THESIS Submitted in fulfilment of the requirements for the degree MAGISTER TECHNOLOGIAE in INFORMATION TECHNOLOGY in the FACULTY OF BUSINESS INFORMATICS at the CAPE PENINSULA UNIVERSITY OF TECHNOLOGY 2005 / The aim of this research was to determine how search engine exclusion policies and spam affect the indexing of e-Commerce websites. The Internet has brought along new ways of doing business. The unexpected growth of the World Wide Web made it essential for firms to adopt e-commerce as a means of obtaining a competitive edge. The introduction of e-commerce in turn facilitated the breaking down of physical barriers that were evident in traditional business operations. It is important for e-commerce websites to attract visitors, otherwise the website content is irrelevant. Websites can be accessed through the use of search engines, and it is estimated that 88% of users start with search engines when completing tasks on the web. This has resulted in web designers aiming to have their websites appear in the top ten search engine result list, as a high placement of websites in search engines is one of the strongest contributors to a commercial website’s success. To achieve such high rankings, web designers often adopt Search Engine Optimization (SEO) practices. Some of these practices invariably culminate in undeserving websites achieving top rankings. It is not clear how these SEO practices are viewed by search engines, as some practices that are deemed unacceptable by certain search engines are accepted by others. Furthermore, there are no clear standards for assessing what is considered good or bad SEO practices. This confuses web designers in determining what is spam, resulting in the amount of search engine spam having increased over time, impacting adversely on search engine results. From the literature reviewed in this thesis, as well as the policies of five top search engines (Google, Yahoo!, AskJeeves, AltaVista, and Ananzi), this author was able to compile a list of what is generally considered as spam. Furthermore, 47 e-commerce websites were analysed to determine if they contain any form of spam. The five major search engines indexed some of these websites. This enabled the author to determine to what extent search engines adhere to their policies. This analysis returned two major findings. A small amount of websites contained spam, and from the pre-compiled list of spam tactics, only two were identified in the websites, namely keyword stuffing and page redirects. Of the total number of websites analysed, it was found that 21.3% of the websites contained spam. From these findings, the research contained in this thesis concluded that search engines adhere to their own policies, but lack stringent controls for the majority of websites that contained spam, and were still listed by search engines. In this study, the author only analysed e-commerce websites, and cannot therefore generalise the results to other websites outside ecommerce.

Thesis (DTech (Information Technology))Cape Peninsula University of Technology, 2011 / It was concluded in the literature review that small- to medium-sized enterprises (SMME) should prioritise utilising the websites on the Internet, as it provides a low cost infrastructure, unlocking opportunities and allowing small- to medium-sized enterprises to market to the international customer, promoting business activities in a low-risk environment. However, visitors do not know that they do not know, meaning a need for facilitation exists between the Internet user in terms of the information required and the information available on the Internet. Search engines (governed by their organic ranking algorithms) were created for this very purpose, to facilitate users in finding relevant information on the Internet in the shortest time possible. Search engines interpret and evaluate any given indexed web page from a targeted keywords perspective, indicating that web pages must be optimised from a search engine perspective. However, the elements search engines perceive to be important may not always be aligned with what website visitors perceive to be important. Anything on the web page that may remotely impede the visitors’ experience could be detrimental as alternative website options are but a click away. An example would be the excessive use of content on a given web page. The search engine may find the excessive content useful as it may provide contextual interpretation of the web page. However, the excessive content may impede a visitor’s website interaction as it is estimated that the average visitors will often view a web page for 45-60 seconds and read a maximum of 200 words only. During the process of identifying the contradictory search engine optimisation (SEO) elements and website usability (WU) attributes, three journal articles were written, with two journal articles following their own research methodologies and the third journal article utilising all the research results in order to create the fused SEO and WU model. Journal Article 1: Two websites were used as part of the experiment: • Control Website (CW): http://www.copywriters.co.za • Experimental Website (EW): http://www.copywriters.co.za/ppc/. The CW is an existing website with no special emphasis applied to SEO and/or WU. The EW was developed by implementing the WU attributes and ignoring all contradictory SEO elements. In order to ensure integrity of the experiment, search engines were denied access to the EW. The traffic sources for the CW were search engines (organic) traffic, as well as direct and referrer traffic.

Content of this thesis is dedicated to problematics of design and implementation of a web base video player with slides as a JavaScript plugin. As the outcome of this thesis is supposed to replace an already existing player , the first chapter is dedicated to it's throughout analysis . Following chapters are the dedicated to desing , implementation and testing of the player , using information acquired in the phase of analysis .

