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关键词： 大学生   竞赛活动   常规教学  

摘要： 随着社会对技能型人才要求越来越高,应用型本科院校越来越重视人才能力的培养,特别是实践动手能力的培养。学校通过各类技能竞赛来检验教师的常规教学能力和学生的实践能力是否达到人才培养的要求。文章主要针对大学生竞赛活动与常规教学相结合,深入分析大学生竞赛活动,积极探索技能竞赛与常规教学融合,阐述我国高等教育的现状及存在问题,探讨创新型教学方法和人才培养模式。

关键词： Task analysis   Stock markets   Bipartite graph   Image edge detection   Encoding   Investment   Computer science   Graph mining   representation learning   attributed interaction graph   node embedding  

摘要： Node embedding techniques have gained prominence since they produce continuous and low-dimensional features, which are effective for various tasks. Most existing approaches learn node embeddings by exploring the structure of networks and are mainly focused on static non-attributed graphs. However, many real-world applications, such as stock markets and public review websites, involve bipartite graphs with dynamic and attributed edges, called attributed interaction graphs. Different from conventional graph data, attributed interaction graphs involve two kinds of entities (e.g. investors/stocks and users/businesses) and edges of temporal interactions with attributes (e.g. transactions and reviews). In this paper, we study the problem of node embedding in attributed interaction graphs. Learning embeddings in interaction graphs is highly challenging due to the dynamics and heterogeneous attributes of edges. Different from conventional static graphs, in attributed interaction graphs, each edge can have totally different meanings when the interaction is at different times or associated with different attributes. To tackle the above challenges, we introduce the temporal dependency and conditional proximity, which are two fundamental characteristics of interaction graphs. Then, we propose a deep node embedding method called IGE+ (Interaction Graph Embedding+). By preserving these two characteristics, IGE+ is able to produce effective node embeddings in interaction graphs. We evaluate our proposed method and various comparing methods on four real-world datasets. The experimental results prove the effectiveness of the learned embeddings by IGE+ on both node-based and edge-based tasks.

关键词： 数据结构   课程思政   教学设计   哈夫曼编码  

摘要： 在当前高等职业教育教学改革的形势下,数据结构作为计算机类专业承上启下的核心基础课程,探索其课程思政的建设思路和教学设计,对于高职院校进行德育教育和高素质高技能人才培养具有重要的示范和辐射意义。本文首先分析计算机类课程思政的教学现状,然后以数据课程为例,对知识模块树中的哈弗曼编码进行思政教学设计,较为详细地阐述了课程思政的教学内容、教学方法和教学过程,让政治思想元素和专业课知识点技能点紧密结合,使德育教育于无形之中渗透专业教学,创新了课堂教学,提高了教育教学效果。以课程思政为导向的课堂革命,必将为高职院校的高质量发展注入新的活力和动力。

关键词： Lips   Semantics   Computer science   Adaptation models   Task analysis   Encoding   Correlation   Cross-modal retrieval   matrix tri-factorization hashing   varying hash length   semantic correlation matrix  

摘要： Hashing has recently sparked a great revolution in cross-modal retrieval because of its low storage cost and high query speed. Recent cross-modal hashing methods often learn unified or equal-length hash codes to represent the multi-modal data and make them intuitively comparable. However, such unified or equal-length hash representations could inherently sacrifice their representation scalability because the data from different modalities may not have one-to-one correspondence and could be encoded more efficiently by different hash codes of unequal lengths. To mitigate these problems, this paper exploits a related and relatively unexplored problem: encode the heterogeneous data with varying hash lengths and generalize the cross-modal retrieval in various challenging scenarios. To this end, a generalized and flexible cross-modal hashing framework, termed Matrix Tri-Factorization Hashing (MTFH), is proposed to work seamlessly in various settings including paired or unpaired multi-modal data, and equal or varying hash length encoding scenarios. More specifically, MTFH exploits an efficient objective function to flexibly learn the modality-specific hash codes with different length settings, while synchronously learning two semantic correlation matrices to semantically correlate the different hash representations for heterogeneous data comparable. As a result, the derived hash codes are more semantically meaningful for various challenging cross-modal retrieval tasks. Extensive experiments evaluated on public benchmark datasets highlight the superiority of MTFH under various retrieval scenarios and show its competitive performance with the state-of-the-arts.

