Searching

Semantic Search
can be defined as the notion of using or exploiting metadata to improve search on documents. In the case of, it more explicitly refers to embedding metadata in HTML5. have evolved from producing a series of probabilistic results or links, to becoming answer engines that produce much more specific results for users. Semantic search allows for incredibly high relevancy answers to queries entered into. In other words, semantic searching should provide the results that a user is truly looking for.

Determining the user's intent is one of the best ways to exploit semantic technology. It can be accomplished by:


 * Correctly interpreting either a portion of a query, or the query entirely
 * Providing an educated guess to an answer by reasoning via information from well-known resources
 * Forming a knowledge base or web of data by adding consumed information and its reasoning 1

“Structured data is becoming an increasingly important part of the web ecosystem. Google makes use of structured data in a number of ways including  which allow websites to highlight specific types of content in search results. Websites participate by marking up their content using industry-standard formats and schemas.”


 * The image to the left depicts a recent Google  search of the band 'Imagine Dragons'. An immense collection of information is immediately displayed. Users often no longer even need to click on a result to get an answer to their query. In this case, searching for the band name instantly provides a description of the band and its members, images of the band, a full list of their songs, a calendar of their upcoming events, various YouTube videos, and a vast array of news articles related to the band. In total the search returned over 91 million results. In addition to this, websites with subsections such as the Imagine Dragons website or their Wikipedia page provide links to information that used to be found deeper within the websites.

Timeline of Semantic Web Adoption

 * Yahoo! opens Search Monkey:  February 2008Semantic Search An Introduction
 * Bing acquires Powerset: July 2008
 * Google  introduces reviews and aggregate reviews using rich snippets: May 2009
 * Google introduces specifying an image’s license using RDFa:  August 2009
 * Google introduces RDFa support for videos:  September 2009
 * Google encourages webmasters to “help us make the web better” by using rich snippets: October 2009
 * Google announces use of structured data to describe an organization: March 2010
 * Google announces rich snippets for recipes: April 2010
 * Google announces rich snippets go international: April 2010
 * Facebook announces : April 2010
 * Google acquires MetaWeb: July 2010
 * Google Refine is announced: November 2010
 * Google announces rich snippets for shopping sites: November 2010
 * Google, Yahoo, and Bing announce : June 2011 1

Semantic Search vs. Semantic Web

 * "The Semantic Web  is a set of technologies for representing, storing, and querying information. Although these technologies can be used to store textual data, they typically are used to store smaller bits of data." 2


 * "Semantic search is the process of typing something into a search engine and getting more results than just those that feature the exact keyword you typed into the search box. Semantic search will take into account the context and meaning of your search terms. It's about understanding the assumptions that the searcher is making when typing in that search query." 2

Therefore, the semantic web can include things like numbers and dates for answering a very complex question. Semantic search will focus on the text, but the semantic web focuses on obtaining data from many sources and formats.

Schema
is a well-known website that can provide a collection of 'schemas', or html tags, that webmasters can employ in order to be recognized by major search providers. The major search engines including Bing, Google, and Yahoo! rely on the markup in order to improve the output of their search results, resulting in higher relevancy for query responses.

"Many sites are generated from structured data, which is often stored in databases. When this data is formatted into HTML, it becomes very difficult to recover the original structured data. Many applications, especially search engines, can benefit greatly from direct access to this structured data. On-page markup enables search engines to understand the information on web pages and provide richer search results in order to make it easier for users to find relevant information on the web. Markup can also enable new tools and applications that make use of the structure." 3