The contents of Section 2.2 and Chapter 4 first appeared in proceedings of the 12th International Conference on Web Information Systems and Technologies, 2016 (www.webist.org). The contents of Section 2.3 and Chapter 5 first appeared in DBSJ Journal, vol. 14, article no. 2, March 2016. The contents of Section 2.5 and Chapter 7 first appeared in proceedings of the 11th Asia Information Retrieval Societies Conference, Lecture Notes in Computer Science, vol. 9460, pp. 188-200, 2015 (The final publication is available at link.springer.com). / 京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19854号 / 情博第605号 / 新制||情||105(附属図書館) / 32890 / 京都大学大学院情報学研究科社会情報学専攻 / (主査)教授 田島 敬史, 教授 田中 克己, 教授 吉川 正俊 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

A growing number of information retrieval applications rely on search behavior aggregated over many users. If aggregated data such as search query reformulations is not handled properly, it can allow users to be identified and their privacy compromised. Besides leveraging aggregate data, it is also common for applications to make use of user-specific behavior in order to provide a personalized experience for users. Unlike aggregate data, privacy is not an issue in individual personalization since users are the only consumers of their own data. The goal of this work is to explore the effects of personalization and privacy preservation methods on three information retrieval applications, namely search task identification, task-aware query recommendation, and searcher frustration detection. We pursue this goal by first introducing a novel framework called CrowdLogging for logging and aggregating data privately over a distributed set of users. We then describe several privacy mechanisms for sanitizing global data, including one novel mechanism based on differential privacy. We present a template for describing how local user data and global aggregate data are collected, processed, and used within an application, and apply this template to our three applications. We find that sanitizing feature vectors aggregated across users has a low impact on performance for classification applications (search task identification and searcher frustration detection). However, sanitizing free-text query reformulations is extremely detrimental to performance for the query recommendation application we consider. Personalization is useful to some degree in all the applications we explore when integrated with global information, achieving gains for search task identification, task-aware query recommendation, and searcher frustration detection. Finally we introduce an open source system called CrowdLogger that implements the CrowdLogging framework and also serves as a platform for conducting in-situ user studies of search behavior, prototyping and evaluating information retrieval applications, and collecting labeled data.

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This research is an integral part of the effort aimed at overcoming the limitations of the classic search engines. This thesis is concerned with the investigation of the impact of different modes of mediation on the web search process. Conceptually, it is divided into three main parts. The first part details the investigation of methods and mechanisms in user profile generation and in filtering search results. The second part deals with the presentation of an approach and its application in the development of a mediation framework between the user and the classic Web Search engines. This involved the integration of the explicit, implicit and hybrid modes of mediation within a content-based method, and was facilitated by the adoption of the Vector Space Model. The third part presents an extensive comparative evaluation of the impact of the different types of mediation systems on web search, in terms of precision, recall and F-measure. The thesis concludes by identifying the contribution of the research programme and the satisfaction of the stated objectives.

Due to rapid growth of the number of Web pages, web users encounter two main problems, namely: many of the retrieved documents are not related to the user query which is called low precision, and many of relevant documents have not been retrieved yet which is called low recall. Information Retrieval (IR) is an essential and useful technique for Web search; thus, different approaches and techniques are developed. Because of its parallel mechanism with high-dimensional space, Genetic Algorithm (GA) has been adopted to solve many of optimization problems where IR is one of them. This thesis proposes searching model which is based on GA to retrieve HTML documents. This model is called IR Using GA or IRUGA. It is composed of two main units. The first unit is the document indexing unit to index the HTML documents. The second unit is the GA mechanism which applies selection, crossover, and mutation operators to produce the final result, while specially designed fitness function is applied to evaluate the documents. The performance of IRUGA is investigated using the speed of convergence of the retrieval process, precision at rank N, recall at rank N, and precision at recall N. In addition, the proposed fitness function is compared experimentally with Okapi-BM25 function and Bayesian inference network model function. Moreover, IRUGA is compared with traditional IR using the same fitness function to examine the performance in terms of time required by each technique to retrieve the documents. The new techniques developed for document representation, the GA operators and the fitness function managed to achieves an improvement over 90% for the recall and precision measures. And the relevance of the retrieved document is much higher than that retrieved by the other models. Moreover, a massive comparison of techniques applied to GA operators is performed by highlighting the strengths and weaknesses of each existing technique of GA operators. Overall, IRUGA is a promising technique in Web search domain that provides a high quality search results in terms of recall and precision.