A site map for visualizing both a Web site's structure and keywords

Recommendation algorithms aim at proposing "next" pages to a user based on her current visit and the past users' navigational patterns. In the vast majority of related algorithms, only the usage data are used to produce recommendations, whereas the structural properties of the Web graph are ignored. We claim that taking also into account the Web structure and using link analysis algorithms ameliorates the quality of recommendations. In this paper we present UPR, a novel personalization algorithm which combines usage data and link analysis techniques for ranking and recommending Web pages to the end user. Using the Web site's structure and its usage data we produce personalized navigational graph synopsis (prNG) to be used for applying UPR and produce personalized recommendations. Experimental results show that the accuracy of the recommendations is superior to pure usage-based approaches.

Googling for Health Information

Web personalization is the customization of information or services provided by the Web site according to user needs, through the knowledge of the navigational habits of users and individual interest, combined with the content and structure of Web sites. Objective of Web personalization is to provide information needed by user, without having to ask the user explicitly. In this paper we present analysis and implementation of Web personalization for Web site that sells used cars in Japan. Used cars dealers in Japan mostly sell their cars to other dealers located overseas. Web site is a very effective method to sell because it can be easily accessed by people from all over the world. Since their Web site contains vast amount of cars, Web personalization is expected to facilitate users in finding the desired item. There are a number of aspects and techniques in the development of Web personalization system. The aspects are: the approach of interaction with users, the information used to form the user model, user model renewal time, personalization system architecture, and personalization techniques. Among other Web personalization techniques, we perform analysis for two techniques, namely content-based filtering and collaborative filtering. Based on the analysis of the characteristics of the case (used-cars ecommerce site), content-based filtering is more appropriate than collaborative filtering. The result of Web personalization implementation was tested using k-fold cross validation and variation in the number of training set. Performance accuracy of Web personalization will be calculated using precision and recall, which is commonly applied in information retrieval field. Test with k-fold cross validation produces precision value of 0.322 and the recall of 0.322. Test with variation in the number of training set results that precision and recall values are greater as number of training set increased.

Local and global topics in text modeling of web pages nested in web sites

Many Web information retrieval methods are related to special Web sites, for example, the method based on extracting rules and the one based on training page samples. These methods can do well in a Web site but fail in the others without adding new rules or inputting new training pages manually. Furthermore, if the template of the Web site is changed, it has to redesign the extracting rules or re-inputting the training pages. It is hard to be maintained and used to extract information from large number of different Web sites. In the paper, there is a new method that is based on the keywords of a certain topic, instead of rules and training pages. Experimental evaluation on a large of Web pages from different Web sites indicates that this method correctly and automatically extracts the information ignoring which Web sites the pages come from. This method has been applied to the system of intelligent searching and mining of electronic business successfully.

Reasoning for Web document associations and its applications in site map construction

Web applications are becoming more and more complex and difficult to maintain. To satisfy the customer's demands, they need to be updated often and quickly. In the maintenance phase, Web site understanding is a central activity. In this phase, programmers spend a lot of time and effort in the comprehension of the internal Web site structure. Such activity is often required because the available documentation is not aligned with the implementation, if not missing at all. Reverse engineering techniques have the potential to support Web site understanding, by providing views that show the organization of a site and its navigational structure. However, representing each Web page as a node in a diagram recovered from the source code of the Web site often leads to huge and unreadable graphs. Moreover, since the level of connectivity is typically high, the edges in such graphs make the overall result even less usable. In this paper, we propose an approach to Web site understanding based on clustering of client‐side HTML pages with similar content. This approach works well with content‐oriented sites rather than application‐oriented ones and uses a crawler to download the Web pages of the target Web site. The presence of common keywords is exploited to decide when it is appropriate to group pages together. An experimental work, including 17 Web sites, validates our approach and shows that the clusters produced automatically are close to those that a human would produce for a given Web site. Copyright © 2007 John Wiley & Sons, Ltd.

