searchengine
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search_engine
deepweb
DiscoverEd is a search prototype developed by Creative Commons to explore metadata enhanced search, specifically for OER. While most search engines rely solely on algorithmic analyses of resources, DiscoverEd can incorporate data provided by the resource publisher or curator . DiscoverEd supports several common metadata formats, including OAI-PMH and RDFa. The use of these formats allows otherwise unrelated educational projects, curators, and repositories to express facts about their resources in the a way that tools (like DiscoverEd) can use for purposes like search and discovery.
DiscoverEd from ccLearn
This search facility normally uses Google's Custom Search Engine (CSE) to search the full-text of material held in open access repositories listed in Open DOAR.
Search Contents of Open Access Repositories
Lucene - Overview - Apache Lucene
Apache Lucene(TM) is a high-performance, full-featured text search engine library written entirely in Java. It is a technology suitable for nearly any application that requires full-text search, especially cross-platform. The Apache Software Foundation provides support for the Apache community of open-source software projects. The Apache projects are defined by collaborative consensus based processes, an open, pragmatic software license and a desire to create high quality software that leads the way in its field. Apache Lucene, Apache Solr, Apache PyLucene, Apache Open Relevance Project and their respective logos are trademarks of The Apache Software Foundation. All other marks mentioned may be trademarks or registered trademarks of their respective owners.
blinkx
blinkx's commitment to innovation is reflected in the ground-breaking, sophisticated, user-orientated products which it has regularly released since the company launched and which includes blinkx Remote, blinkx it and the blinkx Video Wall. blinkx takes a holistic approach to video search : the power of its solution lies in using every characteristic of the video itself to understand the content. For example, blinkx listens to the sound track using speech-to-text technology, looks at the images on screen using advanced video analytics, and reads other information embedded into the file by using media-analysis plug-ins to extract, for example, closed captioning. In this way, blinkx is processing as much information as possible to enable both extremely accurate search, and more advanced operations such as automatic hyperlinking of related content or implicit query, which understands the content a user is producing and viewing.