Titlebook: Entropy Guided Transformation Learning: Algorithms and Applications; Cícero Nogueira Santos,Ruy Luiz Milidiú Book 2012 The Author(s) 2012

描绘

Prepare Your SharePoint Intranet,n a given text. Some of these event structures include . did . to ., . and .. We evaluate the performance of ETL over two English language corpora: CoNLL-2004 and CoNLL-2005. ETL system achieves regular results for the two corpora. However, for the CoNLL-2004 Corpus, our ETL system outperforms the T

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Adding Sophistication to Basic I/O,ation based learning by solving the TBL bottleneck: the construction of good template sets. ETL relies on the use of the information gain measure to select feature combinations that provide effective template sets. In this work, we also present ETL committee, an ensemble method that uses ETL as the

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https://doi.org/10.1007/978-1-4471-2978-3Entropy Guided Transformation Learning; Named Entity Recognition; Part-of-speech Tagging; Semantic Role

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Cícero Nogueira Santos,Ruy Luiz MilidiúDetailed explanation of the Entropy Guided Transformation Learning algorithm.Detailed explanation of how to create ensembles of ETL classifiers.Explains how to apply ETL to four NLP problems.Includes

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Introduction generalizes transformation based learning (TBL) by automatically solving the TBL bottleneck: the construction of good template sets. The main advantage of ETL is its easy applicability to natural language processing (NLP) tasks. This introductory chapter presents the motivation behind ETL and summa

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General ETL Modeling for NLP Tasksame configuration when applying ETL for the four examined tasks. Hence, the ETL modeling phase is performed with little effort. Moreover, the use of a common parameter setting can also provide some insight about the robustness of the learning algorithm. This chapter is organized as follows. In Sect.