Thesis (M.S. in Computer Science)--Naval Postgraduate School, December 2002. / Thesis advisor(s): Neil C. Rowe, Xavier Maruyama. Includes bibliographical references (p. 105-109). Also available online.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Don Brutzman, Curt Blair, Barb Helfer. Includes bibliographical references (p. 95-99). Also available online.

Thesis (M. Ed.(RGO)--Universiteit van Pretoria, 2001. / Includes bibliographical references (p. 68-71).

With the globalisation and constant changes in the marketplace, enterprises are adapting themselves to face new challenges. Therefore, strategic corporate alliances to share knowledge, expertise and resources represent an advantage in an increasing competitive world. This has led the integration of companies, customers, suppliers and partners using networked environments. This thesis presents three novel solutions in the tooling area, developed for Seco tools Ltd, UK. These approaches implement a proposed distributed computing architecture using Internet technologies to assist geographically dispersed tooling engineers in process planning tasks. The systems are summarised as follows. TTS is a Web-based system to support engineers and technical staff in the task of providing technical advice to clients. Seco sales engineers access the system from remote machining sites and submit/retrieve/update the required tooling data located in databases at the company headquarters. The communication platform used for this system provides an effective mechanism to share information nationwide. This system implements efficient methods, such as data relaxation techniques, confidence score and importance levels of attributes, to help the user in finding the closest solutions when specific requirements are not fully matched In the database. Cluster-F has been developed to assist engineers and clients in the assessment of cutting parameters for the tooling process. In this approach the Internet acts as a vehicle to transport the data between users and the database. Cluster-F is a KD approach that makes use of clustering and fuzzy set techniques. The novel proposal In this system is the implementation of fuzzy set concepts to obtain the proximity matrix that will lead the classification of the data. Then hierarchical clustering methods are applied on these data to link the closest objects. A general KD methodology applying rough set concepts Is proposed In this research. This covers aspects of data redundancy, Identification of relevant attributes, detection of data inconsistency, and generation of knowledge rules. R-sets, the third proposed solution, has been developed using this KD methodology. This system evaluates the variables of the tooling database to analyse known and unknown relationships in the data generated after the execution of technical trials. The aim is to discover cause-effect patterns from selected attributes contained In the database. A fourth system was also developed. It is called DBManager and was conceived to administrate the systems users accounts, sales engineers’ accounts and tool trial monitoring process of the data. This supports the implementation of the proposed distributed architecture and the maintenance of the users' accounts for the access restrictions to the system running under this architecture.

The availability of large-scale data on the Web motivates the development of automatic algorithms to analyze topics and to identify relationships between topics. Various approaches have been proposed in the literature. Most focus on specific topics, mainly those representing people, with little attention to topics of other kinds. They are also less flexible in how they represent topics. In this thesis we study existing methods as well as describe a different approach, based on profiles, for representing topics. A Topic Profile is analogous to a synopsis of a topic and consists of different types of features. Profiles are flexible to allow different combinations of features to be emphasized and are extensible to support new features to be incorporated without having to change the underlying logic. More generally, topic profiles provide an abstract framework that can be used to create different types of concrete representations for topics. Different options regarding the number of documents considered for a topic or types of features extracted can be decided based on requirements of the problem as well as the characteristics of the data. Topic profiles also provide a framework to explore relationships between topics. We compare different methods for building profiles and evaluate them in terms of their information content and their ability to predict relationships between topics. We contribute new methods in term weighting and for identifying relevant text segments in web documents. In this thesis, we present an application of our profile-based approach to explore social networks of US senators generated from web data and compare with networks generated from voting data. We consider both general networks as well as issue-specific networks. We also apply topic profiles for identifying and ranking experts given topics of interest, as part of the 2007 TREC Expert Search task. Overall, our results show that topic profiles provide a strong foundation for exploring different topics and for mining relationships between topics using web data. Our approach can be applied to a wide range of web knowledge discovery problems, in contrast to existing approaches that are mostly designed for specific problems.

Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: leaf 281-310.

