Web Page Content Research Articles

Webometric Ranking of European Universities

In year 2004 Aguillo and colleagues launched the Webometrics Ranking of World's Universities (www.webometrics.info), the ranking of universities by their presence on the Internet with the aim of promoting and enriching the content of university web pages. This paper presents research which gathered data for 12.000 universities using Aguillo's methodology. Data analysis revealed shortcomings in the implementation of the algorithm used by Aguillo et al. for ranking of world universities, which negatively influenced ranking of 768 world universities (6.4% of universities represented in ranking). Shortcomings in implementation will be demonstrated on example of University of Zagreb. It will be presented that by correct application of the algorithm, ranking of affected universities extremely improves, which changes overall ranking of other universities.

Web data mining: exploring hyperlinks, contents, and usage data

Web mining aims to discover useful information and knowledge from Web hyperlinks, page contents, and usage data. Although Web mining uses many conventional data mining techniques, it is not purely an application of traditional data mining due to the semi-structured and unstructured nature of the Web data. The field has also developed many of its own algorithms and techniques. Liu has written a comprehensive text on Web mining, which consists of two parts. The first part covers the data mining and machine learning foundations, where all the essential concepts and algorithms of data mining and machine learning are presented. The second part covers the key topics of Web mining, where Web crawling, search, social network analysis, structured data extraction, information integration, opinion mining and sentiment analysis, Web usage mining, query log mining, computational advertising, and recommender systems are all treated both in breadth and in depth. His book thus brings all the related concepts and algorithms together to form an authoritative and coherent text.The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in Web mining and data mining both as a learning text and as a reference book. Professors can readily use it for classes on data mining, Web mining, and text mining. Additional teaching materials such as lecture slides, datasets, and implemented algorithms are available online.

Vocabulary Expansion Technique for Advertisement Classification

Contextual advertising is an important revenue source for major service providers on the Web. Ads classification is one of main tasks in contextual advertising, and it is used to retrieve semantically relevant ads with respect to the content of web pages. However, it is difficult for traditional text classification methods to achieve satisfactory performance in ads classification due to scarce term features in ads. In this paper, we propose a novel ads classification method that handles the lack of term features for classifying ads with short text. The proposed method utilizes a vocabulary expansion technique using semantic associations among terms learned from large-scale search query logs. The evaluation results show that our methodology achieves 4.0% ~ 9.7% improvements in terms of the hierarchical f-measure over the baseline classifiers without vocabulary expansion.

GIS Day and Web Promotion: Retrospective Analysis of U.S. ARL Libraries' Involvement

Given the increasing demand for GIS services and collections in libraries, librarians should use every outreach tool available to reach potential audiences. An annual event, GIS Day has a robust and established range of supporting tools that are easily customized for local use. Effective marketing, including visibility and longevity of Web pages, is an effective tool for increasing awareness of GIS services. This study analyzes content of Web pages to evaluate the levels of participation and promotion of GIS through GIS Day at U.S.-based Association of Research Libraries academic libraries and their host universities. Results indicate a range of involvement, with some libraries participating in numerous events while others are not taking full advantage of this valuable outreach opportunity.

A Personalized Product Based Recommendation System Using Web Usage Mining and Semantic Web

To be globally competent and competitive a successful presence on the web is necessary to sustain and retain itself in the market. The WWW is an interesting area for data mining because of abundance of information. Web users exhibit a variety of navigational interests through clicking a sequence of web pages. Analysis of this data will lead to discover many interesting patterns and facilitate users to locate more preferable web pages. Advanced mining processes are needed for this knowledge to be extracted, understood and used. Web Usage Mining (WUM) systems are specifically designed to carry out this task by analyzing the data representing usage data about a particular Web Site. The semantic information of the Web page contents is generally not included in Web usage mining. Online recommendation and prediction is one of the web usage mining applications. In this paper we present architecture for integrating semantic information about the products with web log data and generate a list of recommended products by using LCS Algorithm.

