Semantic Search Integration

Semantic Search is a technology that allows machine comprehension of all forms of content.

Traditional Information Retrieval technology is based on the occurrence of words in documents. Most of the present search engines augment this in the context of the Web with information about the hyperlink structure of the Web.
The pieces of data that make

up present-day web based documents are not aware of their relationships with the document’s other pieces of data or for that matter data in other documents. What this essentially means is that the user needs to sort through a list of loosely related keyword results to get what he is actually looking for.

Hence, in order to make search results more relevant to a user, semantic search was conceptualised. It looks for meanings in data, document content, or application code using technologies based on open standards rather than looking for specific keywords in them.

A Semantic search can automatically place pages into dynamic categories, or tag them without human intervention. Knowing what topic a page relates to is invaluable for returning relevant results. It can offer related topics and keywords to help narrow the search successfully.

With a keyword like Tennis the search engine would offer you a list of tennis related images, photos, headline news, history of the sport, championships involved, players, statistics and records, magazines and publications, tennis gear etc - all relevant to Tennis. Thus, instead of merely presenting the user with links to pages with ‘Tennis’ as the keyword, the semantic search engine directly incorporates the related content into the search and produces the results.

Semantic search uses the ‘Natural Language’ for looking up content. What this means is that the search engine uses the entire phrase input by the user. Assume that a user is interested in looking up the many references to Lance Armstrong’s fight against Cancer. A conventional search would return thousands of separate documents containing each of the key words in the search string, which you would have to spend time looking for the exact information. A semantic web search would use the entire search phrase and present the relevant information.

Benefits

• Precise search for everyday business operations
• Adds intelligence to data by using rules and inference technologies
• Better, smaller, analysed set of results
• Enhanced productivity
• Saves time and money

DATASiSAR offers the following services to help integrate semantic search technology into your products/solutions.

• Analyse search requirements
• Define search engine architecture
• Build ontologies
• Define document structure
• Build a search solution

DATASiSAR can also develop for you a product that fully exploits the capabilities of semantic technology.