Web Site Reorganization Based on Topology and Usage Patterns

Googling for Health Information

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

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.

With the exponentially growing amount of information available on the Internet, an effective technique for users to discern the useful information from the unnecessary information is urgently required. Cleaning web pages for web data extraction becomes critical for improving performance of information retrieval and information extraction. So, we investigate to remove various noise patterns in Web pages instead of extracting relevant content from Web pages to get main content information. In this paper, we propose an approach that detect multiple noise patterns and remove these noise patterns from Web pages of any Web sites. The method first build DOM tree for any Web page. Our approach is based on the basic idea of Case-Based Reasoning (CBR) to find noise pattern in current Web page by matching similar noise pattern kept in Case-Based. We also apply a back propagation neural network algorithm to classify the stored various noise patterns by matching similar noise data in current Web page. We have implemented our method on several commercial Web sites and News Web sites to evaluate the performance and improvement of our approach. Experiments show that results leads to a more accurate and effectiveness of the approach.

With the maturity of network technology, the deterministic factor of a 'successful' web site does not as much depend on its connectivity to the Internet, rather the content of web pages plays a more important role. The inclusion of dynamic data, for example, has become an increasingly desirable feature of a web page. Web servers that support dynamic web pages are capable of retrieving data at the time of user requests. Rather than being statically included in the web page, these dynamically retrieved data may physically reside in various file systems or database servers across the Internet.JAVA, a new object-oriented programming language, has become a buzzword since its introduction by Sun Microsystems in 1994 [1, 2, 3]. It was claimed that JAVA, via its ability to embed applets in a web page, would make the content of a web page alive and dynamic. Data and information on a web page can now be updated dynamically when users request them.In this paper, we discuss our experience of developing JAVA applets that use various types of JDBC (JAVA Database Connectivity) drivers to connect to and then manipulate data stored in SQL (Structured Query Language) database servers. We first start with the discussion of general client/server model involving JDBC, and then introducing the procedure of setting up programming projects employing this approach in an undergraduate database course.

At present, there are many security risks from the network, so it has practical significance for students in the university to learn the knowledge about Web pages and website security performance and have Web pages and web site security performance detection capability. It is described that the recent organization of a number of students to carry out a Web page and Web site security performance experiments. In experiments students’ security awareness on the Web page and website are trained through the use of security vulnerability detection tools and enable students to have basic security performance testing capabilities of web page and website

Social book marking Web sites have emerged recently for collecting and sharing of interesting Web sites among users. People can add Web pages to such sites as bookmarks and allow themselves as well as others to manipulate them. One of the key features of the social book marking sites is the ability of annotating a Web page when it is being bookmarked. The annotation usually contains a set of words or phrases, which are collectively known as tags, that could reveal the semantics of the annotated Web page. Efficient and effective search of Web pages can then be achieved via such tags. However, spam tags that are irrelevant to the content of Web pages often appear to deceive other users for malicious or commercial purposes. Various techniques have been devised to tackle such tag spam detection problem. Most of these techniques were able to detect a user that always annotate spam tags. However, finer levels of detection are seldom discussed. In this work, we will propose a method based on a text mining approach to discover the relations between Web pages and there tag posts. These relations are then used to compute the similarity between a Web page and its tag post to decide if it is a spam post. Preliminary experiments show that the accuracy of the post-level spam detection task is 83%.