Geotracking of webpage sources: a defence against drive-by-download attacks

Currently, numerous freeware URL screening tools are available online. While these tools exhibit various levels of sophistication in dealing with traditional web-based exploits, most of them are quite ineffective in detecting some more subtle forms of infection. In particular, most of these tools omit to detect and/or alert against drive-by-download injections that do not result in the download and/or execution of a malware, but instead only aim to tarnish the credibility of the compromised website or intrude on the privacy of its users. In this paper, we present our new visual location-based URL screening tool, named VLUS. We demonstrate that with this tool, various forms of drive-by-download injection leading to redirection can be easily spotted, irrespective of the nature of the injected content. The tool is also useful for the purposes of general webpage content analysis. We close the paper by outlining an alternative implementation of VLUS in the form of a browser Chrome extension. By a simple monitoring of the application-level traffic calls performed by the browser, this implementation offers several unique advantages over the standard VLUS implementation.

Korean and Chinese Webpage Content: Who Are Talking About What and How?

This paper examines how China and Korea communicate through the Internet. LexiURL Searcher was used to retrieve data from Yahoo!, and select 800 random webpages to examine their authorship, subject topic, and website format. The results indicate some similarities and differences between Chinese and Korean webpages. Most of the webpages were owned by firms, and their content fell into 3 categories: “related links,”“education, scholarship, and research,” and “business, economy, finance, and industry.” However, there is an important difference in the webpage format between Korean and Chinese pages: Korean webpages were more interactive than Chinese ones. This difference may be due in part to differences in the organizational culture between the 2 countries. Other potential causes are discussed in detail. © 2012 Wiley Periodicals, Inc.

Query Sensitive Comparative Summarization of Search Results Using Concept Based Segmentation

Query sensitive summarization aims at providing the users with the summary of the contents of single or multiple web pages based on the search query. This paper proposes a novel idea of generating a comparative summary from a set of URLs from the search result. User selects a set of web page links from the search result produced by search engine. Comparative summary of these selected web sites is generated. This method makes use of HTML DOM tree structure of these web pages. HTML documents are segmented into set of concept blocks. Sentence score of each concept block is computed with respect to the query and feature keywords. The important sentences from the concept blocks of different web pages are extracted to compose the comparative summary on the fly. This system reduces the time and effort required for the user to browse various web sites to compare the information. The comparative summary of the contents would help the users in quick decision making.

From Learning Style of Webpage Content to Learner's Learning Style

Technology plays an important role in the development of students who can search for the concepts which they learn in the books on the Internet and find out more information on them. This will increase the depth of their knowledge. According to some researches, students tend to be more active and more participative when technology is being integrated in their lesson resulting to better comprehension and good performance. Using technology in the learning process can facilities automatic detection of the learner’s learning styles which can help the learner to develop his coping strategies to compensate for his/her weaknesses, capitalize on his/her strengths, improve the quality of the learning process and make it more effective. This research presents an automatic tool for detecting learning styles in a learning environment by analyzing the content of the learner’s favorite WebPages using social bookmarking services(www.tagme1.com) and shows that how actual behavior of the learners during the learning process can be used as an effective source for detecting their learning styles based on Felder-Silverman learning style model (FSLSM) .

A Review of the Content and Format of Transgender-Related Webpages

Transgender persons represent a highly diverse group of individuals who have been historically underserved, despite being disproportionately at risk for HIV (human immunodeficiency virus) and other health conditions. Despite the need for more research on transgender health issues, no review of online transgender-related resources has been conducted. The purpose of this study was to broadly characterize (1) the types of transgender-related webpages that appear as a result of keyword searches, and (2) the extent to which webpages differ in content and format depending on whether the intended audience for the webpage was transgender individuals, health professionals, or the general population. An online search using 28 keywords yielded 204 eligible webpages, of which 58% targeted transgendered individuals, 23% targeted health professionals, and 39% targeted the general public. The highest percentage of webpages appeared to be operated and/or created by transgender individuals or groups (46%), followed by for-profit businesses (17%). The majority of mental health (80%), HIV-related (89%), and primary care (100%) webpages targeted health professionals. Although various features are available that may increase user interest in and perceived credibility of a webpage, the results show that many of these features were underutilized. There appears to be significant opportunity to develop web resources that directly target unique subgroups within the transgender community to improve their health outcomes, increase the visibility of features that increase user interest and perceived credibility of webpages, and possibly train transgender individuals to seek relevant online information.

