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Title:
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AUTOMATIC IMPROVEMENT OF TERMS USED IN FOCUSED CRAWLING PROCESSES ON WEB PAGES |
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Author(s):
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Gilson Faria Costa, Guilherme Tavares de Assis and Marcos Vinicius Oliveira Souza |
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ISBN:
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978-989-8533-69-2 |
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Editors:
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Pedro Isaías and Hans Weghorn |
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Year:
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2017 |
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Edition:
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Single |
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Keywords:
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Automatic Improvement of Terms, Web Crawling, Focused Crawling |
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Type:
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Full Paper |
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First Page:
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71 |
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Last Page:
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78 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The great popularity and, specially, the fast Web growth have led to the proposal and analysis of new techniques for helping users to locate effectively the needed information in a satisfactory time, without much difficulty. Traditional crawlers are not capable to identify relevant sub-spaces on Web related to a specific theme; however, focused crawlers are capable to solve, effectively and efficiently, the mentioned problem. Usually, a focused crawler process requires, as an input parameter, a well-defined set of terms that express the desired topic of interest; depending on such set of terms, the effectiveness of a crawling process may not be satisfactory. In order to automatically improve the set of terms necessary to perform focused crawling processes related to a genre-aware approach, we propose two strategies in this work. Our experiments generated results that improved precision and F1 measures by up to 88.9% and 32.1%, respectively, in crawling processes that considered not well-defined sets of terms as input parameter. |
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