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Cognitive Science Tags > Tag based links for Chunking

The following links have been tagged chunking by users just like you, because these resources are off-site we cannot guarantee the accuracy or quality of any third-party information.

Text Chunking using Regularized Winnow: (2001), pp. 539-546.This paper describes a text chunking system based on a generalization of the Winnow algorithm.Tong Zhang, Fred Damerau, David Johnson

Source: (2001), pp. 539-546.
Text Chunking Using Transformation -Based Learning: (1995), pp. 82-94.Eric Brill introduced transformation -based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebank-deriv ed data, this technique achieved ...Lance Ramshaw, Mitch Marcus

Source: (1995), pp. 82-94.
Chunking with support vector machines: (2001)We apply Support Vector Machines (SVMs) to identify English base phrases (chunks). SVMs are known to achieve high generalization performance even with input data of high dimensional feature spaces. Furthermore, by the Kernel principle, SVMs can carry out training with smaller computational overhead independent of their dimensionality . We apply weighted voting of 8 SVMsbased systems trained with distinct chunk representation s. Experimental results show that our approach achieves higher accuracy...T Kudo, Y Matsumoto

Source: (2001)
Representing text chunks: (1999)Dividing sentences in chunks of words is a useful preprocessing step for parsing, information extraction and information retrieval. (Ramshaw and Marcus, 1995) have introduced a "convenient" data representation for chunking by converting it to a tagging task. In this paper we will examine seven different data representation s for the problem of recognizing noun phrase chunks. We will show that the the data representation choice has a minor influence on chunking performance. However, equipped with ...T Sang, E Jorn

Source: (1999)
Experiments in German noun chunking: (2002), pp. 1-7.Michael Schiehlen

Source: (2002), pp. 1-7.
Fast methods for kernelbased text analysis: (2003)Kernel-b ased learning (e.g., Support Vector Machines) has been successfully applied to many hard problems in Natural Language Processing (NLP). In NLP, although feature combinations are crucial to improving performance, they are heuristically selected. Kernel methods change this situation. The merit of the kernel methods is that effective feature combination is implicitly expanded without loss of generality and increasing the computational costs. Kernel-based text analysis shows an ...T Kudo, Y Matsumoto

Source: (2003)
Text Chunking Using Transformation -Based Learning: (1995), pp. 82-94.. Transformation -based learning, a technique introduced by Eric Brill (1993b), has been shown to do part-of-speech tagging with fairly high accuracy. This same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebank-deriv ed data, this ...Lance Ramshaw, Mitch Marcus

Source: (1995), pp. 82-94.
Finding clauses in unrestricted text by finitary and stochastic methods: (1988), pp. 219-227.This paper is a report of an attempt to provide a better foundation for parsing text by the use of simple finitary and stochastic computational methods. These simple methods have not figured prominently in the theory and practice of natural langauge parsing, with some exceptions (Langendoen 1975, Church 1982, Ejerbed & Church 1983). For an experimental, and more complicated method to derive all prosodic units in the text-to-speech system, i.e. not just tonal minor and major phrases but every...Eva Ejerhed

Source: (1988), pp. 219-227.
An Algorithm for finding Noun Phrase Correspondence s in Bilingual Corpora: (1993), pp. 17-22.The paper describes an algorithm that employs English and French text taggers to associate noun phrases in an aligned bilingual corpus. The taggers provide part-of-speech categories which are used by finite-state recognizers to extract simple noun phrases for both languages. Noun phrases are then mapped to each other using an iterative re-estimation algorithm that bears similarities to the Baum-Welch algorithm which is used for training the taggers. The algorithm provides an alternative to...Julian Kupiec

Source: (1993), pp. 17-22.
A language--inde pendent shallow--parse r compiler: (2001), pp. 330-337.Alexan dra Kinyon

Source: (2001), pp. 330-337.

If you would like to find additional social bookmark based links on the topic of chunking we recommend the Open Tag Directory > Chunking. If you would like to find related tags we recommend Tag Patterns > Chunking.