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Focussed crawlers enable the automatic discovery of Web resources about a given topic by automatically navigating the Web link structure and selecting the hyperlinks to follow by estimating their relevance to the topic based on evidence obtained from the already downloaded pages. This work proposes a classifier-guided focussed crawling approach that estimates the relevance of a hyperlink to an unvisited Web resource based on the combination of textual evidence representing its local context, namely the textual content appearing in its vicinity in the parent page, with visual evidence associated with its global context, namely the presence of images relevant to the topic within the parent page. The proposed focussed crawling approach is applied towards the discovery of environmental Web resources that provide air quality measurements and forecasts, since such measurements (and particularly the forecasts) are not only provided in textual form, but are also commonly encoded as multimedia, mainly in the form of heatmaps. Our evaluation experiments indicate the effectiveness of incorporating visual evidence in the link selection process applied by the focussed crawler over the use of textual features alone, particularly in conjunction with hyperlink exploration strategies that allow for the discovery of highly relevant pages that lie behind apparently irrelevant ones. [ABSTRACT FROM AUTHOR]

Web mining is an emerging research area due to the rapid growth of websites. Web mining is classified into Web Content Mining (WCM), Web Usage Mining and Web Structure Mining. Extraction of required information from web page content available on World Wide Web (WWW) is WCM. The WCM is further classified into two categories first category is to directly mine the content on documents and second category is to mine the content using search engine. The mining method focuses on the information extraction and integration. The content of Web may be text, image, audio, video. Web pages typically contain a large amount of information that is not part of the main contents of the pages, like banner advertisements, navigation bars, copyright notices, etc. Such noises on Web pages usually lead to poor results in Web mining. This paper focuses on the problem of Noise free Information retrieval on web pages, which means the pre-processing of Web pages automatically to detect and eliminate noises. This paper proposes an approach for eliminating noises from web pages for the purpose of improving the accuracy and efficiency of web content mining. The main objective of removing noise from a Web Page is to improve the performance of the search. It is very essential to differentiate important information from noisy content that may misguide users' interest. This approach mainly concentrates on removing the following noises in stages: (1) Primary noises-Navigation bars, Panels and Frames, Page Headers and Footers, Copyright and Privacy Notices, Advertisements and other Uninteresting Data such as audio, video, multiple links. (2) Duplicate Contents and (3) Noise Contents according to block importance. The removal of these noises is done by performing three operations. Firstly, using the Block Splitting operation, primary noises are removed and only the useful text contents are partitioned into blocks. Secondly, using simhash algorithm, the duplicate blocks are removed to obtain the distinct blocks. For each block, three parameters namely Keyword Redundancy (KR), Linkword Percentage (LP) and Titleword Relevancy (TR) calculated. Using these three parameters block importance value (BI) is calculated, which is called Simhash algorithm. The importance of the block is then calculated using simhash algorithm. Based on a threshold value the important blocks are selected using sketching algorithm and the keywords are extracted from those important blocks. [ABSTRACT FROM AUTHOR]

Despite being criticized as unrepresentative and misleading, retention and graduation rates are an important part of college-search web sites and accountability systems, and they frequently have been used as indicators of institutional quality and effectiveness in educational research. Retention and graduation rates are often compared over time and across institutions. However, such comparisons can be confounded by differences in entering student cohorts and differences among the institutions being compared. This research examined the effects of institutional and cohort characteristics on one-year retention rates using random-effect and fixed-effect regression models for panel data. The use of a fixed-effect model allowed the researchers to account for omitted variables (unobserved heterogeneity) in the analyses. Results indicated that unobserved heterogeneity was a significant issue in the study, and that traditional regression methods may overstate the effects of institutional characteristics on retention rates. Results also indicated that the effects of institutional and cohort characteristics were essentially stable over time and across cohorts. [ABSTRACT FROM AUTHOR]

Psychological researchers have begun to utilize Amazon's Mechanical Turk (MTurk) marketplace as a participant pool. Although past work has established that MTurk is well suited to examining individual behavior, pseudo-dyadic interactions, in which participants falsely believe they are interacting with a partner, are a key element of social and cognitive psychology. The ability to conduct such interdependent research on MTurk would increase the utility of this online population for a broad range of psychologists. The present research therefore attempts to qualitatively replicate well-established pseudo-dyadic tasks on MTurk in order to establish the utility of this platform as a tool for researchers. We find that participants do behave as if a partner is real, even when doing so incurs a financial cost, and that they are sensitive to subtle information about the partner in a minimal-groups paradigm, supporting the use of MTurk for pseudo-dyadic research. [ABSTRACT FROM AUTHOR]

