Observations of textual document management by individuals and organizations have suggested the popularity of using categories (e.g., folders) to organize, archive and access documents. The document grouping behavior is intentional acts, reflecting a user¡¦s preferential perspective on semantic coherency or relevant groupings between subjects. Although becoming less adequate as new documents are accumulated, the existing category set or hierarchy may preserve to some extent the user¡¦s preferential perspective on document grouping. Thus, when deriving a new category set or hierarchy, the category set or hierarchy previously established by the user (i.e., semantic coherency of the documents embedded in the existing category set or category hierarchy) should be taken into consideration. In this study, we have proposed an evolution-based technique, Category Hierarchy Evolution (CHE), for managing category hierarchy rather than category set. Specifically, in CHE, the overall similarity between two documents is measured not only by their content similarity but also by their location similarity in the existing category hierarchy. Our empirical evaluation results suggest that the proposed CHE technique outperformed the discovery-based technique (i.e., the traditional content-based document-clustering technique).

A typical online knowledge-sharing environment would generate vast amount of formal knowledge elements or interactions that generally available as textual documents. Thus, an effective management of the ever-increasing volume of online knowledge documents is essential to organizational knowledge sharing. Reply-semantic relationships between knowledge documents may exist either explicitly or implicitly. Such reply-semantic relationships between knowledge documents, once discovered or identified, would facilitate subsequent knowledge access by providing a novel and more semantic retrieval mechanism. In this study, we propose a preliminary taxonomy of reply-semantic relationships for documents organized in reply-replied structures and develop a SEmantic Enrichment between Knowledge documents (SEEK) technique for automatically annotating reply-semantic relationships between reply-pair documents. Based on the content-based text categorization techniques and genre classification techniques, we propose and evaluate different feature-set models, combinations of keyword features, POS statistics features, and/or given/new information (GI/NI) features. Our empirical evaluation results show that the proposed SEEK technique can achieve a satisfactory classification accuracy. Furthermore, use of keyword and GI/NI features by the proposed SEEK technique resulted in the best classification accuracy for the Answer/Comment classification task. On the other hand, the use of keyword features only can best differentiate Explanation and Instruction relationships.

The central government and most of local governments in Taiwan have adopted the e-mail services to provide citizens for requesting services or expressing their opinions through Internet. Traditionally, these requests/opinions need to be manually classified into appropriate departments for service rendering. However, due to the ever-increasing number of requests/opinions received, the manual classification approach is time consuming and becomes impractical. Therefore, in this study, we attempt to apply text categorization techniques for constructing automatically a classification mechanism in order to establish an efficient e-government service portal. The purpose of this thesis is to investigate effectiveness of different text categorization methods in supporting automatic classification of service requests/opinions emails sent to Mayor¡¦s mailbox. Specifically, in each phase of text categorization learning, we adopt and evaluate two methods commonly employed in prior research. In the feature selection phase, both the maximal x2¡@statistic method and the weighted average x2¡@statistic method of x2¡@statistic are evaluated. We consider the Binary and TFxIDF representation schemes in the document representation phase. Finally, we adopt the decision tree induction technique and the support vector machines (SVM) technique for inducing a text categorization model for our target e-government application. Our empirical evaluation results show that the text categorization method that employs the maximal x2 statistic method for feature selection, the Binary representation scheme, and the support vector machines as the underlying induction algorithm can reach an accuracy rate of 77.28% and an recall and precision rates of more than 77%. Such satisfactory classification effectiveness suggests that the text categorization approach can be employed to establish an effective and intelligent e-government service portal.

Environmental scanning is an important process, which acquires and uses the information about events, trends, and relationships in an organization's external environment. It permits an organization to adapt to its environment and to develop effective responses to secure or improve their position in the future. Event detection technique that identifies the onset of new events from streams of news stories would facilitate the process of organization's environmental scanning. However, traditional feature-based event detection techniques, which identify whether a news story contains an unseen event by comparing the similarity of words between the news story and past news stories, incur some limitations (e.g., the features shown in news document cannot actually represent the event described in it.). Thus, in this study, we developed an information extraction-based event detection (NEED) technique that combines information extraction and text categorization techniques to address the problems inherent to traditional feature-based event detection techniques. The empirical evaluation results showed that the NEED technique outperformed the traditional feature-based event detection techniques in miss rate and false alarm rate and achieved comparable event association accuracy rate to its counterpart.

