A Study on Short Text Matching Method Based on KS-BERT Algorithm

To improve the accuracy of short text matching,a short text matching method with knowledge and structure enhancement for BERT(KS-BERT)was proposed in this study.This method first introduced external knowledge to the input text,and then sent the expanded text to both the context encoder BERT and the structure encoder GAT to capture the contextual relationship features and structural features of the input text.Finally,the match was determined based on the fusion result of the two features.Experiment results based on the public datasets BQ_corpus and LCQMC showed that KS-BERT outperforms advanced models such as ERNIE 2.0.This Study showed that knowledge enhancement and structure enhancement are two effective ways to improve BERT in short text matching.In BQ_corpus,ACC was improved by 0.2%and 0.3%,respectively,while in LCQMC,ACC was improved by 0.4%and 0.9%,respectively.

创设问题情境激励学生发现问题

哈佛有句名言:教育的真正目的就是让人不断地提出问题,思索问题。这也是目前我们在课程改革中所要体现的重点教育教学理念。在音乐教学实践中,很多学生总觉得在课堂上没有问题可提,只是盲从地、被动地接受教师的引导,顺着教师引导的思路去回答一些问题。而放开手。

让知识和能力在课堂教学中自然生成

在课堂教学中,要提高课堂教学效率就不能刻意地去追求理想的手段和方法,不能凭外在的想象,而要遵从学生发展的自然规律。正如亚里士多德所说:"在教育儿童时,我们当然应该先把功夫用在他们的习惯方面,然后再及于理性方面"。也就是说,在课堂教学中,

A survey of deep learning-based visual question answering

With the warming up and continuous development of machine learning,especially deep learning,the research on visual question answering field has made significant progress,with important theoretical research significance and practical application value.Therefore,it is necessary to summarize the current research and provide some reference for researchers in this field.This article conducted a detailed and in-depth analysis and summarized of relevant research and typical methods of visual question answering field.First,relevant background knowledge about VQA(Visual Question Answering)was introduced.Secondly,the issues and challenges of visual question answering were discussed,and at the same time,some promising discussion on the particular methodologies was given.Thirdly,the key sub-problems affecting visual question answering were summarized and analyzed.Then,the current commonly used data sets and evaluation indicators were summarized.Next,in view of the popular algorithms and models in VQA research,comparison of the algorithms and models was summarized and listed.Finally,the future development trend and conclusion of visual question answering were prospected.

On Constructing the Cognitive Model of Knowledge Acquisition in Globalization-Oriented Study

This paper which is directed to constructing the cognitive model of knowledge acquisition in view of the increasing need of globalization-oriented study, points out features of globalization-oriented study, and proposes the importance and necessity for constructing the CMKAGS （cognitive model of knowledge acquisition in globalization-oriented study） which includes attention, background knowledge, and chunking memory that involves semantic chunking, information encoding as well as choice of information encoding. The cognitive model of knowledge acquisition in question aims at helping e-learners to memorize their learned knowledge and improve their studies effectively and efficiently, whether they study in enhanced conditions or in natural conditions

An Effective Reading Process： The Application of Annotation to English as a Foreign Language Reading

In this study, the author investigated insights of 15 college students majored in English as they explored their own use of annotation strategy and how they applied this strategy in effective reading process. As an action research, the report is an attempt to explore the role played by annotation in reading comprehension in English as a Foreign Language （EFL） classrooms. By means of learner diaries, the researcher found that annotation, as an efficient writing-to-learn strategy, is able to help EFL learners to research a deeper level of engagement and to encourage active reading. The findings also suggest that reading strategy training can be integrated with reading tasks in the EFL classrooms.

Review of Effects of Glosses on Incidental Vocabulary Learning and Reading Comprehension

词汇学习是语言学习的基础。Hunt and Beglar(1998)将能促进词汇学习的方法分为三种:附带学习、直接学习和独立策略学习。三种方法中,词汇附带学习被认为是二语词汇习得的一个基本的部分。许多研究证明了注释对词汇附带学习和阅读理解的有效性。本文总结并分析了近年来有关注释对词汇附带习得和阅读理解的研究成果,并指出了其中的不足,提出了未来研究的方向。

A deep-learning method for evaluating shaft resistance of the cast-in-site pile on reclaimed ground using field data

This study proposes a deep learning-based approach for shaft resistance evaluation of cast-in-site piles on reclaimed ground,independent of theoretical hypotheses and engineering experience.A series of field tests was first performed to investigate the characteristics of the shaft resistance of cast-in-site piles on reclaimed ground.Then,an intelligent approach based on the long short term memory deep-learning technique was proposed to calculate the shaft resistance of the cast-in-site pile.The proposed method allows accurate estimation of the shaft resistance of cast-in-site piles,not only under the ultimate load but also under the working load.Comparisons with empirical methods confirmed the effectiveness of the proposed method for the shaft resistance estimation of cast-in-site piles on reclaimed ground in offshore areas.

Attention-based encoder-decoder model for answer selection in question answering

One of the key challenges for question answering is to bridge the lexical gap between questions and answers because there may not be any matching word between them. Machine translation models have been shown to boost the performance of solving the lexical gap problem between question-answer pairs. In this paper, we introduce an attention-based deep learning model to address the answer selection task for question answering. The proposed model employs a bidirectional long short-term memory （LSTM） encoder-decoder, which has been demonstrated to be effective on machine translation tasks to bridge the lexical gap between questions and answers. Our model also uses a step attention mechanism which allows the question to focus on a certain part of the candidate answer. Finally, we evaluate our model using a benchmark dataset and the results show that our approach outperforms the existing approaches. Integrating our model significantly improves the performance of our question answering system in the TREC 2015 LiveQA task.

Scaffolding Students’ Self-Assessment of Their English Essays with Annotated Samples: A Mixed-Methods Study

This paper aims to investigate the effectiveness of rubric-referenced student self-assessment(SSA)on students’English essay writing by employing a two-group pre-post-quasi-experimental research design.The method was tested on 54 students at a Chinese university.During a 17-week experiment,the experimental group(EG)received the rubric and annotated samples,while the comparison group(CG)received only the rubric in self-assessment.Data sources included students’scores in the pre-test and post-test and interviews.Quantitative findings indicated that the EG made significantly stronger progress than the CG in the post-test.Interview results suggested that annotation-based rubric-referenced SSA can help students understand the task requirements,initiate their self-regulatory behaviors,and improve their self-assessment confidence,although students still wanted to receive assistance from teachers partly due to the Confucian-heritage culture settings in China.The findings are discussed in terms of the design features of sample annotations within the framework of self-regulated learning(SRL),as well as the implications of using this method in the classroom.

An Empirical Study of the Influence of Attention Strategy Training on Second Language Vocabulary Acquisition

This paper presents the results of a 14-week attention strategy training of 174 college freshmen. It illustrates the promoting function of attention in second language vocabulary acquisition by raising students＇ expectations for new words, by increasing the frequency of exposure to them, by enhancing their perceptual salience, and by increasing the task demand for word study. The results show that enhancing attention in input could promote students＇ vocabulary acquisition and help them form vocabulary learning strategy suitable for their levels of proficiency.