E. Giglia. European journal of physical and rehabilitation medicine, 44 (2):
221-30(Juni 2008)5633<m:linebreak></m:linebreak>LR: 20100601; JID: 101465662; ppublish;<m:linebreak></m:linebreak>Cerca bibliogràfica.
K. Kingsley, G. Galbraith, M. Herring, E. Stowers, T. Stewart, und K. Kingsley. BMC medical education, (Januar 2011)6676<br/>JID: 101088679; OID: NLM: PMC3097006; 2010/06/29 received; 2011/04/25 accepted; 2011/04/25 aheadofprint; epublish;<br/>Cerca bibliogràfica.
K. Becker, und F. Stalder (Hrsg.) Studien-Verlag, Innsbruck u.a., (2009)Viele Beiträge in diesem Band wurden zuerst auf der Deep Search-Konferenz vorgestellt, die am 8. November 2008 in Wien stattfand..
J. Osterhoff, J. Waitelonis, und H. Sack. Proc. of 2. Workshop Interaktion und Visualisierung im Daten-Web (IVDW 2012), im Rahmen der INFORMATIK 2012, Braunschweig, (2012)
J. Waitelonis, und H. Sack. Proceedings of International Conference on Semantic Systems (i-semantics), September 2-4, 2009, Graz, Austria, Verlag der TU Graz, Austria, (2009)
J. Waitelonis, und H. Sack. Proceedings of the 2nd IEEE International Workshop on Data Semantics for Multimedia Systems and Applications (DSMSA), in conjunction with IEEE International Symposium on Multimedia (ISM), 14-16 December, 2009, San Diego, California, USA, Seite 540--545. IEEE Computer Society, (2009)
J. Waitelonis, N. Ludwig, und H. Sack. Proceedings of 5th International Conference on Semantic and Digital Media (SAMT 2010), December 1-3, 2010, DFKI Saarbrücken, Germany, (2010)
J. Waitelonis, M. Knuth, L. Wolf, J. Hercher, und H. Sack. Proceedings of the Workshop on Linked Data in the Future Internet at the Future Internet Assembly, December 16-17, 2010, Ghent, Belgium, CEUR Workshop Proceedings, 700, (2010)
S. Brin, und L. Page. http://ilpubs.stanford.edu:8090/361/, (1998)In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present in hypertext. Google is designed to crawl and index the Web efficiently and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/. To engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system which can exploit the additional information present in hypertext. Also we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want..
B. Pinkerton. Proceedings of the 2nd International World Wide Web, Volume 18(6) von Online & CDROM review: the international journal of, Medford, NJ, USA, Learned Information, (1994)