by Lucy M.S. Kwan. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1989. / Bibliography: leaf 41.

by Jacqueline, Wai-ting Wong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (p. 107-109). / Abstract --- p.i / Acknowledgement --- p.iii / List of Tables --- p.viii / List of Figures --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Chinese Information Processing --- p.6 / Chapter 2.1 --- Chinese Word Segmentation --- p.7 / Chapter 2.1.1 --- Statistical Method --- p.8 / Chapter 2.1.2 --- Probabilistic Method --- p.9 / Chapter 2.1.3 --- Linguistic Method --- p.10 / Chapter 2.2 --- Automatic Indexing --- p.10 / Chapter 2.2.1 --- Title Indexing --- p.11 / Chapter 2.2.2 --- Free-Text Searching --- p.11 / Chapter 2.2.3 --- Citation Indexing --- p.12 / Chapter 2.3 --- Information Retrieval Systems --- p.13 / Chapter 2.3.1 --- Users' Assessment of IRS --- p.13 / Chapter 2.4 --- Concluding Remarks --- p.15 / Chapter 3 --- Survey on Classification --- p.16 / Chapter 3.1 --- Text Classification --- p.17 / Chapter 3.2 --- Survey on Classification Schemes --- p.18 / Chapter 3.2.1 --- Commonly Used Classification Systems --- p.18 / Chapter 3.2.2 --- Classification of Newspapers --- p.31 / Chapter 3.3 --- Concluding Remarks --- p.37 / Chapter 4 --- System Models and the ACTION Algorithm --- p.38 / Chapter 4.1 --- Factors Affecting Systems Performance --- p.38 / Chapter 4.1.1 --- Specificity --- p.39 / Chapter 4.1.2 --- Exhaustivity --- p.40 / Chapter 4.2 --- Assumptions and Scope --- p.42 / Chapter 4.2.1 --- Assumptions --- p.42 / Chapter 4.2.2 --- System Scope ´ؤ Data Flow Diagrams --- p.44 / Chapter 4.3 --- System Models --- p.48 / Chapter 4.3.1 --- Article --- p.48 / Chapter 4.3.2 --- Matching Table --- p.49 / Chapter 4.3.3 --- Forest --- p.51 / Chapter 4.3.4 --- Matching --- p.53 / Chapter 4.4 --- Classification Rules --- p.54 / Chapter 4.5 --- The ACTION Algorithm --- p.56 / Chapter 4.5.1 --- Algorithm Design Objectives --- p.56 / Chapter 4.5.2 --- Measuring Node Significance --- p.56 / Chapter 4.5.3 --- Pseudocodes --- p.61 / Chapter 4.6 --- Concluding Remarks --- p.64 / Chapter 5 --- Analysis of Results and Validation --- p.66 / Chapter 5.1 --- Seeking for Exhaustivity Rather Than Specificity --- p.67 / Chapter 5.1.1 --- The News Article --- p.67 / Chapter 5.1.2 --- The Matching Results --- p.68 / Chapter 5.1.3 --- The Keyword Values --- p.68 / Chapter 5.1.4 --- Analysis of Classification Results --- p.71 / Chapter 5.2 --- Catering for Hierarchical Relationships Between Classes and Subclasses --- p.72 / Chapter 5.2.1 --- The News Article --- p.72 / Chapter 5.2.2 --- The Matching Results --- p.73 / Chapter 5.2.3 --- The Keyword Values --- p.74 / Chapter 5.2.4 --- Analysis of Classification Results --- p.75 / Chapter 5.3 --- A Representative With Zero Occurrence --- p.78 / Chapter 5.3.1 --- The News Article --- p.78 / Chapter 5.3.2 --- The Matching Results --- p.79 / Chapter 5.3.3 --- The Keyword Values --- p.80 / Chapter 5.3.4 --- Analysis of Classification Results --- p.81 / Chapter 5.4 --- Statistical Analysis --- p.83 / Chapter 5.4.1 --- Classification Results with Highest Occurrence Frequency --- p.83 / Chapter 5.4.2 --- Classification Results with Zero Occurrence Frequency --- p.85 / Chapter 5.4.3 --- Distribution of Classification Results on Level Numbers --- p.86 / Chapter 5.5 --- Concluding Remarks --- p.87 / Chapter 5.5.1 --- Advantageous