With the phenomenal growth of World Wide Web and the huge number of web sites with so many web pages, finding relevant information becomes quite difficult for the web users. Web site promoters also need to ensure that their web site is on the top of the search results for better market share. Finding the right combination of keywords and placing them at the appropriate places may help in bringing the web site on the top of search results when a search engine searches the web sites and creates indexes. Over the years web site optimization research has reported encouraging results. Despite promising results, data mining techniques for web sites classification have hardly been applied. An appropriate implementation of classification of web pages may help designing the web pages accordingly. Here in this work data mining using R’s web scraping technique has been used for performing extraction of web pages and also pair of java tools called “website” and “webscrap” were developed to automatically get pages and for further analysis of the downloaded pages. This is the first attempt to analyze medical related nomenclature using.

Comparison of Quality of Internet Pages on Human Papillomavirus Immunization in Italian and in English

Web sites are dynamic in nature with content and structure changing overtime. Many pages on the Web are produced by content management systems (CMSs) such as WordPress, vBulletin, or phpBB. Tools currently used by Web archivists to preserve the content of the Web blindly crawl and store Web pages, disregarding the CMS the site is based on (leading to suboptimal crawling strategies) and whatever structured content is contained in Web pages (resulting in page-level archives whose content is hard to exploit). We present in this paper an application-aware helper (AAH) that fits into an archiving crawl processing chain to perform intelligent and adaptive crawling of Web applications (e.g., the pages served by a CMS). Because the AAH is aware of the Web application currently crawled, it is able to refine the list of URLs to process and to extend the archive with semantic information about extracted content. To deal with possible changes in structure of Web applications, our AAH includes an adaptation module that makes crawling resilient to small changes in the structure of Web site. We show the value of our approach by comparing the output and efficiency of the AAH with respect to regular Web crawlers, also in the presence of structure change.KeywordsDetection PatternExternal LinkContent Management SystemXPath ExpressionNavigation ActionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The large number of Web pages on many Web sites has raised navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users’ navigation in the adaptive Web site.

This paper investigates a structure of commercial Web sites, and then attempts to analyse various patterns that emerge which may be of future use as a guideline to businesses that intend establishing a Web presence. Key to the understanding of these patterns is a clearer grasp of the implications of human interaction with the new medium. The focus is on an experiential construct, namely flow, and how this might vary by Web site, and on using this to begin to unravel the secrets of good commercial Web site design and its implications for business.

providing health information to consumers [1,2]. Even cancer patients, who are not in the typical demographic group of Internet users, often name the Internet as the second most important source for cancer information after health professionals [3,4,5], and people are more satisfied with information they receive from the Web than from other media [6]. The aim of this chapter is to give an overview of best practices for developing and providing consumer health information on the Web and to provide a framework for best practices, quality criteria, and methods for quality assurance and evaluation. Developers and health information providers are faced with “everyday” practical questions such as how to ensure, monitor, and continuously improve the quality of the information they publish. End-users (consumers) are also interested in “quality criteria” and best practices, as they wish to have “markers” (attributes of a Web site or Web page or a health information provider) that can be used to predict the “quality” in order to select “trustworthy” health information.The issue of quality criteria is also important for third-party expert evaluators working for gateways or portals, or other intermediaries such as librarians or healthcare workers putting together lists of “recommended” health Web sites, because they need to specify and apply selection criteria for the sites they endorse. Similarly, organizations that are in the business of Web site certification need to have a checklist of quality criteria to justify their decisions to certify a Web site. Finally, policy makers are interested in the subject of what makes a good (or bad) health Web site, especially in the context of making regulatory and legislative policy decisions. There has been considerable debate and research on the variable quality of health Web sites [7] and how to best evaluate health information Web sites. One reason for the controversy is that “quality” is an elusive concept and implies subjectivity. Quality can be broadly defined as the “totality of characteristics of a product or service that satisfy stated or implied needs of the user” [8,9]. This definition stresses that “quality” is determined by the concordance (or gap) between individual user needs and the actual attributes of the service or product. Perceived quality (or satisfaction) is further confounded by the users’ prior expectations, which also vary individually. In other words, certain aspects of quality seem to be in the eye of the beholder, and can be measured only by the gap between user needs and attributes of the Web site or service [10]. This apparent subjectivity has led to a pessimistic view that quality of Web sites cannot be measured or evaluated, at least not by third parties [11]. The fact that we are talking about “health information” makes the issue even more problematic, as in medicine there are often “gray” areas with no clear black-or-white 4 Design and Evaluation of Consumer Health Information Web Sites