An Analysis of Children's Web Pages in Public Library Web Sites in Japan

A progenitor article for this work can be found in Public Library Quarterly 27, no. 4. This study is the first to report on the types of contents in children's web pages and the characteristics of Web-OPACs for children in public library websites in Japan. This study reveals that children's web pages, in general, place more emphasis on providing guidance on library services and on the use of information resources for reference services, rather than on helping children with regular learning or providing research assistance to adults on children's services. Other findings are reported as well.

A Novel Web Metric for the Evaluation of Internet Trends

Abstract — Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend. Keywords — Blog, Sentiment Analysis, Web 2.0, Webometrics I. I NTRODUCTION EB 2.0 (social networking, blogging and online forums) creates vast amount of comments on various topics from many different users. Thanks to that, Web 2.0 can serve as a data source for social science research [1]. According to Internet World Statistics [2], approximately 60% of the population in Europe and over 70% of the populations in North America are currently internet users. The number of Internet users has been constantly growing and Web 2.0 has been becoming a popular tool for finding information [3], [4]. Nevertheless, the volume of information on the web has been growing at a very high rate and becoming a network of heterogeneous data, this makes thing difficult to find and is therefore not almost useful. It is necessary to design suitable metric for such volume of information, which would reflect the semantic content of pages in the better way. One of the options for more accurate comprehension of semantic information is to use a sophisticated analysis of sentences called Sentiment Analysis [5]. The knowledge gained will be useful for algorithm design to facilitate user access to the information on the web, and also to obtain the public opinion on specific issues. II. R

From the Field and Into the Classroom

Although it is difficult these days to find a company that does not have a website, you do not have to look very far for to find a website with significant design and architecture flaws. Getting a visitor to your website is one thing, making the experience effortless and allowing them to find exactly what they need is another story. That being said, understanding how the consumer comprehends and navigates webpage content is an important part of the interactive marketing process that demands extra attention. Although this field is well established among marketing research practitioners, information architecture assessment and website usability tests are user-centric methods of website analysis that receive little attention from marketing academics. This article discusses the importance of user-centric methods of website analysis for the field of direct and interactive marketing and outlines strategies for implementing qualitative research techniques in an educational context. Classroom exercises and take-home assignments for an undergraduate curriculum are provided and discussed.

Knowledge Representation and Management: Benefits and Challenges of the Semantic Web for the Fields of KRM and NLP

To summarize excellent current research in the field of knowledge representation and management (KRM). A synopsis of the articles selected for the IMIA Yearbook 2011 is provided and an attempt to highlight the current trends in the field is sketched. This last decade, with the extension of the text-based web towards a semantic-structured web, NLP techniques have experienced a renewed interest in knowledge extraction. This trend is corroborated through the five papers selected for the KRM section of the Yearbook 2011. They all depict outstanding studies that exploit NLP technologies whenever possible in order to accurately extract meaningful information from various biomedical textual sources. Bringing semantic structure to the meaningful content of textual web pages affords the user with cooperative sharing and intelligent finding of electronic data. As exemplified by the best paper selection, more and more advanced biomedical applications aim at exploiting the meaningful richness of free-text documents in order to generate semantic metadata and recently to learn and populate domain ontologies. These later are becoming a key piece as they allow portraying the semantics of the Semantic Web content. Maintaining their consistency with documents and semantic annotations that refer to them is a crucial challenge of the Semantic Web for the coming years.

Institutional Capacity to Dynamically Innovate: An Application to the Portuguese Case

The present paper addresses the dynamics of innovation, by extending the analysis beyond a static - economic perspective. It offers a dynamic - institutional mapping of relational capacities to dynamically innovate. Its main goal is to contribute to the above-mentioned research theme by presenting a new methodology able to pinpoint different trends in the relational capacities of institutions when they are innovative. Thereby, major characteristics in the networks of innovation are identified. This investigation uses an extended set of private institutions and public organizations located in Portugal, evaluated by their Web Page contents. To this data set a new combination of multivariate statistical methods is applied to detect group performances, to compare them, and to identify gradients of capacity to dynamically innovate. The results demonstrate that this method can provide extremely useful and tailor-made information for policy evaluation at regional or national levels.

