Quantitative Evaluation of Web2.0 Application

Web 2.0 is a new generation of web applications where the users are able to participate, collaborate and share the created artefacts. Web 2.0 is all about the collective intelligence. Web 2.0 applications are widely used for all the educational, professional, business and entertainment purposes. But a methodology for quantitative evaluation of web2.0 application quality is still not available. With the advancement of web technology various dimensions to evaluate web2.0 application quality is changing. So studies will be made to select a quality model that is required for web 2.0 application. Then the quantitative analysis will be done on the basis of questionnaire method and statistical formula. Quantitative analysis is necessary to know the weakness and strength of a website and then to improve the web quality. Quantitative evaluation can also be used for comparing two or more websites. In this study, quantitative analysis is done for each quality attribute of two social networking sites. Then the two sites are compared on the basis of the quantitative value of quality.

Identification of Optimal Web Page Set based on Web Usage using Biclustering Optimization Techniques

The primary objective of this chapter is to propose Biclustering Optimization Techniques (BOT) to identify the optimal web pages from web usage data. Bio-inspired optimization techniques like Firefly algorithm and its variant are used as optimization tool to generate optimal usage profile from the given web usage dataset. Finally, empirical study is conducted on the benchmark clickstream datasets like MSNBC, MSWEB and CTI and their results are analyzed to know the performance of the proposed biclustering optimization techniques with respect to optimization techniques available in the literature.

Quality Assurance Aspects of Web Design

The chapter introduces the definition of usability, usability assessment techniques to be adopted during the whole application life cycle for promoting usability. Then, the chapter includes design features for evaluating e-commerce websites such as navigation, content, design, ease of use and structure features and designing usable e-commerce websites. Then the chapter discussed the user testing method followed by a case study which comprises data collection by users' preferences, data analysis and the results. The latter in the chapter, we briefly describe the effectiveness of usability evaluation methods. Lastly, we describe the usability problem areas, strength and weaknesses on different features and sub-features of e-commerce websites followed by a conclusion.

Web based Privacy Disclosure Threats and Control Techniques

Due to advancement of internet technologies, web based applications are gaining popularity day by day. Many organizations maintain large volumes of web site based data about individuals that may carry information that cannot be revealed to the public or researchers. While web-based applications are becoming increasingly pervasive by nature, they also present new security and privacy challenges. However, privacy threats effects negatively on sensitive data and possibly leads to the leakage of confidential information. More ever, privacy preserving data mining techniques allow us to protect the sensitive data before it gets published to the public by changing the original micro-data format and contents. This chapter is intended to undertake an extensive study on some ramified disclosure threats to the privacy and PPDM (privacy preserving data mining) techniques as a unified solution to protect against threats.

Web Analytics

There is a remarkable association between an organization's analytics intricacy and its competitive enactment. The biggest problem to adopting analytics is the lack of knowledge of using it to improve business performance. A website is believed and considered as ‘face' of the company. In present era, there are more than 200 million people who buy goods online across the globe. Business Analytics helps companies to find the most profitable customer and allows them to justify their marketing effort, especially when the competition is very high. Predictive analytics helps organizations to predict churn, default in loan payment, brand switch, insurance loss and even the outcome in a football match. There is ample evidence from the corporate world that the ability to make better decisions (by management executives) improves with analytical skills. This chapter will provide an in-depth knowledge of business analytic techniques and their applications in improving business processes and decision-making.

Web Analytics for Web Site Quality Improvement

Web plays an important role in running business organizations, governments, societies, education sector, scientific organizations, social networks etc. As soon as web application has been deployed into the production environment, some or all of its features are available to the users. Web analytics is used to understand the usage pattern and its behaviour of users. The Web analytics is a procedure of measuring, collecting, analyzing and reporting of Internet data to optimize the business processes and maximize their revenue. Web Analytics is processes of inspecting, analyzing, tracking, measuring and reporting of web data for the purpose of discovering useful information, understanding web site quality, assess and improve the effectiveness of a website.

Website link Structure Optimization

The structure of a website can be represented in the form of a graph where nodes represent pages and edges represent hyperlinks among those pages. The behaviour of website users changes continuously and hence the link structure of a website should be modified frequently. The problem of optimally rearranging the link structure of a website is known as Website Structure Optimization problem. It falls in the category of combinatorial optimization problems. Many methods have been proposed and developed by the researchers to optimize the web graph structure of a website. In this chapter taxonomy of the website link structure optimization models is presented. The formulation and explanation of the working of the models have also been provided so that the readers could easily understand the methodology used by the models.

An Empirical study of Usability Metric for Websites

A Concern is any important property or area of interest of a system that can treat in a modular way. One of the most important Concerns is Usability which is considered one of the key principles in Software Engineering. The importance of Usability Evaluation has dramatically increased due to extremely fast growth in Internet technology. The website design is directly related to the purpose of the website. Website with poor usability can easily destroy the purpose of website. So, the authors have chosen one of the concern “usability” which is the core component of web applications. The purpose of this chapter is to analysis and proposes an appropriate web usability metric for evaluation of universities website. The proposed method will be based partly on a literature study and partly on the survey analysis response by visitors.

Quality Measures for Semantic Web Application

The Semantic Web is a standard of Common Data Formats on WWW with aim to convert the current web data of unstructured and semi-structured documents into a common framework that allows data to be shared and reused across applications, enterprises. The main purpose of the Semantic Web is driving the evolution of the current Web by enabling users to find, share, and combine information more easily. Humans are capable of using the Web to carry out tasks such as searching for the lowest price for a LAPTOP. However, machines cannot accomplish all of these tasks without human direction, because web pages are designed to be read by people, not machines. The semantic web is a vision of information that can be readily interpreted by machines, so machines can perform more of the tedious work involved in finding, combining, and acting upon information on the web. The chapter presents the architecture of semantic web, its challenging issues and also data quality principles. These principles provide a better decision making within organization and will maximize long term data integration and interoperability.

Enhancing the Quality of Educational Website Design through Assessment for Learning Strategies

To improve the quality of a website, many principles or guidelines have been suggested in the literature. However, the application of related principles is not a straightforward issue. It requires the web developer with high level of self-awareness to continuously review his own works and to justify the design based on related web design principles. The web developer should behave as a reflective practitioner for creating a high-quality website which fulfilled web design principles in various aspects. However, reflection cannot be implicitly assumed as an inborn ability. Certain experiences or training must be provided so as to enable the web designer to develop high level of self-reflection. In this connection, this chapter introduces a series of assessment for learning strategies with self- and peer-assessment components for transforming a web developer into a reflective practitioner. Detailed implementation, its effectiveness and participants' opinions of the self- and peer-assessment strategy of a case study will be reported.