Semantic Search and Natural Language Processing Engine
One most exciting thing with the World Wide Web must be searching engine, it is used almost every day by everyone. The searching engine is able to return us a mass of hypertext as long as we enter a keyword. It often works when we are looking up a definition of a new term or queuing a solution to a specific procedure. The working theory of searching engine is basically following the keywords, finding our more relative information from the web. So the traditional searching engine is also a lexical searching engine.
But, the lexicon-based searching engine is not always reliable, especially with a wordy input of keywords in a Format. Because the searching engine is finding out literal matches based on a set of keywords, more importantly, the traditional searching engine is not able to figure out the priority of a sentence so that it can not understand the meaning of a sentence. Thus, people yearn for a semantic engine with the ability to understand the meaning of search queries rather than simply finding literal matches. Semantic search seeks to improve search accuracy by comprehending the intent of the searcher, and the contextual meaning of terms as they appear in the searchable database, i.e. either on Web or within a local system, to generate more relevant results. The designer takes such aspects below into consideration when constructing a semantic searching engine:
Context of search Location Intent Variation of words Synonyms Generalized and specialized queries Concept matching Natural language queries
It can be concluded as a process to transform search queries from natural language form into formatted language for the computer to understand. Besides making use of the contextual meaning of teams by learning from past results and creating links between entities, semantic searching engine represents knowledge in a way suitable for meaningful retrieval.
In fact, some searching engine has made a breakthrough into semantic search such as Google, you can ask natural language questions like ‘What is the weather like today’ and it provides you the current local weather information at the very beginning of the result. This is more than smart compared with the previous lexical searching engine. Nowadays, some believe it is possible to retrieve knowledge from richly structured data sources like ontologies and XML as a set of semantic search techniques is founded on the web. These techniques will enable the formal articulation of domain knowledge at a high level of expressiveness and enable the user to specify their intent in more detail a query time.