TinEye is a reverse image search engine. You can submit an image to TinEye to find out where it came from, how it is being used, if modified versions of the image exist, or to find higher resolution versions. TinEye is the first image search engine on the web to use image identification technology rather than keywords, metadata or watermarks.
yovisto is an new video search engine for educational video content and will be helpful for students or common interested peoples to looking for online lectures and educational staff. yovisto allows searching within videos. Furthermore, there are many other features like: tagging, adding comments, discussing, interaction with other users, uploading videos and organising your videos, etc.
DeepDyve delivers fast, easy access to the vast amounts of expert information hidden in the Deep Web. Today we're focusing in just a few subject areas including Medical and Life Sciences but we are rapidly expanding into additional markets.
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..