Visualization is a technique to graphically represent sets of data. When data is large or abstract, visualization can help make the data easier to read or understand. There are visualization tools for search, music, networks, online communities, and almost anything else you can think of. Whether you want a desktop application or a web-based tool, there are many specific tools are available on the web that let you visualize all kinds of data. Here are some of the best:
The CLEVER search engine incorporates several algorithms that make use of the Web's hyperlink structure for discovering high-quality information. It can be exceedingly difficult to locate resources on the World Wide Web that are both high-quality and relevant to a user's informational needs. Traditional automated search methods for locating information on the Web are easily overwhelmed by low-quality and unrelated content. Second generation search engines have to have effective methods for focusing on the most authoritative documents. The rich structure implicit in hyperlinks among Web documents offers a simple, and effective, means to deal with many of these problems. Additional Information: Publications:
Abstract. In order to support web applications to understand the content of HTML pages an increasing number of websites have started to annotate structured data within their pages using markup formats such as Microdata, RDFa, Microformats. The annotations are used by Google, Yahoo!, Yandex, Bing and Facebook to enrich search results and to display entity descriptions within their applications. In this paper, we present a series of publicly accessible Microdata, RDFa, Microformats datasets that we have extracted from three large web corpora dating from 2010, 2012 and 2013.
M. abbas Choudhary M. Asif Naeem. IEEE International Conference on Advanced Computer vision and Information Technology, Seite 397-405. http://www.itvidya.com/acvit_2007_aurangabad, Department of Computer Science and IT, Dr. B.A.M. U Aurangabad. (MS) India, I. K. International, (Dezember 2007)
A. Arasu, und H. Garcia-Molina. Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, San Diego, California, USA, June 9-12, 2003, Seite 337-348. ACM, (2003)