Presentation
A Novel Approach to Web Information Extraction
Author/s | Reina Quintero, Antonia María
Jiménez Aguirre, Patricia Corchuelo Gil, Rafael |
Department | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos |
Publication Date | 2015-06 |
Deposit Date | 2023-03-21 |
Published in |
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ISBN/ISSN | 978-3-319-19026-6 (impreso) 978-3-319-19027-3 (online) 1865-1348 (impreso) 1865-1356 (online) |
Abstract | Business Intelligence requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers. The Web is the largest source of information nowadays. ... Business Intelligence requires the acquisition and aggregation of key pieces of knowledge from multiple sources in order to provide valuable information to customers. The Web is the largest source of information nowadays. Unfortunately, the information it provides is available in semi-structured human-friendly formats, which makes it difficult to be processed by automated business processes. Classical propositional and ILP machine-learning techniques have been applied for this purpose. However, the former have not enough expressive power, whereas the latter are more expressive but intractable with large datasets. Propositionalisation was devised as a means to provide propositional techniques with more expressive power, enabling them to exploit structural information in a propositional way that allows them to be efficient. In this paper, we present a proposal to extract information from semi-structured web documents that uses this approach. It leverages a classical propositional machine learning technique and enhances it with the ability to learn from an unbounded context, which helps increase its precision and recall. Our experiments prove that our proposal outperforms other state-of-art techniques in the literature |
Funding agencies | Ministerio de Ciencia Y Tecnología (MCYT). España Junta de Andalucía Ministerio de Ciencia e Innovación (MICIN). España Ministerio de Economía, Industria y Competitividad Ministerio de Economía y Competitividad (MINECO). España |
Project ID. | TIN2007-64119
P07-TIC-2602 P08-TIC-4100 TIN2008-04718-E TIN2010-21744 TIN2010-09809-E TIN2010-10811-E TIN2010-09988-E TIN2011-15497-E TIN2013-40848-R |
Citation | Reina Quintero, A.M., Jiménez Aguirre, P. y Corchuelo Gil, R. (2015). A Novel Approach to Web Information Extraction. En 18th International Conference: Business Information Systems (BIS 2015) (152-161), Poznań, Polonia: Springer International Publishing AG. |
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