Characteristics of ACTION --- p.88 / Chapter 6 --- Conclusion --- p.93 / Chapter 6.1 --- Perspectives in Document Representation --- p.93 / Chapter 6.2 --- Classification Schemes --- p.95 / Chapter 6.3 --- Classification System Model --- p.95 / Chapter 6.4 --- The ACTION Algorithm --- p.96 / Chapter 6.5 --- Advantageous Characteristics of the ACTION Algorithm --- p.96 / Chapter 6.6 --- Testing and Validating the ACTION algorithm --- p.98 / Chapter 6.7 --- Future Work --- p.99 / Chapter 6.8 --- A Final Remark --- p.100 / Chapter A --- System Models --- p.102 / Chapter B --- Classification Rules --- p.104 / Chapter C --- Node Significance Definitions --- p.105 / References --- p.107

Electronic commerce (e-commerce) markets provide benefits for both buyers and sellers; however, because of cyber security risks consumers are reluctant to transact online. Trust in e-commerce is paramount for adoption. Trust as a subject for research has been a term considered in depth by numerous researchers in various fields of study, including psychology and information technology. Various models have been developed in e-commerce to alleviate consumer fears, thus promoting trust in online environments. Third-party web seals and online scanning tools are some of the existing models used in e-commerce environments, but they have some deficiencies, e.g. failure to incorporate compliance, which need to be addressed. This research proposes an e-commerce assurance model for safe online shopping. The machine learning model is called the Page ranking analytical hierarchy process (PRAHP). PRAHP builds complementary strengths of the analytical hierarchy process (AHP) and Page ranking (PR) techniques to evaluate the trustworthiness of web attributes. The attributes that are assessed are Adaptive legislation, Adaptive International Organisation for Standardisation Standards, Availability, Policy and Advanced Security login. The attributes were selected based on the literature reviewed from accredited journals and some of the reputable e-commerce websites. PRAHP’s paradigms were evaluated extensively through detailed experiments on business-to-business, business-to-consumer, cloud-based and general e-commerce websites. The results of the assessments were validated by customer inputs regarding the website. The reliability and robustness of PRAHP was tested by varying the damping factor and the inbound links. In all the experiments, the results revealed that the model provides reliable results to guide customers in making informed purchasing decisions. The research also reveals hidden e-commerce topics that have not received attention, which generates knowledge and opens research questions for future researchers. These ultimately made significant contributions in e-commerce assurance, in areas such as security and compliance through the fusing of AHP and PR, integrated into a decision table for alleviating trustworthiness anxiety in various e-commerce transacting partners, e-commerce platforms and markets. / College of Engineering, Science and Technology / D. Phil. Information Systems

Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Includes bibliographical references. / by Cheryl Ann Wheeler. / B.S.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1982. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING / Includes bibliographical references. / by Susan Aileen Hall. / M.S.