This study investigates the effects of users' visualization ability and Web site structure display design on users' performance and memory organization in Web site information search tasks using a browsing strategy. A human-centered design-structure preview-was proposed in this study. Structure preview is a Web site navigation menu in which each menu item serves as a link to one Web page, similar to a menu design in Microsoft Windows 95 and Windows 98. An experiment was conducted in which 40 individuals participated. The experimental design was a 2-factor factorial design. Independent variables were visualization ability (low and high) and Web site design (conventional and structure preview). Twenty participants were identified as users with low visualization ability and 20 participants were identified as users with high visualization ability. Dependent variables were the number of identified items, the number of steps per item, and memory organization. Results indicated that both low- and high-visualization users' performance improved significantly (76.3% more identified items and 83.4% fewer steps per item for low-visualization users; 36.5% more identified items and 78.4% fewer steps per item for high-visualization users) when using the structure preview design than when using the conventional design. When using the conventional design, high-visualization users had significantly better performance (36.9% more identified items and 23.6% fewer steps per item) than low-visualization users. Also, the memory organization of all users (including both low- and high-visualization users) improved significantly (42.9%) when using the structure preview design compared with the conventional design.

Over the last decade, we have witnessed an explosive growth in the information available on the Web. Today, Web browsers provide easy access to myriad sources of text and multimedia data. Search engines index more than a billion pages and finding the desired information is not an easy task. This profusion of resources has prompted the need for developing automatic mining techniques on Web, thereby giving rise to the term “Web mining” (Pal, Talwar, & Mitra, 2002). Web mining is the application of data mining techniques on the Web for discovering useful patterns and can be divided into three basic categories: Web content mining, Web structure mining, and Web usage mining. Web content mining includes techniques for assisting users in locating Web documents (i.e., pages) that meet certain criteria, while Web structure mining relates to discovering information based on the Web site structure data (the data depicting the Web site map). Web usage mining focuses on analyzing Web access logs and other sources of information regarding user interactions within the Web site in order to capture, understand and model their behavioral patterns and profiles and thereby improve their experience with the Web site. As citizens requirements and needs change continuously, traditional information searching, and fulfillment of various tasks result to the loss of valuable time spent in identifying the responsible actor (public authority) and waiting in queues. At the same time, the percentage of users who acquaint with the Internet has been remarkably increased (Internet World Stats, 2005). These two facts motivate many governmental organizations to proceed with the provision of e-services via their Web sites. The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth and popularity of e-government, e-commerce, and e-business applications. In this framework, the Web is emerging as the appropriate environment for business transactions and user-organization interactions. However, since it is a large collection of semi-structured and structured information sources, Web users often suffer from information overload. Personalization is considered as a popular solution in order to alleviate this problem and to customize the Web environment to users (Eirinaki & Vazirgiannis, 2003). Web personalization can be described, as any action that makes the Web experience of a user personalized to his or her needs and wishes. Principal elements of Web personalization include modeling of Web objects (pages) and subjects (users), categorization of objects and subjects, matching between and across objects and/or subjects, and determination of the set of actions to be recommended for personalization. In the remainder of this article, we present the way an e-government application can deploy Web mining techniques in order to support intelligent and personalized interactions with citizens. Specifically, we describe the tasks that typically comprise this process, illustrate the future trends, and discuss the open issues in the field.