ScienceDaily (Sep. 30, 2009) — 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”
Potential users
This search tool is designed for both private investors and large financial concerns. Its creators anticipate that it will be a very useful tool for analysts and stockbrokers. “It will be especially useful to the finance departments of banks and saving banks or to add to an existing search engine added value over its competitors” Gómez Berbís points out. And the search for accurate, reliable, relevant information in this business area has become a key factor in a domain where speed and quality of data are critical factors with an exceptional impact on business processes.
According to the researchers, this project aims to respond to a need from the financial sector, that is, the analysis of a large volume of information in order to take decisions. In this way, the execution of this project will allow the financial community to have access to a set of intelligent systems for the aggregated search of information in the financial domain and enable them to improve procedures for integrating company information and processes.
Researchers are currently incorporating new functions into the search tool and also receiving requests to adapt it to other domains, such as transport and biotechnology. In any case, the project is constantly evolving in order to enhance accuracy and reliability. “In SONAR2 we are working on two Intelligent Decision Support Systems for Financial Investments, one based on Fundamental Analysis and the other on Technical Chartist Analysis, which assists the work of the trader and average investor”, reveals professor Gómez Berbis.
Adapted from materials provided by Universidad Carlos III de Madrid.
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”
Potential users
This search tool is designed for both private investors and large financial concerns. Its creators anticipate that it will be a very useful tool for analysts and stockbrokers. “It will be especially useful to the finance departments of banks and saving banks or to add to an existing search engine added value over its competitors” Gómez Berbís points out. And the search for accurate, reliable, relevant information in this business area has become a key factor in a domain where speed and quality of data are critical factors with an exceptional impact on business processes.
According to the researchers, this project aims to respond to a need from the financial sector, that is, the analysis of a large volume of information in order to take decisions. In this way, the execution of this project will allow the financial community to have access to a set of intelligent systems for the aggregated search of information in the financial domain and enable them to improve procedures for integrating company information and processes.
Researchers are currently incorporating new functions into the search tool and also receiving requests to adapt it to other domains, such as transport and biotechnology. In any case, the project is constantly evolving in order to enhance accuracy and reliability. “In SONAR2 we are working on two Intelligent Decision Support Systems for Financial Investments, one based on Fundamental Analysis and the other on Technical Chartist Analysis, which assists the work of the trader and average investor”, reveals professor Gómez Berbis.
Adapted from materials provided by Universidad Carlos III de Madrid.
