World Wide Web | EPFL Graph Search

vignette|Logo historique du World Wide Web par Robert Cailliau. vignette|Où la toile est née, plaque commémorant la création du World Wide Web dans les locaux du CERN. Le World Wide Web ( ; littéralement la « toile (d’araignée) mondiale », abrégé www ou le Web), la toile mondiale ou la toile, est un système hypertexte public fonctionnant sur Internet. Le Web permet de consulter, avec un navigateur, des pages accessibles sur des sites. L’image de la toile d’araignée vient des hyperliens qui lient les pages web entre elles. Le Web est une des applications d’Internet, distincte d’autres applications comme le courrier électronique, la visioconférence et le partage de fichiers en pair à pair. Inventé en 1989-1990 par Tim Berners-Lee suivi de Robert Cailliau, c'est le Web qui a rendu les médias grand public attentifs à Internet. Depuis, le Web est fréquemment confondu avec Internet ; en particulier, le mot toile est souvent utilisé dans les textes non techniques sans qu'il soit clair si l'

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

Eda Baykan, Monika Henzinger

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

WebAL Comes of Age: A Review of the First 21 Years of Artificial Life on the Web

Joshua Evan Auerbach, Sebastian Risi, Jason Yosinski

We present a survey of the first 21 years of web-based artificial life (WebAL) research and applications, broadly construed to include the many different ways in which artificial life and web technologies might intersect. Our survey covers the period from 1994—when the first WebAL work appeared—up to the present day, together with a brief discussion of relevant precursors. We examine recent projects, from 2010–2015, in greater detail in order to highlight the current state of the art. We follow the survey with a discussion of common themes and methodologies that can be observed in recent work and identify a number of likely directions for future work in this exciting area.

Mit Press2016

Understanding the Web

Eda Baykan

EPFL2009