The current World Wide Web is a web of pages. Users have to guess possible keywords that might lead through search engines to the pages that contain information of interest and browse hundreds or even thousands of the returned pages in order to obtain what they want. This frustrating problem motivates an approach to turn the web of pages into a web of knowledge, so that web users can query the information of interest directly. This dissertation provides a step in this direction and a way to partially overcome the challenges. Specifically, this dissertation shows how to turn machine-generated web pages like those on the hidden web into semantic web pages for the web of knowledge. We design and develop three systems to address the challenge of turning the web pages into web-of-knowledge pages: TISP (Table Interpretation for Sibling Pages), TISP++, and FOCIH (Form-based Ontology Creation and Information Harvesting). TISP can automatically interpret hidden-web tables. Given interpreted tables, TISP++ can generate ontologies and semantically annotate the information present in the interpreted tables automatically. This way, we can offer a way to make the hidden information publicly accessible. We also provide users with a way where they can generate personalized ontologies. FOCIH provides users with an interface with which they can provide their own view by creating a form that specifies the information they want. Based on the form, FOCIH can generate user-specific ontologies, and based on patterns in machine-generated pages, FOCIH can harvest information and annotate these pages with respect to the generated ontology. Users can directly query on the annotated information. With these contributions, this dissertation serves as a foundational pillar for turning the current web of pages into a web of knowledge.

No / This paper presents a discussion based on a literature review and a case study on the suitability of using an intranet as a platform to implement Knowledge Management System (KMS). A description of Knowledge Management (KM) and the current research carried out in this area, with examples of web-based KMS systems currently implemented in organisations, are presented. Further, this paper then describes how knowledge mapping of an organisation's intranet as a form of a KMS can be used to promote the re-utilisation of knowledge, which will contribute to the competitiveness of the organisation. A case study that illustrates and presents evidence of the need and suitability of such a system is provided. The paper ends with a proposal for future research to be carried out in this area.

Intellectual capital is the single most important asset owned by any organization. Business continuity and the long term sustainability of every business organization depends partly on how well accumulated organizational knowledge is passed on from generation to generation. Knowledge is hard to capture due to its implicit nature and even harder to manage, thus the deployment of numerous knowledge management systems by organizations in recent times. Knowledge sharing among employees within organizations can sometimes be very problem-atic. These problems stem from issues pertaining to power, secrecy, individualism, time, ignorance and technological issues among others. This paper seeks to investigate how web 2.0 technologies are being used to overcome these problems and facilitate knowledge sharing as well as collaboration. Web 2.0 has been described as the new web which focuses on the use of platforms. Platforms are digital environments in which contributions and interactions are globally visible. The new web technologies which are based on platforms are referred to as emergent social software platforms (ESSP‘s). The use of these web 2.0 technologies (ESSP‘s) within a business enterprise for the achievement of business goals is known as enterprise 2.0 (E2.0). Central to this research is the knowledge sharing cycle model, which has three main stages; internalization, externalization, and objectification. Internalization occurs when individuals acquire or learn from the organization. Externalization is achieved when individual implicit knowledge is made explicit. Objectification is making new knowledge globally accepted. This cycle has been adapted to illustrate the role played by ESSP‘s in facilitating knowledge sharing. A case study of IBM Corporation is used to arrive at the findings which are used to adapt the model. IBM Corporations extensively deploys E2.0. The company uses one central Social networking platform called IBM connections, which incorporates several ESSP‘s. There are seven services on IBM connections which include profiles, Activities, wikis, blogs, bookmarks, Files, and communities. Employing the interview technique, observations and the use of secondary data, the research questions are answered. The findings indicate that ESSP‘s can be used to support knowledge sharing practices and also helps to convert knowledge into its different forms (explicit and implicit). Blogs, wikis, and communities support internaliza-tion and externalization. The process of objectification is supported by wikis. Findings also indicate that the services within IBM connections platform support mass collaboration and foster strong ties among employees. In an objective manner, the paper points out some of the negative consequences of E2.0. Major issues uncovered through the case study include, sensi-tive data, undefined way of working with ESSP‘s, privacy, abuse of use, and lack of interest.

Ontologien spielen eine zentrale Rolle für die formalisierte Repräsentation von Wissen und Informationen sowie für die Infrastruktur des sogenannten semantic web. Trotz früherer Initiativen der Bibliotheken und Gedächtnisinstitutionen hat sich die deutschsprachige Musikwissenschaft insgesamt nur sehr zögerlich dem Thema genähert. Im Rahmen einer Bestandsaufnahme werden neben der Erläuterung grundlegender Konzepte, Herausforderungen und Herangehensweisen bei der Modellierung von Ontologien daher auch vielversprechende Modelle und bereits erprobte Anwendungsbeispiele für eine ‚semantische‘ digitale Musikwissenschaft identifiziert. / Ontologies play a crucial role for the formalised representation of knowledge and information as well as for the infrastructure of the semantic web. Despite early initiatives that were driven by libraries and memory institutions, German musicology as a whole has turned very slowly to the subject. In an overview the author addresses basic concepts, challenges, and approaches for ontology design and identifies models and use cases with promising applications for a ‚semantic‘ digital musicology.