The aim of this study was to assess the changes in the characteristics of rheumatoid arthritis information on the Internet over a 15-year period and the positioning of Web sites posted by universities, hospitals, and medical associations. We replicated the methods of a 2001 study assessing rheumatoid arthritis information on the Internet using WebCrawler. All Web sites and pages were critically assessed for relevance, scope, authorship, type of publication, and financial objectives. Differences between studies were considered significant if 95% confidence intervals did not overlap. Additionally, we added a Google search with assessments of the quality of content of web pages and of the Web sites posted by medical institutions. There were significant differences between the present study's WebCrawler search and the 2001-referent study. There were increases in information sites (82 vs 36%) and rheumatoid arthritis-specific discussion pages (59 vs 8%), and decreases in advertisements (2 vs 48%) and alternative therapies (27 vs 45%). The quality of content of web pages is still dispersed; just 37% were rated as good. Among the first 300 hits, 30 (10%) were posted by medical institutions, 17 of them in the USA. Regarding readability, 7% of these 30 web pages required 6years, 27% required 7-9years, 27% required 10-12years, and 40% required 12 or more years of schooling. The Internet has evolved in the last 15years. Medical institutions are also better positioned. However, there are still areas for improvement, such as the quality of the content, leadership of medical institutions, and readability of information.

A home page is the gateway to an organization's Web site. To design effective Web home pages, it is necessary to understand the fundamental drivers of user's perception of Web pages. Not only do designers have to understand potential users' frame of mind, they also have at their choosing a stupefying array of attributes – including numerous font types, audio, video, and graphics – all of which can be arranged on a page in different ways, compounding the complexity of the design task. A theoretical model capable of explaining user reactions at a molar level should be invaluable to Web designers as a complement to prevalent intuitive and heuristic approaches. Such a model transcends piecemeal page attributes to focus on overall Web page perceptions of users. Reasoning that people perceive the cyberspace of Web pages in ways similar to their perception of physical places, we use Kaplan and Kaplan's informational model of place perception from the field of environmental psychology to predict that only two dimensions: understanding of information on a Web page, and the involvement potential of a Web page, should adequately capture Web page perception at a molar level. We empirically verify the existence of these dimensions and develop valid scales for measuring them. Using a home page as a stimulus in a lab experiment, we find that understanding and involvement together account for a significant amount of the variance in the attitude toward the Web page and in the intention to browse the underlying Web site. We show that the informational model is a parsimonious and powerful theoretical framework to measure users' perceptions of Web home pages and it could potentially serve as a guide to Web page design and testing efforts.

CHAPTER 1 - Cross-Site Scripting

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

Web recommendation systems are helpful in overcoming the excess information on web by retrieving the information required by the user with respect to user's or similar users' preferences and interests. In order to make web recommendation system work, web users have to be clustered based on their common interest. The web user clusters are used to obtain the knowledge about the web pages accessed. This knowledge can be used for prefetching of web pages, finding web pages that are frequently accessed together, etc. This paper presents a modification in the original CA clustering algorithm for grouping of web users with respect to access pattern of web pages. The original CA algorithm uses the basic “Fuzzy C Means (FCM) algorithm” to compute the membership matrix. The modified CA algorithm uses a superior FCM algorithm, namely, the Density Weighted FCM (DWFCM) instead of the basic FCM. Experiments are conducted on the datasets obtained from the UCI repository. It is found that the modified CA clustering method exhibits superior capability of clustering when compared to the CA clustering method.

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

We develop a novel framework that aims at automatically adapting previously learned information extraction knowledge from a source Web site to a new unseen target site in the same domain. Two kinds of features related to the text fragments from the Web documents are investigated. The first type of feature is called, a site-invariant feature. These features likely remain unchanged in Web pages from different sites in the same domain. The second type of feature is called a site-dependent feature. These features are different in the Web pages collected from different Web sites, while they are similar in the Web pages originating from the same site. In our framework, we derive the site-invariant features from previously learned extraction knowledge and the items previously collected or extracted from the source Web site. The derived site-invariant features will be exploited to automatically seek a new set of training examples in the new unseen target site. Both the site-dependent features and the site-invariant features of these automatically discovered training examples will be considered in the learning of new information extraction knowledge for the target site. We conducted extensive experiments on a set of real-world Web sites collected from three different domains to demonstrate the performance of our framework. For example, by just providing training examples from one online book catalog Web site, our approach can automatically extract information from ten different book catalog sites achieving an average precision and recall of 71.9% and 84.0% respectively without any further manual intervention.

How Well Do Firms Implement Strategy When They Design Internet Web Pages?