First Intelligent Financial Search Engine Developed

Researchers from the Carlos III University of Madrid (UCM3) have completed the development of the first search engine designed to search for information from the financial and stock market sector based on semantic technology, which enables one to make more accurate thematic searches adapted to the needs of each user.

Unlike conventional search engines, SONAR -so named by its creators- enables the user to perform structured searches which are not based solely on concordance with a series of key words. This corporate financial search engine based on semantic technology, as described on the project website (http://www.proyecto-sonar.org), was developed by researchers from the UC3M in partnership with the University of Murcia, el Instituto de Empresa (the Business Institute) and the company Indra.

According to its creators, it has two main advantages. First, its effectiveness in a concrete domain- that of finance- which is closely defined and has very precise vocabulary. According to Juan Miguel Gómez Berbís, from the Computer Department of the UC3M “This verticality distinguishes SONAR from other more generic search engines, such as Google or Bing” Second, its capacity to establish relations between news, share valuations and prices via logical reasoning.

The first prototype works by making use of semantic web elements. Basically, the system collects data from both public information sources (Internet) and private, corporate ones (Intranet), adds them to a repository of semantically recorded data (labelled and structured) and allows intelligent access to this data. To achieve this, the platform incorporates an inference engine, a mechanism capable of performing reasoning tasks on the recorded information, as well as a natural language processor, which helps the user to perform the search in the simplest way possible. In this way the results obtained are matched to requests, eliminating ambiguities in polysemic terms, for example in searches carried out by users on stored data. “SONAR enables us to establish relations between different sources of information and discover and expand our knowledge, while at the same time it allows us to classify them so that users can get much more benefit from the experience”

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Tags: conventional search engines, financial search engine, generic search engines, inference engine, Innovation, market sector, natural language processor, public information sources, share valuations, thematic searches

This entry was posted on Sunday, October 4th, 2009 at 11:47 am and is filed under Finance, Innovation, Science Digest / Science Daily. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.