The Experts below are selected from a list of 42696 Experts worldwide ranked by ideXlab platform
Marisi Debora - One of the best experts on this subject based on the ideXlab platform.
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The effect learning styles on students Sentence Structure achievement
2014Co-Authors: Marisi DeboraAbstract:This article presents the research findings of the effect of the students’ learning styles on their students’ Sentence Structure achievement. The study analyzed the students’ learning styles questionaires and their Sentence Structure test. It was found that students’ learning styles do not significantly affect their Sentence Structure achievement. It is concluded that although each student has his / her own characteristics that lead them into their own learning styles, they also have their own learning strategies, which facilitate learning task that help them to be a better language learner.
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The effect of explicit, implicit instructions and learning styles on students’ Sentence Structure achievement
2010Co-Authors: Marisi DeboraAbstract:The objectives of this study are to investigate whether Explicit Instruction and Implicit Instructions techniques significantly affect the students’ Sentence Structure achievement, to find out whether the students’ learning styles affect students’ Sentence Structure achievement and to find out whether there is an interaction between explicit and Implicit instructions and learning styles to students’ Sentence Structure achievement. An experimental research with factorial design 2x2 was used in this research. There were 120 students from 2008 Academic year of English Department State University of Medan taken as sample of this research. The post test was given to both groups. The data were analyzed by applying Two-Way ANOVA. The result of testing the first hypothesis showed that that explicit and Implicit instructions significantly affect students’ Sentence Structure achievement. The result of the testing the second hypothesis showed that students’ learning style do not significantly affect students’ Sentence Structure achievement. The result of the testing the third hypothesis showed that there is interaction between instructions techniques and learning styles on students’ Sentence Structure achievement. After the Scheffe test was applied, it showed that students who have Field Independent learning style got higher result if they were taught by Explicit instruction and students who have Field Dependent learning style got higher result if they were taught by Implicit instruction. Key Words: explicit instruction; implicit instruction; learning styles
Zhengyu Zhu - One of the best experts on this subject based on the ideXlab platform.
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a deceptive detection model based on topic sentiment and Sentence Structure information
Applied Intelligence, 2020Co-Authors: Ruiqi Zhu, Fuqiang Zhao, Fangzhou Zhao, Ping Han, Zhengyu ZhuAbstract:Deceptive reviews on Web are a common phenomenon and how to detect them has a very important impact on products, services, and even business policies. In order to filter out deceptive reviews more accurately, a new model called Sentence Joint Topic Sentiment Model (SJTSM) is presented in this paper, which incorporates the Sentence Structure of reviews and the sentiment label information of words based on Latent Dirichlet Allocation (LDA) model to extract the review features. The proposed model employs Gibbs algorithm to estimate the maximum likelihood parameters and takes the vector of topic-sentiment distribution as the review features. Then a voting system of multiple-classifier, which takes the extracted review feature vector as its input is designed to realize the classification of deceptive review detection. The comparative experiments on different public datasets with other existing methods based on LDA model show that the new classifying system based on SJTSM model can achieve more satisfying classification results on deceptive review detection.
Chi Yu-huan - One of the best experts on this subject based on the ideXlab platform.
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Automatic Machine Translation Evaluation Based on Sentence Structure Information
2009 International Conference on Asian Language Processing, 2009Co-Authors: Zhang Quan, Miao Jian-ming, Chi Yu-huanAbstract:Automatic evaluation of machine translation plays an important role in improving the performance of machine translation systems. In this paper, we firstly introduce three traditional methods of automatic evaluation, including BLEU, NIST and WER. All these methods are based on surface layer information of translations like vocabularies, so we do some studies on the evaluation method using the information of Sentence Structure. Because the Hierarchical Network of Concepts (HNC) theory thinks that Sentence category and format transformations are two most important links in machine translation, we do some researches about Sentence category and format transformations, and get the Sentence Structure information which is composed of Sentence category information and format information of every Sentence in the bilingual (Chinese and English) translation corpora. Then, considering the traditional methods above, we propose the method of automatic evaluation based on the information of Sentence Structure and have proved it effective by experiment.
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IALP - Automatic Machine Translation Evaluation Based on Sentence Structure Information
2009 International Conference on Asian Language Processing, 2009Co-Authors: Zang Han-fen, Zhang Quan, Miao Jian-ming, Chi Yu-huanAbstract:Automatic evaluation of machine translation plays an important role in improving the performance of machine translation systems. In this paper, we firstly introduce three traditional methods of automatic evaluation, including BLEU, NIST and WER. All these methods are based on surface layer information of translations like vocabularies, so we do some studies on the evaluation method using the information of Sentence Structure. Because the Hierarchical Network of Concepts (HNC) theory thinks that Sentence category and format transformations are two most important links in machine translation, we do some researches about Sentence category and format transformations, and get the Sentence Structure information which is composed of Sentence category information and format information of every Sentence in the bilingual (Chinese and English) translation corpora. Then, considering the traditional methods above, we propose the method of automatic evaluation based on the information of Sentence Structure and have proved it effective by experiment.
Catherine Blake - One of the best experts on this subject based on the ideXlab platform.
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the role of Sentence Structure in recognizing textual entailment
Meeting of the Association for Computational Linguistics, 2007Co-Authors: Catherine BlakeAbstract:Recent research suggests that Sentence Structure can improve the accuracy of recognizing textual entailments and paraphrasing. Although background knowledge such as gazetteers, WordNet and custom built knowledge bases are also likely to improve performance, our goal in this paper is to characterize the syntactic features alone that aid in accurate entailment prediction. We describe candidate features, the role of machine learning, and two final decision rules. These rules resulted in an accuracy of 60.50 and 65.87% and average precision of 58.97 and 60.96% in RTE3Test and suggest that Sentence Structure alone can improve entailment accuracy by 9.25 to 14.62% over the baseline majority class.
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ACL-PASCAL@ACL - The Role of Sentence Structure in Recognizing Textual Entailment
Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing - RTE '07, 2007Co-Authors: Catherine BlakeAbstract:Recent research suggests that Sentence Structure can improve the accuracy of recognizing textual entailments and paraphrasing. Although background knowledge such as gazetteers, WordNet and custom built knowledge bases are also likely to improve performance, our goal in this paper is to characterize the syntactic features alone that aid in accurate entailment prediction. We describe candidate features, the role of machine learning, and two final decision rules. These rules resulted in an accuracy of 60.50 and 65.87% and average precision of 58.97 and 60.96% in RTE3Test and suggest that Sentence Structure alone can improve entailment accuracy by 9.25 to 14.62% over the baseline majority class.
Wu Han-ping - One of the best experts on this subject based on the ideXlab platform.
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An Analysis of the Negative Transfer of Sentence Structure of Mother Tongue in Chinese Students’ English Writing
Journal of Wuhan Textile S.n.T. Institute, 2005Co-Authors: Wu Han-pingAbstract:There commonly exists a phenomenon of negative transfer of Chinese Sentence Structure in our students’ English writing,which greatly impedes the improvement of the students’ writing competence.An attempt is made to analyze the phenomenon and probe into its causes through the comparison between English and Chinese Sentence Structure.
