Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 2010

Mail questionnaires are a popular and valuable method of data collection. Nonresponse bias is, however, a potentially serious threat to their validity. The best way to combat this threat is to obtain the highest possible return rate. To this end, many factors that are believed to influence return rates have been empirically studied. One factor that has not been empirically examined is the impact of item response effort on return rates, where response effort is defined as the amount of effort that is required by a respondent to answer questionnaire items. The purpose of this study was to determine if the type of item response effort required to complete a questionnaire had any differential impact on the response rate of a mailed questionnaire. For this study, two questionnaires that differed only in the level of item response effort were sent to two randomly selected and assigned groups. The first group received a mailed questionnaire with seven questions that were answered by a simple item response type (5-point Likert scale). The second group received a mailed questionnaire with seven questions that required a more difficult item response type (short answer). A large difference between the return rates of the two questionnaires was observed, with the questionnaire containing questions that could be answered on a Likert scale having a higher return rate (56%) than the questionnaire containing questions requiring a short written response (30%). The results of this study provide evidence that the difficulty of item response effort affects the response rate of mailed questionnaires. The practical application of this finding is that researchers should endeavor to keep the types of item response on mailed questionnaires as simple as possible, to maximize response rates (unless, of course, the needed information can only be elicited by providing written responses).

Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2006. / Includes bibliographical references (p. 43-45).

No description available.

EXCEL SHEET BASED SEMANTIC EMAIL Rajesekhar R, Dandolu December 10, 2004. 47 Pages Directed by: Dr. Guangming Xing Department of Computer Science Western Kentucky University The Semantic Web is an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. The Semantic Web envisions a portion of the World-Wide Web in which the underlying data is machine understandable and can thus be exploited for improved querying, aggregation, and interaction. Excel Sheet Based Semantic Email is a type of Semantic Web application, which deals with the understanding of emails received and performing corresponding actions according to the schema specified in the email. The user can compose an email structure and specify all the semantic actions and necessary information related to a particular schema. The emails received are processed according to the schema format to which they belong and corresponding semantic actions are taken. In this project, Semantic Email is implemented by encoding the information in Excel Sheets. It could be reengineered to support heterogeneous semantic actions based on the particular application. The project can be enhanced providing a web interface, apart from the email system that is currently used as the way of communication. The clients can directly use the web page,

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The electronic mail has become one of the most popular communication channels in the modern world. Due to its convenience and low cost, however, many business salesmen utilize this channel to promote their products by distributing e-mails to people as far as they can reach, which causes troubles to irrelevant e-mail receivers. As a result, many a research has been devoted to filtering irrelevant e-mails based on data mining techniques to alleviate users¡¦ mental loadings in processing e-mails they receive. Nevertheless, current approaches have their own drawbacks. Issues on what appropriate classifies to construct, how to endow such classifiers with the adaptive learning ability, and how to customize the e-mail management process for each user are still under investigation. The objective of this research is therefore to construct an e-mail classifier with learning ability to self-correct from erroneous outcomes. Furthermore, we propose a customized e-mail management process that can handle users¡¦ e-mails based on their own preferences. Ultimately, it can adapt itself to the changes of users¡¦ preferences when handling their e-mails. Several experiments are conducted to verify the performance of the constructed classifier. The results show that our proposed classifier possesses high accuracy and high precision with outstanding adaptive learning ability. We also illustrate a real application of the customized e-mail management process. It shows that our approach can detect the changes of users¡¦ preferences and learn to follow the changes. The feasibility of employing our approach to constructing e-mail classifiers is thus justified.

E-mail is changing direct marketing. A rapidly maturing set of permission e-mail marketing technologies is profoundly impacting the way companies market to their customers. Lifelong learning will be essential for everyone as we move into the 21st century and it has to be made accessible to all. Education and training systems also must play an important role. As the world moves increasingly to knowledge-based economies and societies, the emphasis given to this goal is not only right, but also it must be reinforced. In this study, we¡¦ll discuss the current situation of educational training services applying permission e-mail marketing in Taiwan. Therefore, the paper provides a good direction for researchers in e-mail marketing. Furthermore, educational training services can apply e-mail marketing strategies easily and gain benefits from them.

The spread of spam mails have become a serious threat in the Internet. In addition to commercial messages, some malicious messages such as phishing, pornography messages, fraudulent messages and malicious codes are spread via spam. A practical server-side anti-spam system should have ability to (1) filter out growing volume of spam mails correctly; (2) recognize new type of spam mails and (3) manage the increasing spam rules automatically. Most work only focused on single aspect (especially for spam rule generation) to prevent spam mail. However, in real world, spam prevention is not just applying data mining algorithm for rule generation. To filter out spam mails correctly and efficiently in a real world, there are still many issues should be considered in addition to spam rule generation. In this research, we propose and integrate three sub-systems to form a practical anti-spam system, the sub-systems are spam rule generation sub-system, spam rule sharing sub-system and spam rule management sub-system. In this research, rule-based data mining approach is used to generate manageable and shareable spam rules. The latest spam rules are shared through machine-readable XML format. Spam rules stored in mail servers are managed based on statistical testing approach. The Rule management sub-system can automatically enable high performance rules and disable out-of-date rules to improve the miss rate and efficiency of spam filter. This research will develop and integrate the three sub-systems to achieve the goal of spam prevention.

Hamburg, Universität, Thesis (doctoral), 2001.