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Database optimization for novelty mining of business blogs
Authors:Flora S. Tsai  Agus T. Kwee
Affiliation:1. DEIB – Politecnico di Milano, Piazza Leonardo da Vinci 32, Milano, Italy;2. IIS – Eidgenössische Technische Hochschule Zürich, Switzerland;3. Alma Mater Studiorum - University of Bologna, Italy;4. Dompé Farmaceutici SpA, Italy;5. FEUP – Universidade do Porto, Portugal;6. CINECA, Italy;7. IT4Innovations, VSB – Technical University of Ostrava, Czechia;8. INRIA, Rennes, France;9. Sygic, Slovakia;10. IRISA/CNRS, France
Abstract:The widespread growth of business blogs has created opportunities for companies as channels of marketing, communication, customer feedback, and mass opinion measurement. However, many blogs often contain similar information and the sheer volume of available information really challenges the ability of organizations to act quickly in today’s business environment. Thus, novelty mining can help to single out novel information out of a massive set of text documents. This paper explores the feasibility and performance of novelty mining and database optimization of business blogs, which have not been studied before. The results show that our novelty mining system can detect novelty in our dataset of business blogs with very high accuracy, and that database optimization can significantly improve the performance.
Keywords:
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