by Leung Ho-Yin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1997. / Includes bibliographical references (leaves 82-89). / Abstract --- p.ii / Table of Contents --- p.iv / LIST of Figures --- p.viii / List of Tables --- p.ix / Acknowledgments --- p.xi / Chapter / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Intensive Care Unit --- p.2 / Chapter 1.1.1 --- Expensive Costs of Intensive Care --- p.2 / Chapter 1.1.2 --- Tremendous Demands with Limited Resources --- p.3 / Chapter 1.1.3 --- Conflicting Roles of ICU Physicians --- p.3 / Chapter 1.1.4 --- Disorganized Patient Information --- p.4 / Chapter 1.2 --- ICU Management Problems --- p.5 / Chapter 1.3 --- Executive Information Systems (EIS) for ICU Physician --- p.6 / Chapter 1.4 --- Determine Information Requirements of the EIS --- p.7 / Chapter 1.5 --- Scope of the Study --- p.8 / Chapter 1.6 --- Organization of the Report --- p.8 / Chapter 2. --- Literature Review --- p.9 / Chapter 2.1 --- Intensive Care Unit --- p.9 / Chapter 2.1.1 --- Costs of ICU --- p.10 / Chapter 2.2 --- ICU Physicians are Executives --- p.10 / Chapter 2.3 --- Computers in ICU --- p.11 / Chapter 2.3.1 --- Record Keeping --- p.11 / Chapter 2.3.2 --- Data Management --- p.12 / Chapter 2.3.3 --- Decision Making --- p.13 / Chapter 2.4 --- Problems Facing ICU Physicians --- p.14 / Chapter 2.4.1 --- Conflicting Role --- p.14 / Chapter 2.4.2 --- Information Overload --- p.14 / Chapter 2.4.3 --- Poor Information Quality --- p.15 / Chapter 2.4.4 --- Technophobia --- p.16 / Chapter 2.5 --- Executive Information Systems --- p.16 / Chapter 2.5.1 --- Definition --- p.16 / Chapter 2.5.2 --- Characteristics of EIS --- p.17 / Chapter 2.5.3 --- EIS in Healthcare Industry --- p.20 / Chapter 2.6 --- Determining Information Requirements --- p.20 / Chapter 2.6.1 --- Strategies and Methods to Determine Information Requirements --- p.21 / Chapter 2.6.2 --- Critical Success Factors Analysis --- p.25 / Chapter 2.6.2.1 --- Definition of CSFs --- p.26 / Chapter 2.6.2.2 --- Different Executives Have Different CSFs and Different Information Needs --- p.26 / Chapter 2.6.2.3 --- Hierarchical Nature of CSFs --- p.26 / Chapter 2.6.2.4 --- Steps in the CSFs Approach --- p.28 / Chapter 2.6.2.5 --- "Critical Information, Assumptions, and Decisions" --- p.29 / Chapter 3. --- Research Methodology --- p.31 / Chapter 3.1 --- Literature Review --- p.31 / Chapter 3.2 --- Design a Methodology for Information Requirements Determination --- p.32 / Chapter 3.3 --- ICU Admission Case Study --- p.34 / Chapter 3.4 --- Analysis and Validation --- p.35 / Chapter 3.5 --- COPD Survey: The Importance of Medical History --- p.36 / Chapter 3.5.1 --- Chronic Obstructive Pulmonary Disease --- p.36 / Chapter 3.5.2 --- The Survey --- p.38 / Chapter 4. --- A Three-Stage Methodology --- p.41 / Chapter 4.1 --- Stage 1 - Understanding ICU Operations --- p.42 / Chapter 4.2 --- Stage 2 - Determine CSFs within the ICU --- p.43 / Chapter 4.2.1 --- CSFs Analysis Steps in the Study --- p.44 / Chapter 4.2.2 --- Step 1: Determine CSFs of ICUs --- p.44 / Chapter 4.2.3 --- Step 2: Determine CSFs of the ICU Physicians --- p.45 / Chapter 4.2.4 --- Step 3: Determine CSFs of the ICU Admission --- p.45 / Chapter 4.3 --- Stage 3 譯 Determine Information Requirements --- p.45 / Chapter 4.4 --- Importance of Medical History: A COPD Survey --- p.46 / Chapter 4.4.1 --- COPD Questionnaire --- p.46 / Chapter 5. --- Findings --- p.48 / Chapter 5.1 --- Findings in Stage 1 --- p.48 / Chapter 5.1.1 --- Decision Making in ICU --- p.49 / Chapter 5.2 --- Findings in Stage 2 - CSFs --- p.54 / Chapter 5.2.1 --- CSFs of the ICU --- p.54 / Chapter 5.2.2 --- CSFs of the ICU Physicians --- p.56 / Chapter 5.2.3 --- CSFs of the ICU Admission --- p.56 / Chapter 5.3 --- Findings in Stage 3 --- p.58 / Chapter 5.3.1 --- Types of Information Requirement --- p.58 / Chapter 