Song Dawei. / "August 2000." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (p. 159-162). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

by Chan Chi Wai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves [89]-91). / Abstract --- p.ii / List of Tables --- p.vii / List of Figures --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background Information And Scope of Thesis --- p.6 / Chapter 2.1 --- Related Work --- p.6 / Chapter 2.2 --- Scope of Thesis --- p.10 / Chapter 3 --- System Architecture and Design Principle --- p.12 / Chapter 3.1 --- Overall System Architecture --- p.12 / Chapter 3.2 --- Entry Term Construct and Thesaurus Frame --- p.14 / Chapter 3.2.1 --- Semantic Classification --- p.15 / Chapter 3.2.2 --- "Word, Entry Term and Semanteme" --- p.17 / Chapter 3.2.3 --- Relationship Type and Relationship Link --- p.19 / Chapter 3.3 --- Thesaurus Module and Maintenance Module --- p.22 / Chapter 3.4 --- Data Structure --- p.22 / Chapter 3.4.1 --- Semantic Classification Tree --- p.24 / Chapter 3.4.2 --- Entry Term Construct --- p.24 / Chapter 3.4.3 --- Thesaurus Frame --- p.26 / Chapter 4 --- Relationship Inference --- p.28 / Chapter 4.1 --- Study on a Traverse of Two Relationship Links --- p.29 / Chapter 4.2 --- Grammar of the Relationship Inference Rules Definition --- p.33 / Chapter 4.3 --- Implementation Detail and API of Relationship Inference --- p.35 / Chapter 4.4 --- Evaluation on Relationship Inference --- p.39 / Chapter 5 --- Weight Schemes --- p.41 / Chapter 5.1 --- Thesaurus Frame Construction and Relationship Type Definition --- p.42 / Chapter 5.2 --- Two Kinds of Relationship Types --- p.44 / Chapter 5.3 --- Evaluation on different Weighting Scheme Formulas --- p.46 / Chapter 5.4 --- Term Ranking --- p.57 / Chapter 5.5 --- Normalization on Semantic Distance --- p.62 / Chapter 6 --- User Interface and API --- p.66 / Chapter 6.1 --- User Interface --- p.66 / Chapter 6.2 --- API --- p.74 / Chapter 6.2.1 --- Thesaurus Management --- p.75 / Chapter 6.2.2 --- Semantic Classifications --- p.76 / Chapter 6.2.3 --- Entry Terms --- p.77 / Chapter 6.2.4 --- Semantemes --- p.79 / Chapter 6.2.5 --- Relationship Types and Relationship Links --- p.80 / Chapter 6.2.6 --- Weighting Schemes --- p.83 / Chapter 7 --- Conclusion --- p.86 / Reference --- p.89 / Chapter A --- System Installation --- p.92 / Chapter A.1 --- File Organization of TheSys --- p.92 / Chapter A. 1.1 --- API Source Codes (THESYS/API) --- p.93 / Chapter A. 1.2 --- Header Files (THESYS/include) --- p.94 / Chapter A. 1.3 --- Interface Source Codes and Library (THESYS/UI and THESYS/lib) --- p.95 / Chapter A. 1.4 --- System Generated Files --- p.96 / Chapter A.2 --- Setup TheSys with its User Interfaces --- p.97 / Chapter A.3 --- Employ TheSys with Customized Applications --- p.97 / Chapter B --- API Description --- p.99 / Chapter B.1 --- Thesaurus Management --- p.102 / Chapter B.2 --- Semantic Classifications --- p.107 / Chapter B.3 --- Entry Terms --- p.116 / Chapter B.4 --- Semanemes --- p.123 / Chapter B.5 --- Relationship Types and Relationship Links --- p.130 / Chapter B.6 --- Relationship Inference --- p.141 / Chapter B.7 --- Weighting Schemes --- p.145

No description available.

No description available.

Information available in digital form has grown phenomenally in recent years. Finding the required information has become a difficult and challenging task. This is primarily due to the diversity and enormous volume of information available and the change in the nature of people now seeking information – from experts to ordinary users of desktop computers with varying interest and objectives. The problem of finding relevant information is further impacted by the poor retrieval effectiveness of most current information retrieval (IR) systems that are primarily based on keyword indexing techniques. Though these systems retrieve documents that contain those keywords specified in the query, the documents that are retrieved may not necessarily be in the context in which the user would have wanted them to be. This research works argues that exploiting the user’s context of the information need has the potential to improve the performance of information retrieval systems. Context can reduce the ambiguity by associating meanings to request/query terms, and thus limit the scope of the possible misinterpretations of query terms. A new way of defining context categories based on information type is proposed and this notion of context differs from the conventional way of defining information categories based on subject topics as it is closely linked with the situation in which the user’s needs for information originates. A new context-based information retrieval system where users could specify the context in which they are seeking information is presented. This work also includes a full-scale development, implementation and evaluation of the new context-based information system / Doctor of Philosophy (PhD)

A fully automated method for content-based color image retrieval is developed to extract color and shape content of an image. A color segmentation algorithm based on the k-mean clustering algorithm is used and a saturated distance is proposed to discriminate between two color points in the HSV color space. The feature set describing an image includes main object shape, which is extracted using the morphological operations. The computed image features are tagged within the image and a graphical user interface is presented for retrieving images based on the color and shape of the objects. The experimental results using natural color images demonstrate effectiveness of the proposed method. / Graduation date: 2000

Thesis (M.S.)--Naval Postgraduate School, 2002. / Thesis advisor(s): Rex Buddenberg, Steven Iatrou. Includes bibliographical references (p. 119-120). Also available online.

Thesis (Ph. D.)--Stanford University, 1986. / Cover title. "June 1986." Includes bibliographical references.

The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed February 12, 2010). Thesis advisor: Dr. Toni Kazic. Includes bibliographical references.

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