinary subject. It also shows that the available vocabularies for describing gender and feminist literature are very limited. The practise in indexing and classifying multidisciplinary subjects in general are neither sufficient nor consistent. / Uppsatsnivå: D

The system of Library of Congress Subject Headings (LCSH) has been the subject of feminist, critical examinations since the 1970s. Subject headings pertaining both to feminist literature and to women in general have been analyzed to determine how LCSH represents these topics. In this study, I contribute to this body of scholarship by analyzing and reporting on the nature of the LCSH subject representation of 52 core works published from 1986-1998 in the areas of feminist theory and women’s movements. These monographs were selected from the 3rd edition of Women’s Studies: A Recommended Bibliography (Krikos & Ingold, 2004). The analysis of works of/on feminist theory and on women’s movements is preceded by a pilot study of 24 core works on the topics of Communications, Film, Television, Media, and Journalism. I utilize the abstracts of these works in Krikos & Ingold (2004), as well as the works themselves, to establish the nature of each monograph’s perspective and scope. To this information I compare the LC subject headings employed in the bibliographic records representing these works in the Library of Congress Online Catalog in order to assess the headings’ usefulness as surrogate representations of these monographs in terms of accuracy, relevance, specificity, and currency. I present my findings as sets of problems and solutions illustrated with specific examples. Overall, LCSH is not able to represent adequately the 24 works in the pilot study sample or the 52 core works in the main study based on its current application. I conclude with a proposed set of subject headings as suggested by the abstracts of these works.

The system of Library of Congress Subject Headings (LCSH) has been the subject of feminist, critical examinations since the 1970s. Subject headings pertaining both to feminist literature and to women in general have been analyzed to determine how LCSH represents these topics. In this study, I contribute to this body of scholarship by analyzing and reporting on the nature of the LCSH subject representation of 52 core works published from 1986-1998 in the areas of feminist theory and women’s movements. These monographs were selected from the 3rd edition of Women’s Studies: A Recommended Bibliography (Krikos & Ingold, 2004). The analysis of works of/on feminist theory and on women’s movements is preceded by a pilot study of 24 core works on the topics of Communications, Film, Television, Media, and Journalism. I utilize the abstracts of these works in Krikos & Ingold (2004), as well as the works themselves, to establish the nature of each monograph’s perspective and scope. To this information I compare the LC subject headings employed in the bibliographic records representing these works in the Library of Congress Online Catalog in order to assess the headings’ usefulness as surrogate representations of these monographs in terms of accuracy, relevance, specificity, and currency. I present my findings as sets of problems and solutions illustrated with specific examples. Overall, LCSH is not able to represent adequately the 24 works in the pilot study sample or the 52 core works in the main study based on its current application. I conclude with a proposed set of subject headings as suggested by the abstracts of these works.

Thesis--University of Pittsburgh. / Cover title: Vocabulary control in L.C. classification. Bibliography: p. 147-55.

Over the last decade, the rapid growth and adoption of the World Wide Web has further exacerbated user needs for e±cient mechanisms for information and knowledge location, selection, and retrieval. How to gather useful and meaningful information from the Web becomes challenging to users. The capture of user information needs is key to delivering users' desired information, and user pro¯les can help to capture information needs. However, e®ectively acquiring user pro¯les is di±cult. It is argued that if user background knowledge can be speci¯ed by ontolo- gies, more accurate user pro¯les can be acquired and thus information needs can be captured e®ectively. Web users implicitly possess concept models that are obtained from their experience and education, and use the concept models in information gathering. Prior to this work, much research has attempted to use ontologies to specify user background knowledge and user concept models. However, these works have a drawback in that they cannot move beyond the subsumption of super - and sub-class structure to emphasising the speci¯c se- mantic relations in a single computational model. This has also been a challenge for years in the knowledge engineering community. Thus, using ontologies to represent user concept models and to acquire user pro¯les remains an unsolved problem in personalised Web information gathering and knowledge engineering. In this thesis, an ontology learning and mining model is proposed to acquire user pro¯les for personalised Web information gathering. The proposed compu- tational model emphasises the speci¯c is-a and part-of semantic relations in one computational model. The world knowledge and users' Local Instance Reposito- ries are used to attempt to discover and specify user background knowledge. From a world knowledge base, personalised ontologies are constructed by adopting au- tomatic or semi-automatic techniques to extract user interest concepts, focusing on user information needs. A multidimensional ontology mining method, Speci- ¯city and Exhaustivity, is also introduced in this thesis for analysing the user background knowledge discovered and speci¯ed in user personalised ontologies. The ontology learning and mining model is evaluated by comparing with human- based and state-of-the-art computational models in experiments, using a large, standard data set. The experimental results are promising for evaluation. The proposed ontology learning and mining model in this thesis helps to develop a better understanding of user pro¯le acquisition, thus providing better design of personalised Web information gathering systems. The contributions are increasingly signi¯cant, given both the rapid explosion of Web information in recent years and today's accessibility to the Internet and the full text world.