Structure-based analysis of Web sites

The performance of information retrieval on the Web is heavily influenced by the organization of Web pages, user navigation patterns, and guidance-related functions. Having observed the lack of measures to reflect this factor, this paper focuses on an approach based on both structure properties and navigation data to analyze and improve the performance of Web site. Two types of indices are defined two major factors for analysis and improvement- "aaccessibility" reflects the structure property to measure how easy the user can access the pages and "popularity" implies the navigation data primarily based on the log statistics. The accessibility and popularity (A-P) plot serves as a compass for the Web designer to get an overview of current performance status and explore in the possible directions for improvement to balance the design anticipation and navigation expectation.published_or_final_versio

Design and evaluation of improvement method on the Web information navigation - a stochastic search approach

With the advent of fast growing Internet and World Wide Web (WWW), more and more companies start the electronic commerce to enhance the business competitiveness. On the other hand, more and more people surf on the Web for information gathering/processing. Due to unbalanced traffic and poorly organized information, users suffer the slow communication and disordered information organization. The information provider can analyze the traffic and uniform resource locator (URL) counters to adjust the organization; however, heterogeneous navigation patterns and dynamic fluctuating Web traffic make the tuning process very complicated. Alternatively the user may be provided with guidance to navigate through the Web pages efficiently. In this paper, a Web site was modeled as a Markov chain associated with the corresponding dynamic traffic and designated information pages. We consider four models: inexperienced surfers on guidance-less sites, experienced surfers on guidance-less sites, sites with the mean-length guidance, and sites with the known-first-arc guidance (generalized as sites with dynamic stochastic shortest path guidance). Simulation is conducted to evaluate the performance of the different types of navigation guidance. We also propose a reformulation policy to highlight the hyperlinks as steering guidance. The evolution on complexity and applicability is also discussed for the design guideline of general improvement methods. The paper concludes with the summary and future directions.published_or_final_versio

Design and evaluation of improvement method on the web information navigation - A stochastic search approach

With the advent of fast growing Internet and World Wide Web (the Web), more and more companies enhance the business competitiveness by conducting electronic commerce. At the same time, more and more people gather or process information by surfing on the Web. However, due to unbalanced Web traffic and poorly organized information, users suffer from slow communication and disordered information. To improve the situation, information providers can analyze the traffic and Uniform Resource Locator (URL) counters to adjust the information layering and organization; nevertheless, heterogeneous navigation patterns and dynamic fluctuating Web traffic complicate the improvement process. Alternatively, improvement can be made by giving direct guidance to the surfers in navigating the Web sites. In this paper, information retrieval on a Web site is modeled as a Markov chain associated with the corresponding dynamic Web traffic and designated information pages. We consider four models of information retrieval based on combination of the level of skill or experience of the surfers as well as the degree of navigation support by the sites. Simulation is conducted to evaluate the performance of the different types of navigation guidance. In addition, we evaluate the four models of information retrieval in terms of complexity and applicability. The paper concludes with a research summary and a direction for future research efforts. © 2009 Elsevier B.V. All rights reserved.postprin

Constructing web views from automated navigation sessions

Existing web search engines provide users with the ability to query an off-line database of indices in order to decide on an entry point for further manual navigation. Results are often presented as a list of URLs in descending order of relevance, with no information on the underlying topology of the result set. We believe that information on the topology is important for useful exploration and can also help to reduce the feeling of disorientation that users experience. We present an alternative to the result set of a conventional search engine, which we call a web probabilistic view -- a weighted subgraph of the underlying document space which maximizes the overall expected relevance of trails. We model a web database as a probabilistic grammar and present several algorithms to calculate its weights, expressed as probabilities attached to transition rules. We provide results from a recent set of experiments, showing the effectiveness of our approach measured as improvement in the expe..