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关键词： 专业实体识别   RoBERTa-wwm   专家研究领域   计算机科学  

摘要： 为获取科研学术论文中涉及的专家研究领域等专业实体信息,给学术论文或科技项目评审专家的推荐提供理论参考,面向计算机科学领域,提出了一种基于RoBERTa-wwm的实体识别模型对专家学术论文中包含的专业实体进行识别。首先,以已有的专家基本信息数据表为参照,利用中国知网高级检索功能和爬虫技术获取表中列举专家的学术论文摘要数据;接着,将摘要数据经人工标注后,通过RoBERTa-wwm预训练模型获取具有语义特征的字符向量作为下游模型的输入;最后,将上游的语义字符向量输入BiLSTM-CRF模型中实现对文本中的专业实体识别。通过实验验证,提出的模型在自主标注的数据集中取得了更好的效果。其中,模型F1值达到了89.94%,高于实验中的对比模型,具有良好的识别专业实体的能力。

关键词： Correlation   Task analysis   Convolutional neural networks   Computer science   Trajectory   Predictive models   Encoding   Flow prediction   graph convolutional networks (GCNs)   mobile data analysis   urban computing  

摘要： Predicting urban crowd patterns/flows is a challenging task due to complex spatial-temporal (ST) dependencies. In this article, we aim to examine and report the capability and effectiveness of the current most widely used graph convolutional networks (GCNs) on mobile data analysis in ST networks for crowd flow forecasting. Specifically, we propose a novel dual-stream framework leveraging multigraph with attentive ST networks (MG-ASTN) to simultaneously predict crowd in-out flow and origin-destination (OD) flow based on the trajectory data collected by on-board devices (e.g., GPS). MG-ASTN utilizes multi-GCNs encoding non-Euclidean correlations to explore pairwise relationships among regions. In addition, we further apply a cross-channel attention mechanism with 3-D temporal convolutional network to address the heterogeneity of ST features and capture more meaningful data representations for multitask learning. In the evaluation, we conduct experiments based on two real-world data sets and verify most well-known state-of-the-art methods for crowd flow prediction. The results demonstrate that MG-ASTN could outperform other solutions-in-out flow prediction with lowest RMSE and MAE, and OD flow prediction beyond others in most cases, thus it has great potential in modeling the complex correlations among regions in ST networks and enabling accurate prediction in urban computing.

关键词： 中国计算机科技   杰出人才   群体特征   学科发展   计量研究  

摘要： 以510位中国计算机科技领域杰出人才为研究对象,采用CV分析法和SPSS数理统计软件对该群体的性别比例、年龄结构、受教育经历、出生地域、工作单位等基本情况和研究领域的学科分布特征进行计量研究,得出该群体杰出女性人才占比少,整体年龄结构较好,自主培养率较高,毕业院校集聚性强等人才结构特征,通过重视女性和中青年计算机科技人才的培养,协调地域集聚性和人才流动性之间的张力,构筑全面均衡发展的高质量计算机学科体系等路径,实现中国计算机科技事业的兴盛和“网络强国”“数字中国”的建设。

关键词： 新工科   OBE   计算机   材料科学   育人模式  

摘要： 针对计算机在材料科学中的应用课程教学中虚拟仿真缺乏实验验证及计算机在材料成形检测中教学内容无实践环节的现状,考虑信息技术在材料科学和教学中的应用,以培养掌握计算机技术在材料科学中应用的具有社会主义核心价值观的民航特色人才为主线,以培养学生的基础理论和实践能力为重点,基于OBE理念对教学内容进行更新及分模块重构,通过开展课程思政与思想政治课协同、线上与线下协同、虚拟仿真与实验验证协同、大作业与竞赛及毕业设计协同、终结性考核与形成性考核协同教学,构建了“一条主线、两个重点、五个协同”的课程育人模式,取得了一定效果。

关键词： 学生思维   初中英语   读写结合   实践  

摘要： 在学生思维能力培养导向下,如何结合信息加工理论,开展初中英语读写结合教学活动,引导学生参与语言输入和输出活动,培养其良好的思维品质,成为教师需要思考的重要问题。文章阐述初中英语读写结合教学中培养学生思维的重要性,从读写重视程度、读写分离现象、读写教学质量入手,分析初中英语读写结合教学中存在的问题,并以人教版英语教材八年级上册Unit 6 Section B为例,围绕借助主题情境支架、设计读写问题支架、搭建写作范例支架、构建学生向导支架、设计观察点评支架五个维度,探讨英语读写结合教学实践策略,以培养学生的思维能力与思维品质。

关键词： Nearest neighbor methods   Data structures   Navigation   Runtime   Approximation algorithms   Computer science   Computed tomography   Cover tree   data mining   machine learing   data structure and algorithms  

摘要： The cover tree (CT) and its improved version are hierarchical data structures that simplified navigating nets while maintaining good runtime guarantees. They can perform nearest neighbor search in logarithmic time and provide efficient computation in practice. In this article, we revisit cover trees for nearest neighbor search, and propose a more competitive method. The central idea of our method is to fully exploit the unused distance and direction information. More specially, our method introduces three novel concepts/techniques: (i) range list, (ii) quadrant information, and (iii) vectorial angle cosine. These techniques are seamlessly integrated into our suggested data structure and search algorithms. As an extra bonus, we explore approximate nearest neighbor and k nearest neighbor based on the proposed techniques, and present algorithms for handling updates. Extensive experimental results, based on both real and synthetic datasets, consistently demonstrate that our method is attractive and competitive, compared against existing cover tree structures for nearest neighbor search and its variants.

摘要： In an era where Computer Science plays a transformative role in society, the need to address Diversity, Equity, and Inclusion within the field has become increasingly imperative. Using a data-driven approach, this work shows how Women and Black students, as a percentage of total completions of CS related programs, are decreasing in recent years. This trend is particularly alarming in the Southeast region of the United States.

摘要： Our research explores perceptions related to writing in the computer science discipline. It is a common misconception that this skill is not important in the field, and we are motivated to dispel that notion and assist students in gaining experience and confidence in their disciplinary writing skills. To that end, we surveyed undergraduate students at the start and end of term in our Artificial Intelligence course, an advanced computer science elective. Students wrote two blogs-like items, one each for audiences with and without technical knowledge of the field, and also produced technical documentation related to two programming assignments. We found that on average, students agreed that writing in the discipline is important, and that they have some confidence in their writing abilities across audiences. While we did not find a statistically significant difference between perceptions at the start and end of the term, our overall results and open-ended feedback indicate that students find writing in the field to be important, and that there is strong interest in further curricular enhancements in this area.