SONAR: A Semantically Empowered Financial Search Engine

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.

• Type: Conference
• Year: 2009
• Where: IWINAC
• Authors: Juan Miguel Gómez, Francisco García Sánchez, Rafael Valencia-García, Ioan Toma, Carlos García Moreno
• Keywords: Artificial Intelligence, Disparate Data Models, Heterogeneous Business Sources, IWINAC 2009, State-of-the-art Technology Caveats