What Is Semantic Search?
Semantic search is a data searching technique that a search query aims to not only find keywords, but also to determine the intent and contextual meaning of the the words a person is using for search. Semantic search provides more meaningful search results by evaluating and understanding the search phrase and finding the most relevant results in a website, database or any other data repository.
Semantic search seeks to improve search accuracy by understanding searcher intent and the contextual meaning of terms as they appear in the searchable dataspace, whether on the Web or within a closed system, to generate more relevant results.Semantic search systems consider various points including context of search, location, intent, variation of words, synonyms, generalized and specialized queries, concept matching and natural language queries to provide relevant search results.Major web search engines like Google and Bing incorporate some elements of semantic search.
We can distinguish two important forms of search ; navigational and research .In navigational search, the user is using the search engine as a navigation tool to navigate to a particular intended document. Semantic search is not applicable to this kind of searches. In research search, the user provides the search engine with a phrase which is intended to denote an object about which the user is trying to gather/research information. There is no particular document which the user knows about and is trying to get to. Rather, the user is trying to locate a number of documents which together will provide the desired information.
Semantic search works on the principles of language semantics. Unlike typical search algorithms, semantic search is based on the context, substance, intent and concept of the searched phrase. Semantic search also incorporates location, synonyms of a term, current trends, word variations and other natural language elements as part of the search. Semantic search concepts are derived from various search algorithms and methodologies, including keyword-to-concept mapping and graph patterns.
1- Handling morphological variations
2- Handling synonyms with correct senses
3- Handling generalizations
4- Handling concept matching
5- Handling knowledge matching
6- Handling natural language queries and questions
7- Ability to point to uninterrupted paragraph and the most relevant sentence
8- Ability to Customize and Organic Progress
9- Ability to operate without relying on statistics, user behavior, and other artificial means
10- Ability to detect its own performance
http://en.wikipedia.org/wiki/Semantic\_search#Semantic\_search\_portals
http://www.techopedia.com/definition/23731/semantic-search
http://davidamerland.com/seo-tips/986-five-steps-to-a-fully-semantic-web.html