ABSTRACT For long, scholars have been using the research tools invented in the western world to examine the leadership styles developed in western societies. With so many cultural differences between western and eastern societies, it¡¦s very difficult to explain the leadership styles and phenomena of Chinese leaders if only the same research tools are applied. In the past, many researches on the relationship between leadership behavior and leadership effectiveness were only focused on leadership behavior before leadership effectiveness was narrated; however, whether a leadership style works or how effectively it works isn¡¦t decided by the leader only. Thus, in this study, 297 pairs of supervisors and subordinates from 30 banks in central Taiwan (2 regional centers and 63 branches) were selected for an empirical study. Their background information was collected for the analysis of chaxu geju¡Xa criterion of categorization for relationship, loyalty and capability. Every subordinate was categorized into an ¡§insider¡¨ or ¡§outsider¡¨ according to the perception of his/her supervisor. Then, the relationship between the performance of every subordinate and the leadership behavior (patriarchal leadership: authoritarianism, benevolence and moral) of his/her supervisor were analyzed for leadership effectiveness. The findings of this study showed the Chinese supervisors would objectively categorize their subordinates into ¡§insiders¡¨ and ¡§outsiders¡¨ according to the rank of relationship, loyalty and capability. The supervisors tended to give ¡§insiders¡¨ better performance evaluation. The insiders felt they were given more benevolence and moral, but less authoritarianism; the outsiders felt just the opposite. The Chinese supervisors had greater personal attachment to the insiders and allocated more resources to them, so the insiders had better work attitude and performance; the outsiders was the contrary. Without equal treatment, the leadership effectiveness in the insiders and in the outsiders was different. Finally a concrete brief on the limitations of the study, further research direction in the future and how the study was related to the management in the real world was presented. Key words: chaxu geju (a multiplicity of individual distinctions of rank and distance), criterion of categorization, leadership behavior, leadership effectiveness

Organizations use work teams to solve complex problems in innovative ways. As such, an abundance of diverse ideas, suggestions, and information should help organizations generate quality products and remain competitive. Yet, there is research which shows that women do not participate as much as men in face-to-face team interactions. Women often get fewer speaking turns than men, they speak for shorter lengths of time, and they are interrupted more often than men. As a result, women?s ideas may often be overlooked in work settings. This is problematic, because women make up 46 percent of the United States workforce, and not being active participants in meetings could results in underutilization of roughly half of the firm?s human capital. This study investigated whether the order of face-to-face and virtual communication used by virtual teams could be used as one means of increasing inclusion and participation of women in male-dominated teams. Results from 82 teams confirmed that women felt more included in the team when they communicated virtually first and then face-to-face as opposed to face-to-face first and then virtually. Findings supported a four-stage model where the medium of communication influences feelings of inclusion which influences participation (both self-reported and objective). Participation, in turn, influences perceptions of interpersonal justice, satisfaction with the team, and ratings received from team members. An objective measure of participation and team performance ratings from five independent raters also show that the more equally team members participate and the higher the team?s total communication volume, in both total speaking turns and words spoken, the higher the team?s ratings and the more creative the team?s output was judged to be.

In a democratic society, the number of public opinion documents increase with days, and there is a pressing need for automatically classifying these documents. Traditional approach for classifying documents involves the techniques of segmenting words and the use of stop words, corpus, and grammar analysis for retrieving the key terms of documents. However, with the emergence of new terms, the traditional methods that leverage dictionary or thesaurus may incur lower accuracy. Therefore, this study proposes a new method that does not require the prior establishment of a dictionary or thesaurus, and is applicable to documents written in any language and documents containing unstructured text. Specifically, the classification method employs genetic algorithm for achieving this goal. In this method, each training document is represented by several chromosomes, and based on the gene values of these chromosomes, the characteristic terms of the document are determined. The fitness function, which is required by the genetic algorithm for evaluating the fitness of an evolved chromosome, considers the similarity to the chromosomes of documents of other types. This study used data FAQ of e-mail box of Taipei city mayor for evaluating the proposed method by varying the length of documents. The results show that the proposed method achieves the average accuracy rate of 89%, the average precision rate of 47%, and the average recall rate of 45%. In addition, F-measure can reach up to 0.7. The results confirms that the number of training documents, content of training documents, the similarity between the types of documents, and the length of the documents all contribute to the effectiveness of the proposed method.

Thesis (Ph. D.)--University of California, San Diego, and San Diego State University, 2004. / Vita. Includes bibliographical references.

Thesis (M.A.)--Miami University, Dept. of Speech Pathology and Audiology, 2003. / Title from first page of PDF document. Document formatted into pages; contains vii, 66 p. Includes bibliographical references (p. 53-59).

This study seeks to investigate this core research topic: how identity is involved in everyday interactions between Chinese microblogging website users? By understanding identity as an element in the interaction context of discursive practices, the investigation is achieved through the analysis of naturally occurring text-based online data. Conversation Analysis (CA) and Membership Categorization Analysis (MCA) are used to do the analysis. The former will focus on the interaction structure while the latter will be used to make some of the contents in the interactions relevant. This study seeks to make the “orderliness” (Sacks, 1972) and “members’ methods” (Garfinkel, 1967) under a particular context describable and analyzable. The sequential and categorical organization described in this study shows how members are oriented to identities in the in situ context when they exchange their ideas on a sensitive topic, and on a microblogging website. / text