Attacking Anonymous Web Browsing at Local Area Networks Through Browsing Dynamics

The majority of current anonymous systems focus on improving anonymity at the network and website level in order to defend against traffic analysis attacks. However, the vulnerability of the connections between end users and the anonymous network do not attract any attention yet. For the first time, we reveal an end user browsing dynamics based attack on anonymous browsing systems at the LAN where the victim locates. This new attack method is fundamentally different from existing attack methodologies. In general, web surfers browse the web following certain patterns, such as requesting a web page, viewing it and requesting another page. The browsing pattern of a victim can be clearly observed by a local adversary when the victim is viewing the web without protection. Unfortunately, browsing dynamics releases rich information for attacking even though the web page content is encrypted. In order to show how a local eavesdropper can decipher which pages have been viewed with the knowledge of user browsing dynamics and the public information of a given website, we established a specific hidden Markov model to represent browsing dynamics for the website. By using this model, we can then identify the optimal of the accessed pages using the Viterbi algorithm. In order to confirm the effectiveness of the revealed attack method, we have conducted extensive experiments on a real data set. The results demonstrated that the attack accuracy can be more than 80%. A few possible counter-attack strategies are discussed at the end of the paper.

Web Content Adaptation System

In this paper we present a Web Content Adaptation System for mobile devices. The system enables the presentation of Web content by considering the problem of small screen display of mobile computing devices, also independent-device access to web content is considered. The focus has mainly been on the adaptation of HTML web page content to make it viewable on mobile devices, constraint that no server-side content adjustments are assumed. The adaptation is done by using the re-authoring technique started by parsing the HTML web page and converting it to tree structure. This conversion will separate presentation from content which will be more efficient in dealing with content, then converting to XML document that is a well structured document. The result is a device independent user interface that could be shown on any device. The output shows TOC that consists of list of hyperlinks, each either the header of the web page or a title of a paragraph or using the first sentence elision as hyperlink and a link to image that will be resized to fit on mobile screen.

A Machine Learning Based Analytical Framework for Semantic Annotation Requirements

The Semantic Web is an extension of the current web in which information is given well-defined meaning. The perspective of Semantic Web is to promote the quality and intelligence of the current web by changing its contents into machine understandable form. Therefore, semantic level information is one of the cornerstones of the Semantic Web. The process of adding semantic metadata to web resources is called Semantic Annotation. There are many obstacles against the Semantic Annotation, such as multilinguality, scalability, and issues which are related to diversity and inconsistency in content of different web pages. Due to the wide range of domains and the dynamic environments that the Semantic Annotation systems must be performed on, the problem of automating annotation process is one of the significant challenges in this domain. To overcome this problem, different machine learning approaches such as supervised learning, unsupervised learning and more recent ones like, semi-supervised learning and active learning have been utilized. In this paper we present an inclusive layered classification of Semantic Annotation challenges and discuss the most important issues in this field. Also, we review and analyze machine learning applications for solving semantic annotation problems. For this goal, the article tries to closely study and categorize related researches for better understanding and to reach a framework that can map machine learning techniques into the Semantic Annotation challenges and requirements.

Continuous time Markov chain based website navigability measure

Website navigability is acquiring a growing importance in website design and redesign, quality evaluation, and improvement. Existing navigability measures mainly depend on site link structure, so that they only consider the impact of site link structure for navigability and ignore the impact of Web page content. A continuous Markov chain model which depicts the user's surfing behavior can balance these two factors in the evaluation of website navigability, and it needs to estimate the page transition probabilities and user stay time according to user access log. In this way, we can obtain more reliable results for website navigability measure than the existed methods. Experiments show that our method is effective.

Extending Object-Oriented Network Protocols via alternative Transportation Bindings (Web Services over XMPP)

Distributed and/or composite web applications are driven by intercommunication via web services, which employ application-level protocols, such as SOAP. However, these protocols usually rely on the classic HTTP for transportation. HTTP is quite efficient for what it does — delivering web page content, but has never been intended to carry complex web service oriented communication. Today there exist modern protocols that are much better fit for the job. Such a candidate is XMPP. It is an XML-based, asynchronous, open protocol that has built-in security and authentication mechanisms and utilizes a network of federated servers. Sophisticated asynchronous multi-party communication patterns can be established, effectively aiding web service developers. This paper’s purpose is to prove by facts, comparisons, and practical examples that XMPP is not only better suited than HTTP to serve as middleware for web service protocols, but can also contribute to the overall development state of web services.