SEMANTIC SEARCH

One of the greatest challenges facing innovation and knowledge workers – those folks in your organization tasked with developing new products, finding new markets, and improving existing products – is accessing the information they need in order to solve problems and make decisions.

But accessing knowledge – even internal corporate knowledge – is a time-consuming, tedious and often fruitless undertaking, with some studies claiming knowledge workers spend 30 percent or more of their time performing the ubiquitous task of ‘searching’.

Effective knowledge retrieval demands that computers are able to correctly analyze the information requirements of the user, and to precisely match these requirements to the contents of the documents being searched. To accomplish this level of intelligence in automation, the natural language text of the source documents and query must be analyzed into elements that convey meaning, and then employ these methods as the basis for unambiguous comparison between the query and the documents.

Semantic search promises to help make the finding of information via queries easier.

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