Interaction is an important standard to detect teachers＇ teaching quality and effect in college English classroom teaching and is the most eagerly expected by all English teachers. During the process of classroom tea...Interaction is an important standard to detect teachers＇ teaching quality and effect in college English classroom teaching and is the most eagerly expected by all English teachers. During the process of classroom teaching, bad interaction or failure of interaction often makes teachers frustrated. One of the major reasons is that they ask improper questions in class. The purpose of this paper focuses on the skills of raising effective questions by teachers in order to produce good interaction from students. The method to achieve this purpose is by introducing Socratic Questioning method, which is showed by teachers＇ narrative research based on the author＇s own real classroom teaching with detailed explanation. The result of the experiment shows that Socratic Questioning method is not only a good example of effective questioning but also produces sufficient interaction between teacher-to-students and students-to-students. Generally speaking, this paper expects to have contribution to the effect of interaction so as to help more college English teachers have more excellent classroom teaching.展开更多
For the complex questions of Chinese question answering system, we propose an answer extraction method with discourse structure feature combination. This method uses the relevance of questions and answers to learn to ...For the complex questions of Chinese question answering system, we propose an answer extraction method with discourse structure feature combination. This method uses the relevance of questions and answers to learn to rank the answers. Firstly, the method analyses questions to generate the query string, and then submits the query string to search engines to retrieve relevant documents. Sec- ondly, the method makes retrieved documents seg- mentation and identifies the most relevant candidate answers, in addition, it uses the rhetorical relations of rhetorical structure theory to analyze the relationship to determine the inherent relationship between para- graphs or sentences and generate the answer candi- date paragraphs or sentences. Thirdly, we construct the answer ranking model,, and extract five feature groups and adopt Ranking Support Vector Machine （SVM） algorithm to train ranking model. Finally, it re-ranks the answers with the training model and fred the optimal answers. Experiments show that the proposed method combined with discourse structure features can effectively improve the answer extrac- ting accuracy and the quality of non-factoid an- swers. The Mean Reciprocal Rank （MRR） of the an- swer extraction reaches 69.53%.展开更多
In this context,we study three different strategies to improve the time complexity of the widely used adiabatic evolution algorithms when solving a particular class of quantum search problems where both the initial an...In this context,we study three different strategies to improve the time complexity of the widely used adiabatic evolution algorithms when solving a particular class of quantum search problems where both the initial and final Hamiltonians are one-dimensional projector Hamiltonians on the corresponding ground state.After some simple analysis,we find the time complexity improvement is always accompanied by the increase of some other "complexities" that should be considered.But this just gives the implication that more feasibilities can be achieved in adiabatic evolution based quantum algorithms over the circuit model,even though the equivalence between the two has been shown.In addition,we also give a rough comparison between these different models for the speedup of the problem.展开更多
文摘Interaction is an important standard to detect teachers＇ teaching quality and effect in college English classroom teaching and is the most eagerly expected by all English teachers. During the process of classroom teaching, bad interaction or failure of interaction often makes teachers frustrated. One of the major reasons is that they ask improper questions in class. The purpose of this paper focuses on the skills of raising effective questions by teachers in order to produce good interaction from students. The method to achieve this purpose is by introducing Socratic Questioning method, which is showed by teachers＇ narrative research based on the author＇s own real classroom teaching with detailed explanation. The result of the experiment shows that Socratic Questioning method is not only a good example of effective questioning but also produces sufficient interaction between teacher-to-students and students-to-students. Generally speaking, this paper expects to have contribution to the effect of interaction so as to help more college English teachers have more excellent classroom teaching.
基金supported by the National Nature Science Foundation of China under Grants No.60863011,No.61175068,No.61100205,No.60873001the Fundamental Research Funds for the Central Universities under Grant No.2009RC0212+1 种基金the National Innovation Fund for Technology based Firms under Grant No.11C26215305905the Open Fund of Software Engineering Key Laboratory of Yunnan Province under Grant No.2011SE14
文摘For the complex questions of Chinese question answering system, we propose an answer extraction method with discourse structure feature combination. This method uses the relevance of questions and answers to learn to rank the answers. Firstly, the method analyses questions to generate the query string, and then submits the query string to search engines to retrieve relevant documents. Sec- ondly, the method makes retrieved documents seg- mentation and identifies the most relevant candidate answers, in addition, it uses the rhetorical relations of rhetorical structure theory to analyze the relationship to determine the inherent relationship between para- graphs or sentences and generate the answer candi- date paragraphs or sentences. Thirdly, we construct the answer ranking model,, and extract five feature groups and adopt Ranking Support Vector Machine （SVM） algorithm to train ranking model. Finally, it re-ranks the answers with the training model and fred the optimal answers. Experiments show that the proposed method combined with discourse structure features can effectively improve the answer extrac- ting accuracy and the quality of non-factoid an- swers. The Mean Reciprocal Rank （MRR） of the an- swer extraction reaches 69.53%.
基金supported by the National Natural Science Foundation of China (Grant No. 61173050)
文摘In this context,we study three different strategies to improve the time complexity of the widely used adiabatic evolution algorithms when solving a particular class of quantum search problems where both the initial and final Hamiltonians are one-dimensional projector Hamiltonians on the corresponding ground state.After some simple analysis,we find the time complexity improvement is always accompanied by the increase of some other "complexities" that should be considered.But this just gives the implication that more feasibilities can be achieved in adiabatic evolution based quantum algorithms over the circuit model,even though the equivalence between the two has been shown.In addition,we also give a rough comparison between these different models for the speedup of the problem.