5.3.2 --- Detailed Contents of the Information Requirements --- p.59 / Chapter 6. --- Analysis --- p.65 / Chapter 6.1 --- A Three-Stage Methodology for Information Requirements Determination --- p.65 / Chapter 6.1.1 --- Comparison of the Three-Stage Methodology with CSFs Analysis --- p.66 / Chapter 6.1.2 --- A Case Study Using the Three-Stage Methodology --- p.67 / Chapter 6.2 --- Roles of Information Types in Admission Decision --- p.68 / Chapter 6.2.1 --- Admitting Patients from Different Sources --- p.69 / Chapter 6.2.2 --- Admitting Patients with Different Diseases --- p.70 / Chapter 6.3 --- The Importance of Medical History --- p.71 / Chapter 7 --- Conclusions --- p.78 / Bibliography --- p.82 / Interviews --- p.90 / Appendices --- p.91

Chan, Shing Kai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 106-114). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgements --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Problem Statement --- p.2 / Chapter 1.2 --- Motivation for Story Segmentation --- p.4 / Chapter 1.3 --- Terminologies --- p.5 / Chapter 1.4 --- Thesis Goals --- p.6 / Chapter 1.5 --- Thesis Organization --- p.8 / Chapter 2 --- Background Study --- p.9 / Chapter 2.1 --- Coherence-based Approaches --- p.10 / Chapter 2.1.1 --- Defining Coherence --- p.10 / Chapter 2.1.2 --- Lexical Chaining --- p.12 / Chapter 2.1.3 --- Cosine Similarity --- p.15 / Chapter 2.1.4 --- Language Modeling --- p.19 / Chapter 2.2 --- Feature-based Approaches --- p.21 / Chapter 2.2.1 --- Lexical Cues --- p.22 / Chapter 2.2.2 --- Audio Cues --- p.23 / Chapter 2.2.3 --- Video Cues --- p.24 / Chapter 2.3 --- Pros and Cons and Hybrid Approaches --- p.25 / Chapter 2.4 --- Chapter Summary --- p.27 / Chapter 3 --- Experimental Corpora --- p.29 / Chapter 3.1 --- The TDT2 and TDT3 Multi-language Text Corpus --- p.29 / Chapter 3.1.1 --- Introduction --- p.29 / Chapter 3.1.2 --- Program Particulars and Structures --- p.31 / Chapter 3.2 --- Data Preprocessing --- p.33 / Chapter 3.2.1 --- Challenges of Lexical Chain Formation on Chi- nese Text --- p.33 / Chapter 3.2.2 --- Word Segmentation for Word Units Extraction --- p.35 / Chapter 3.2.3 --- Part-of-speech Tagging for Candidate Words Ex- traction --- p.36 / Chapter 3.3 --- Chapter Summary --- p.37 / Chapter 4 --- Indication of Lexical Cohesiveness by Lexical Chains --- p.39 / Chapter 4.1 --- Lexical Chain as a Representation of Cohesiveness --- p.40 / Chapter 4.1.1 --- Choice of Word Relations for Lexical Chaining --- p.41 / Chapter 4.1.2 --- Lexical Chaining by Connecting Repeated Lexi- cal Elements --- p.43 / Chapter 4.2 --- Lexical Chain as an Indicator of Story Segments --- p.48 / Chapter 4.2.1 --- Indicators of Absence of Cohesiveness --- p.49 / Chapter 4.2.2 --- Indicator of Continuation of Cohesiveness --- p.58 / Chapter 4.3 --- Chapter Summary --- p.62 / Chapter 5 --- Indication of Story Boundaries by Lexical Chains --- p.63 / Chapter 5.1 --- Formal Definition of the Classification Procedures --- p.64 / Chapter 5.2 --- Theoretical Framework for Segmentation Based on Lex- ical Chaining --- p.65 / Chapter 5.2.1 --- Evaluation of Story Segmentation Accuracy --- p.65 / Chapter 5.2.2 --- Previous Approach of Story Segmentation Based on Lexical Chaining --- p.66 / Chapter 5.2.3 --- Statistical Framework for Story Segmentation based on Lexical Chaining --- p.69 / Chapter 5.2.4 --- Post Processing of Ratio for Boundary Identifi- cation --- p.73 / Chapter 5.3 --- Comparing Segmentation Models --- p.75 / Chapter 5.4 --- Chapter Summary --- p.79 / Chapter 6 --- Analysis of Lexical Chains Features as Boundary Indi- cators --- p.80 / Chapter 6.1 --- Error Analysis --- p.81 / Chapter 6.2 --- Window Length in the LRT Model --- p.82 / Chapter 6.3 --- The Relative Importance of Each Set of Features --- p.84 / Chapter 6.4 --- The Effect of Removing Timing Information --- p.92 / Chapter 6.5 --- Chapter Summary --- p.96 / Chapter 7 --- Conclusions and Future Work --- p.98 / Chapter 7.1 --- Contributions --- p.98 / Chapter 7.2 --- Future Works --- p.100 / Chapter 7.2.1 --- Further Extension of the Framework --- p.100 / Chapter 7.2.2 --- Wider Applications of the Framework --- p.105 / Bibliography --- p.106