This paper is concerned with a framework to compute the importance of webpages by using real browsing behaviors of Web users. In contrast, many previous approaches like PageRank compute page importance through the use of the hyperlink graph of the Web. Recently, people have realized that the hyperlink graph is incomplete and inaccurate as a data source for determining page importance, and proposed using the real behaviors of Web users instead. In this paper, we propose a formal framework to compute page importance from user behavior data (which covers some previous works as special cases). First, we use a stochastic process to model the browsing behaviors of Web users. According to the analysis on hundreds of millions of real records of user behaviors, we justify that the process is actually a continuous-time time-homogeneous Markov process, and its stationary probability distribution can be used as the measure of page importance. Second, we propose a number of ways to estimate parameters of the stochastic process from real data, which result in a group of algorithms for page importance computation (all referred to as BrowseRank). Our experimental results have shown that the proposed algorithms can outperform the baseline methods such as PageRank and TrustRank in several tasks, demonstrating the advantage of using our proposed framework. [ABSTRACT FROM AUTHOR]

The web provides an unprecedented opportunity to evaluate ideas quickly using controlled experiments, also called randomized experiments, A/B tests (and their generalizations), split tests, Control/Treatment tests, MultiVariable Tests (MVT) and parallel flights. Controlled experiments embody the best scientific design for establishing a causal relationship between changes and their influence on user-observable behavior. We provide a practical guide to conducting online experiments, where end-users can help guide the development of features. Our experience indicates that significant learning and return-on-investment (ROI) are seen when development teams listen to their customers, not to the Highest Paid Person’s Opinion (HiPPO). We provide several examples of controlled experiments with surprising results. We review the important ingredients of running controlled experiments, and discuss their limitations (both technical and organizational). We focus on several areas that are critical to experimentation, including statistical power, sample size, and techniques for variance reduction. We describe common architectures for experimentation systems and analyze their advantages and disadvantages. We evaluate randomization and hashing techniques, which we show are not as simple in practice as is often assumed. Controlled experiments typically generate large amounts of data, which can be analyzed using data mining techniques to gain deeper understanding of the factors influencing the outcome of interest, leading to new hypotheses and creating a virtuous cycle of improvements. Organizations that embrace controlled experiments with clear evaluation criteria can evolve their systems with automated optimizations and real-time analyses. Based on our extensive practical experience with multiple systems and organizations, we share key lessons that will help practitioners in running trustworthy controlled experiments. [ABSTRACT FROM AUTHOR]

Websites for colleges and universities have become the primary means for students to obtain information in the college search process. Consequently, institutions of higher education should target their websites toward prospective and current students’ needs, interests, and tastes. Numerous parameters must be determined in creating a school website (e.g. number of links, page size, use of graphics, utilization of dynamic elements, and menuing options). This research details a decision support framework based upon Kohonen self-organizing feature maps to determine students’ specific preferences for school websites. This research attempts to remove some of the subjectivity in designing a school website by finding the commonalities among websites that students find appealing and effective. Self-organizing feature maps are employed as a clustering method to compare the school’s current website to other sites that students find both appealing and effective. [ABSTRACT FROM AUTHOR]

The article presents news briefs pertaining to the field of environmental geology. A summer school program was established in Svalbard, Norway to allow students to observe changes in sea ice facilitated by climatic changes. The American Geological Institute's Environmental Geoscience Program disseminates news on its findings via the Web site www.agiweb.org/environment/index.html. Google is extending funds to geothermal energy projects in an attempt to generate 1 gigawatt of renewable power.

The article discusses the dangers of blindly believing information found on the Internet. The author mentions a website found on a blog at the Washington Post online dealing with Burmese Mountain Dogs, which he discovered to be fake. He also discusses a website for the Coalition to Ban DHMO, which he explains is the chemical name for water, which contains accurate information despite looking unauthentic. The importance of educators showing students examples of both good and bad websites so that they can learn to tell the difference between the two is stressed.

Aims and objectives To investigate the quality and content of dental practice websites by constructing an audit framework based on regulations, guidance and expert advice, and applying this framework to a random sample of UK dental practices' websites.Methods An audit framework was constructed and in-depth data collected from a random sample of 150 UK dental practices.Results Thirty-five percent of dental practices in this study were found to have websites. Compliance with rules and regulations regarding dental practice websites was generally poor. Use of advised content for practice promotion was variable. Many websites were poorly optimised. Eighty-nine percent of the websites advertised tooth whitening, despite the issues surrounding its legality; 25% of the websites advertised Botox even though advertising of prescription only medicines is illegal. Some websites gave misleading information about the specialist status of their dentists.Conclusions Those responsible for dental practice websites need to be aware of a wide range of regulations and guidance, and are advised to follow expert advice on content and optimisation in order to maximise the potential of their websites. [ABSTRACT FROM AUTHOR]