SONAR: A Semantically Empowered Financial Search Engine

Authors:
Juan Miguel Gómez;Francisco García-Sánchez;Rafael Valencia-García;Ioan Toma;Carlos García Moreno
Affiliations:
Departamento de Informática, Escuela Politécnica Superior, Universidad Carlos III de Madrid, Leganés, Madrid, Spain;Departamento de Informática y Sistemas, Univeridad de Murcia, Spain;Departamento de Informática y Sistemas, Univeridad de Murcia, Spain;STI Innsbruck, University of Innsbruck, Innsbruck, Austria A6020;Indra Software Labs, Madrid, Spain 28045
Venue:
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Year:
2009

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Abstract

The increasingly huge volume of financial information found in a number of heterogeneous business sources is characterized by unstructured content, disparate data models and implicit knowledge. As Semantic Technologies mature, they provide a consistent and reliable basis to summon financial knowledge properly to the end user. In this paper, we present SONAR, a semantically enhanced financial search engine empowered by semi-structured crawling, inference-driven and ontology population strategies bypassing the present state-of-the-art technology caveats and shortcomings.