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Finding information on the Web isn’t hard, as long as you know what you’re looking for. Sometimes, though, the most useful information can remain hidden within the body of a complex document, and only the most carefully chosen combination of keywords will uncover it.

Semantic search technologies promise to help change this by returning more relevant information based on an understanding of the relationships between different words. Last week, Netbase Solutions, a company based in Mountain View, CA, released search software called Content Intelligence that organizes searchable content by analyzing sentence structure in a novel way. The company created a demonstration of the platform that searches through health-related information.

When a user enters the name of a disease, he or she is most interested in common causes, symptoms, and treatments, and in finding doctors who specialize in treating it, says Netbase CEO and cofounder Jonathan Spier. So the company’s new software doesn’t simply return a list of documents that reference the disease, as most search engines would. Instead, it presents the user with answers to common questions. For example, it shows a list of treatments and excerpts from documents that discuss those treatments. The Content Intelligence platform is not intended as a stand-alone search engine, Spier explains. Instead, Netbase hopes to sell it to companies that want to enhance the quality of their results.

The software uses an approach called natural-language processing to unravel the structure of sentences. Other semantic search technologies use the same approach but usually focus on keywords and how those words are related. For example, a tool intended for searching medical databases might be built to include information about common names for drugs and how those drugs are related to each other. As a result, those tools only work in specific subject areas and have to be adjusted whenever they are applied to a new topic, says Jens Tellefson, vice president of marketing and product strategy for Netbase.

In contrast, Netbase’s software focuses on recognizing phrases that describe the connections between important words. For example, when the system looks for treatments, it might search for phrases such as “reduce the risk of” instead of the name of a particular drug. Tellefson notes that this isn’t a matter of simply listing instances of this phrase, rather catching phrases with an equivalent meaning. Netbase’s system uses these phrases to understand the relationship between parts of the sentence. Tellefson says that this means the system can be used in different subject areas and does not need constant retraining.

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Credits: Technology Review, Netbase

Tagged: Biomedicine, Web, semantic, healthcare IT, natural-language processing, semantic search

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