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A web page (or webpage) is a hypertext document on the World Wide Web. Web pages are delivered by a web server to the user and displayed in a web browser. A website consists of many web pages linked together under a common domain name. The name "web page" is a metaphor of paper pages bound together into a book. A web page is a structured document. The core element of a web page is a written in the HyperText Markup Language (HTML) which specifies the content of the web page (including links (called hyperlinks) to other web resources, primarily other web pages, and to different sections of the same web page). Multimedia content on the web, such as s, videos, and other web pages, can be directly embedded in a web page to form a compound document. An HTML document can include separate files called Cascading Style Sheets (CSS) documents (which are also text files) which specify the presentation of content on a web page. (This is in principle an alternative to including that information directly in the HTML code.) The document can also include JavaScript or WebAssembly programs, which are executed by the web browser to add dynamic behavior to the web page: for example, a form which accepts input from the user. Web pages with dynamic behavior can function as application software, referred to as web applications. Web navigation Each web page is identified by a distinct Uniform Resource Locator (URL). When the user inputs the URL for a web page into their browser, the browser downloads an HTML file from a web server and transforms all of its elements into an interactive visual representation on the user's device. If the user clicks, taps, or otherwise activates a hyperlink, the browser repeats this process to load the page pointed to by the hyperlink, which could be part of the current website or a different one. The browser has user interface features that indicate which page is displayed. From the perspective of server-side website deployment, there are two types of web pages: static and dynamic.

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Related publications (7)

Related people (7)

Related units (1)

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Understanding the Web

Eda Baykan

The World Wide Web is one of the most widely used information resources. Understanding the web better will enable us to benefit more of it. In this thesis we develop techniques to learn the properties of the web pages like language and topic using only the URLs of web pages. Furthermore we make a comparison and evaluation of web page sampling algorithms to learn about the web properties like content length, top level domain and outdegree distribution. In the first part of this thesis, we develop high performance classifiers for web page language classification using only the URL of web pages. We make a comprehensive study of features and algorithms and test the performance of our classifiers on various real data sets. For language classification the quality of our URL-based classifiers rival the quality of classifiers based on content. Language classification from URL is useful when the content of the web page is not available and when the classification speed is important. Language classifiers based on URLs can be used by crawlers of general and language specific search engines to avoid bandwidth waste. In the second part of this thesis, we investigate whether web page topic classification can be done only with URL. We explore this problem in various dimensions like experimenting with different algorithms, features, data sets and topics. URL-based topic classification is useful when the content of the web page is not available or the content is hidden in images. Topic classifiers based on URLs can be used to filter information and in applications like topic focused crawlers. Although content based topic classifiers give better performances, our URL-based topic classifiers work reasonably well and can be used as a signal to improve the performance of content based classifiers. In the third part of this thesis, we compare the state of art web page sampling algorithms and analyze the samples returned by these algorithms using the web properties like content length, top level domain and outdegree distribution. We discuss the strengths and weaknesses of each algorithm and propose improvements based on experimental results. The sampling algorithms we run on the web are influenced by the structure of the web. We investigate the relationship between the properties of the web and the structure of it. A uniform random sample of the web would be quite useful to learn about the composition and development of the web as it is not possible to download all the web pages to determine the properties of the web.

EPFL2009

A Comparison of Techniques for Sampling Web Pages

Monika Henzinger, Eda Baykan

As the World Wide Web is growing rapidly, it is getting increasingly challenging to gather representative information about it. Instead of crawling the web exhaustively one has to resort to other techniques like sampling to determine the properties of the web. A uniform random sample of the web would be useful to determine the percentage of web pages in a specific language, on a topic or in a top level domain. Unfortunately, no approach has been shown to sample the web pages in an unbiased way. Three promising web sampling algorithms are based on random walks. They each have been evaluated individually, but making a comparison on different data sets is not possible. We directly compare these algorithms in this paper. We performed three random walks on the web under the same conditions and analyzed their outcomes in detail. We discuss the strengths and the weaknesses of each algorithm and propose improvements based on experimental results.

2009

Purely URL-based Topic Classification

Monika Henzinger, Ingmar Weber, Eda Baykan, Ludmila Marian

Given only the URL of a web page, can we identify its topic? This is the question that we examine in this paper. Usually, web pages are classified using their content, but a URL-only classifier is preferable, (i) when speed is crucial, (ii) to enable content filtering before an (objectionable) web page is downloaded, (iii) when a page's content is hidden in images, (iv) to annotate hyperlinks in a personalized web browser, without fetching the target page, and (v) when a focused crawler wants to infer the topic of a target page before devoting bandwidth to download it. We apply a machine learning approach to the topic identification task and evaluate its performance in extensive experiments on categorized web pages from the Open Directory Project (ODP). When training separate binary classifiers for each topic, we achieve typical F-measure values between 80 and 85, and a typical precision of around 85. We also ran experiments on a small data set of university web pages. For the task of classifying these pages into faculty, student, course and project pages, our methods improve over previous approaches by 13.8 points of F-measure.

2009

Static web page

A static web page (sometimes called a flat page or a stationary page) is a web page that is delivered to the user's web browser exactly as stored, in contrast to dynamic web pages which are generated by a web application. Consequently, a static web page often displays the same information for all users, from all contexts, subject to modern capabilities of a web server to negotiate content-type or language of the document where such versions are available and the server is configured to do so.

Web content

Web content is the text, visual or audio content that is made available online and user encountered as part of the online usage and experience on websites. It may include text, , sounds and audio, online videos, among other items placed within web pages. In the book Information Architecture for the World Wide Web, Lou Rosenfeld and Peter Morville wrote, "We define content broadly as 'the stuff in your website.

CSS

Cascading Style Sheets (CSS) is a style sheet language used for describing the presentation of a document written in a markup language such as HTML or XML (including XML dialects such as SVG, MathML or XHTML). CSS is a cornerstone technology of the World Wide Web, alongside HTML and JavaScript. CSS is designed to enable the separation of content and presentation, including layout, colors, and fonts.

Introduction to Geographic Information Systems (part 2)

Ce cours constitue la seconde partie d'un enseignement consacré aux bases théoriques et pratiques des systèmes d’information géographique. Il propose une introduction aux systèmes d’information géogra

Introduction to Geographic Information Systems (part 2)

Geographical Information Systems 2

This course is the second part of a course dedicated to the theoretical and practical bases of Geographic Information Systems (GIS). It offers an introduction to GIS that does not require prior compu

Covers quantum wire analysis, transmission function, and tunneling in dots.

Covers the fundamentals of quantum chemistry, focusing on observables and eigenfunctions.

Covers the Markov Chain Monte Carlo method and the Metropolis-Hastings algorithm for generating samples from a target probability distribution.