The necessity for a functional user friendly laboratory data management program has become evident as the quantity of information required for modern scientific research has increased to to titanic proportions. The required union of strong computer power, ease of operation, and adaptability have until recently been outside the realm of most research laboratories. Previous systems, in addition to their high cost, are necessarily complex and require software experts in order to effect any changes that the end user might deem necessary. This study examines the Apple Macintosh computer program Hypercard as an interactive laboratory information system that is user-friendly, cost effective, and adaptable to the changing demands within a modern molecular or microbiology.

Abstract not available

The purpose of this study was to explore the factors that influence the ability of teachers and administrators to use data obtained from a data warehouse to inform instruction. The mixed methods study was guided by the following questions: 1) What data warehouse application features affect the ability of an educator to effectively use the application for data driven decision making? 2) What sorts of training or professional development and workplace norms are needed to help educators use data warehouse applications more effectively? 3) How do differences in leadership affect an organization's use of data warehouse applications? 4) What, if any, impact has the use of data warehouse applications had on instructional strategies and student performance? Forty-five teachers and administrators completed the survey. A focus group of four administrators and interviews with four teachers provided qualitative data. Descriptive statistics were used to analyze the quantitative data. The qualitative data was coded in several cycles to determine common themes. The results from the qualitative and quantitative data were then compared to determine areas of similarities and differences. The factors that influenced an educator's ability to use a data warehouse application to inform instruction included ease of use of the application, access to student data in a timely manner, and the ability to view data on individual students and small groups of students. The type of data most useful to the participants was summative and formative assessment data. Training and workplace norms influenced the use of the application. The more training received, the easier the educators found the application was to use. Dedicated time to review data and the opportunity to collaborate with colleagues also enhanced the ability of educators to use the application to inform instruction. Educators who thought the use of the application was important to building and district level administrators tended to use the application more frequently. Based on the educator's perceptions, the use of the data warehouse application appeared to have some impact on influencing changes in instructional strategies. Any changes in student performance were attributed to the changes in instructional strategies. Two unexpected findings emerged from this study. The ability to use technology affected an educator���s use of the data warehouse application. A greater comfort level with the use of technology in general was attributed to greater use of the application. Finally, educators needed to have sufficient skills in the use of data in the data driven decision making process to successfully implement the use of the data warehouse application. / Graduation date: 2013