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 Web Technologies mature, they provide a consistent and reliable basis to summon financial knowledge properly to the end user. In this paper, we present SEFSS, a semantically enhanced financial search engine empowered by semi-structured crawling, inference-driven and ontology population strategies bypassing the present state-ofthe- art technology caveats and shortcomings.

Keywords: Semantic Web Technologies, financial knowledge, ontology, Web-services, data crawling

ACM Classification Keywords: I.2.4 Knowledge Representation Formalisms and Methods - Semantic networks, H.3.3 Information Search and Retrieval - Retrieval models

Link:

INTEGRATION OF FINANCIAL DOMAIN KNOWLEDGE ON BASE OF SEMANTIC WEB TECHNOLOGIES

Anatoly Gladun, Julia Rogushina, Rodrigo Martínez-Béjar?, Francisco García- Sanchez and Rafael Valencia-García?

http://foibg.com/ibs_isc/ibs-19/ibs-19-p12.pdf