- About
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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 3 of 3 (0.048 seconds)Spelling suggestions: "subject:"domainspecific search"" "subject:"domainhspecific search""
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Towards completely automatized HTML form discovery on the webMoraes, Maurício Coutinho January 2013 (has links)
The forms discovered by our proposal can be directly used as training data by some form classifiers. Our experimental validation used thousands of real Web forms, divided into six domains, including a representative subset of the publicly available DeepPeep form base (DEEPPEEP, 2010; DEEPPEEP REPOSITORY, 2011). Our results show that it is feasible to mitigate the demanding manual work required by two cutting-edge form classifiers (i.e., GFC and DSFC (BARBOSA; FREIRE, 2007a)), at the cost of a relatively small loss in effectiveness.
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Towards completely automatized HTML form discovery on the webMoraes, Maurício Coutinho January 2013 (has links)
The forms discovered by our proposal can be directly used as training data by some form classifiers. Our experimental validation used thousands of real Web forms, divided into six domains, including a representative subset of the publicly available DeepPeep form base (DEEPPEEP, 2010; DEEPPEEP REPOSITORY, 2011). Our results show that it is feasible to mitigate the demanding manual work required by two cutting-edge form classifiers (i.e., GFC and DSFC (BARBOSA; FREIRE, 2007a)), at the cost of a relatively small loss in effectiveness.
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Towards completely automatized HTML form discovery on the webMoraes, Maurício Coutinho January 2013 (has links)
The forms discovered by our proposal can be directly used as training data by some form classifiers. Our experimental validation used thousands of real Web forms, divided into six domains, including a representative subset of the publicly available DeepPeep form base (DEEPPEEP, 2010; DEEPPEEP REPOSITORY, 2011). Our results show that it is feasible to mitigate the demanding manual work required by two cutting-edge form classifiers (i.e., GFC and DSFC (BARBOSA; FREIRE, 2007a)), at the cost of a relatively small loss in effectiveness.
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