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Wikipedia articles about search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites that have a search facility for online databases.

"Search engines, including web search engines, selection-based search engines, metasearch engines, desktop search tools, and web portals and vertical market websites have a search facility for online databases."

"Discovery Hub is an exploratory search engine built on top of the famous encyclopedia on the web, Wikipedia. The exploratory search is a new way to search the web, not to find what you are searching, but to find what you are not searching, and might be intersting for y"

Symbolab is a semantic web search engine for math and science. It allows users to search for equations, formulas and expressions using mathematical symbols and scientific notations as well as full text search. The stated goal of the site is to provide the most relevant search results that are theoretically and semantically similar, rather than visually.

The semantic mapping of the English language is the key to making Natural Language Processing (NLP) effective. Cognition's unique Semantic Map, which it built over the past 24 years, is the most comprehensive and complete map of the English language available today. It can be used in support of the Semantic Web for semantic search, search tools, business analytics, machine translation, document search, context search, and much more.

"Free software for your own search engine, data explorer and research tools based on Apache Lucene / Solr or Elastic Search open-source enterprise-search and open standards for Linked Data and Semantic Web"

"Semantic Search on Linked Data Here you can search across more than 30 million resources contained in the thousands of semantically enriched Open Access Document Repositories and  Data Repositories included in the CHAIN Knowledge Base. Search results are ranked according to the Ranking Web or Repositories. Some exemplar keywords are: cardiology, cell, cornea, geology, linked data, natural gas."

Semantic Web Search Engines\nThis page collects links to Semantic Web Search Engines. Semantic Web Search Engines use robots to crawl RDF data from the Web and provide search and navigation facilities over crawled data.The page is part of the community project [[SweoIG/TaskForces/CommunityProjects/LinkingOpenData|]]

You can use the input field above to search through 4 million interconnected persons, organisations and places in the semantic web. Enter the name, e-mail, nick, homepage, openid, mbox-hash or URI of the person, organisation or place you are searching.

"Dataset Search enables users to find datasets stored across the Web through a simple keyword search. The tool surfaces information about datasets hosted in thousands of repositories across the Web, making these datasets universally accessible and useful."

Publish and Search Relational DatabasesEnth blends database publishing and search to unlock the value of Internet-connected databases and dramatically increase the ease and speed of finding information. Our patented software platform allows you to easily share structured data online and provide users with a quick way to find information using plain text, achieving time savings, cost savings and increased productivity for your organization.

Searching more than 20 million Pubmed Abstracts Semantic Search service provided by hakia.com, Side-by-side comparison to PubMed

SenseBot (Beta) is a semantic search engine that generates a text summary of multiple Web pages on the topic of your search query. It uses text mining and multidocument summarization to extract sense from Web pages and present it to the user in a coherent manner. A "Semantic Cloud" of concepts is displayed above the summary, allowing to steer the focus of the results. To learn about our approach, go to the About SenseBot page, or browse Samples.

Faceted Wikipedia Search allows users to ask complex queries against Wikipedia. The answers to these queries are not generated using key word matching as the answers of search engines like Google or Yahoo, but are generated based on structured information that has been extracted from many different Wikipedia articles.

We're building an extraordinary search engine that leverages the power of conventional search algorithms, human knowledge and the social web.

Find relevant images of Trending Topics in realtime / Nachofoto is a Semantic Time-based Vertical Image Search Engine. Our focus has been to deliver Fresh and Relevant image results for High Volume and Trending queries. Our goal is to change the way people interact with image search engines.

Real-Time Faceted Search is a journey; a journey that enables you to easily tell the internet what you're looking for and let the internet find it for you. It starts with the same key word everyone is familiar with, but then guides the user through a series of contextual prompts, or 'facets', that eventually build out a more 'complex query' more powerful than that of typical keyword search. Through the use of a number of GUI techniques, the user is able to either select or fill in elements of this query in intuitive ways with all the code crunching being hidden in the background. The query can then be run over mashed up linked data sources. This enables the everyday user to build out these deep queries over linked data and receive much more relevant results.