The Experts below are selected from a list of 32337 Experts worldwide ranked by ideXlab platform
Kimberly S Winchester - One of the best experts on this subject based on the ideXlab platform.
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phonological changes during the transition from one Word to productive Word Combination
Journal of Child Language, 2010Co-Authors: Katsura Aoyama, Ann M Peters, Kimberly S WinchesterAbstract:We investigated developmental changes during the transition from one-Word to two-Word production, focusing on strategies to lengthen utterances phonologically and to control utterances suprasegmentally. We hypothesized that there is a period of reorganization at the onset of Word Combinations indicated by decreases in both filler syllables (Fillers) and final syllable lengthening (FSL). The data are from a visually impaired child (Seth) between 1; 6.21 and 1; 10.26. Seth produced many Fillers until 1; 9 when their number decreased for about two weeks after which they changed in nature. FSL was observed until 1; 8, but diminished at 1; 9. These two regressions coincide with the onset of Word Combination.
Lujiang Zhang - One of the best experts on this subject based on the ideXlab platform.
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Word Combination kernel for text classification with support vector machines
Computing and Informatics \ Computers and Artificial Intelligence, 2013Co-Authors: Lujiang ZhangAbstract:In this paper we propose a novel kernel for text categorization. This kernel is an inner product defined in the feature space generated by all Word Combinations of specified length. A Word Combination is a collection of unique Words co-occurring in the same sentence. The Word Combination of length k is weighted by the k rm th root of the product of the inverse document frequencies (IDF) of its Words. By discarding Word order, the Word Combination features are more compatible with the flexibility of natural language and the feature dimensions of documents can be reduced significantly to improve the sparseness of feature representations. By restricting the Words to the same sentence and considering multi-Word Combinations, the Word Combination features can capture similarity at a more specific level than single Words. A computationally simple and efficient algorithm was proposed to calculate this kernel. We conducted a series of experiments on the Reuters-21578 and 20 Newsgroups datasets. This kernel achieves better performance than the Word kernel and Word-sequence kernel. We also evaluated the computing efficiency of this kernel and observed the impact of the Word Combination length on performance.
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Word Combination kernel for text categorization
Journal of Digital Information Management, 2012Co-Authors: Lujiang Zhang, Shiyin QinAbstract:We proposed a novel kernel for text categorization. This kernel is an inner product in the feature space generated by all Word Combinations of specified length. A Word Combination is a collection of different Words co-occurring in the same sentence. The Word Combination of length k is weighted by the k-th root of the product of the inverse document frequencies (IDF) of its Words. A computationally simple and efficient algorithm was proposed to calculate this kernel. By restricting the Words of a Word Combination to the same sentence and considering multi-Word Combinations, the Word Combination features can capture similarity at a more specific level than single Words. By discarding Word order, the Word Combination features are more compatible with the flexibility of natural language and the dimensionality this kernel can be reduced significantly compared to the Word-sequence kernel. We conducted a series of experiments on the Reuters-21578 dataset and 20 Newsgroups dataset. This kernel consistently achieves better performance than the classical Word kernel and Word-sequence kernel on the two datasets. We also assessed the impact of Word Combination length on performance and compared the computing efficiency of this kernel to those of the Word kernel and Word-sequence kernel.
Martin C Michel - One of the best experts on this subject based on the ideXlab platform.
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a systematic review of urinary bladder hypertrophy in experimental diabetes part 2 comparison of animal models and functional consequences
Neurourology and Urodynamics, 2018Co-Authors: Johanne H Ellenbroek, Ebru Arioglu Inan, Martin C MichelAbstract:Aims To explore whether the bladder hypertrophy consistently seen in rats upon streptozotocin injection also occurs in other animal models of type 1 or 2 diabetes and how hypertrophy is linked to functional alterations of the urinary bladder. Methods A systematic search for the key Word Combination "diabetes," "bladder," and "hypertrophy" was performed in PubMed; additional references were identified from reference lists of those publications. All papers were systematically extracted for relevant information. Results Models other than streptozotocin-injected rats and female animals have been poorly studied. Most animal models of diabetes exhibit less bladder hypertrophy as compared to streptozotocin-injected rats. However, this is not linked to type 1 versus 2 diabetes models, and type 2 models with comparable elevation of blood glucose may exhibit strong or only minor hypertrophy. Bladder dysfunction is frequently observed in experimental diabetes and mostly manifests as increased compliance but does not segregate with hypertrophy. It may at least partly reflect the need to handle large amounts of urine in models associated with major elevation of blood glucose. Conclusions To better understand the relevance of bladder hypertrophy in many models of experimental diabetes, more studies in models of type 2 diabetes are urgently needed. Moreover, the role of factors other than hypertrophy in the genesis of bladder dysfunction requires further exploration.
L I Guichen - One of the best experts on this subject based on the ideXlab platform.
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micro blog sentiment classification based on three Word Combination model
Journal of Shanxi University, 2015Co-Authors: L I GuichenAbstract:For micro-blog opinion analysis,this paper proposed a classification algorithm based on threeWord-Combination model.By constructing sentiment lexicon and micro-blog three-Word-Combination model,the unlabeled corpus are graded and tagged by sentiment polarity automatically.On this basis,the automatic annotation corpus is used train a sentiment classifier.The testing results show that the accuracy can reach 79.26%,by annotated to training corpora without artificial participation.
Katsura Aoyama - One of the best experts on this subject based on the ideXlab platform.
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phonological changes during the transition from one Word to productive Word Combination
Journal of Child Language, 2010Co-Authors: Katsura Aoyama, Ann M Peters, Kimberly S WinchesterAbstract:We investigated developmental changes during the transition from one-Word to two-Word production, focusing on strategies to lengthen utterances phonologically and to control utterances suprasegmentally. We hypothesized that there is a period of reorganization at the onset of Word Combinations indicated by decreases in both filler syllables (Fillers) and final syllable lengthening (FSL). The data are from a visually impaired child (Seth) between 1; 6.21 and 1; 10.26. Seth produced many Fillers until 1; 9 when their number decreased for about two weeks after which they changed in nature. FSL was observed until 1; 8, but diminished at 1; 9. These two regressions coincide with the onset of Word Combination.