关键词： Big Data   Information management   Data mining   Manuals   Cleaning   Automation   Computer science   Data wrangling   data matching   mapping generation   data transformation   data cleaning   source selection  

摘要： The process of preparing potentially large and complex data sets for further analysis or manual examination is often called data wrangling. In classical warehousing environments, the steps in such a process are carried out using Extract-Transform-Load platforms, with significant manual involvement in specifying, configuring or tuning many of them. In typical big data applications, we need to ensure that all wrangling steps, including web extraction, selection, integration and cleaning, benefit from automation wherever possible. Towards this goal, in the paper we: (i) introduce a notion of data context, which associates portions of a target schema with extensional data of types that are commonly available;(ii) define a scalable methodology to bootstrap an end-to-end data wrangling process based on data profiling;(iii) describe how data context is used to inform automation in several steps within wrangling, specifically, matching, value format transformation, data repair, and mapping generation and selection to optimise the accuracy, consistency and relevance of the result;and (iv) we evaluate the approach with real estate data and financial data, showing substantial improvements in the results of automated wrangling.

关键词： 计算机科学与技术   质量评估   人工智能   实践场域  

摘要： 大数据技术作为连接基础学科与数据科学之间的重要纽带,受到越来越多高校的关注。大数据时代计算机科学与技术专业应用型实践人才的大力培养是满足区块链技术发展、国家实施大数据战略、互联网巨头布局量子科技和人工智能时代发展对人才需求的关键举措。但在这一过程中,多数高校在课程设置、师资队伍建设、实践场域等诸多方面依然沿用传统教学方式,严重滞缓了计算机科学与技术专业应用型人才培养进程。为此,文章以大数据为研究背景,探讨了计算机科学与技术专业应用型人才培养的新型模式,并从人才培养要求、课程设置、教师队伍建设、校企合作等方面提出具体优化思路,以提升人才培养质量。

关键词： Twitter   Feature extraction   Semisupervised learning   Data models   Computer science   Location awareness   Twitter   POI   co-location judgement   semi-supervised learning  

摘要： Enabled by smartphones, social media users are increasingly going mobile. This trend fosters various location based services on social media platforms (e.g., Twitter). Many services like friends notification and community detection benefit from co-location judgement, i.e., to decide whether two Twitter users are co-located in some point-of-interest (POI). This problem is challenging due to the limited information in tweets and the lack of explicit geo-tags in tweets that can be used as labeled data. Our approach to this problem is based on a novel concept of HisRect features extracted from users' historical visits and recent tweets: The former has impacts on where a user visits in general, whereas the latter gives more hints about where a user is currently. In practice, labeled data is scarce. Therefore, we design a semi-supervised learning (SSL) framework that leverages unlabeled data to extract HisRect features. Moreover, we employ an embedding neural network layer to process HisRect features of two users, which decides co-location based on the embedding difference between the two features. Our model is extensively evaluated on two large sets of real Twitter data from more than one million users. The experimental results demonstrate that our HisRect features and SSL framework are highly effective at deciding co-locations. In terms of multiple metrics, our approach clearly outperforms alternative approaches using state-of-the-art techniques.

关键词： Wireless sensor networks   Authentication   Biometrics (access control)   Password   Protocols   Computer science   Authentication   three-factor authentication   NS-3   wireless sensor network (WSN)   proverif  

摘要： As an important topic of IoT, wireless sensor network (WSN) data transmission is popular nowadays. It is widely accepted that the wireless channel is hazard, and multifactor authentication schemes are proposed to save the hazard of wireless communication circumstance. To overcome the problems, we give a fresh three-factor authentication scheme providing session keys for WSNs. Formal verification given by Proverif illustrates that the new scheme keeps security properties. At the same time, the informal analysis also denotes that the proposed scheme is practical and satisfies general needs, such as counteraction against various attacks and meeting security properties. Compared to some recent similar schemes, the proposed scheme performs better in security and is suitable for application. At last, we use NS-3 for simulation. The results from the simulation show that the scheme can run in IoT environment normally and has practical perspective.

关键词： Gamification   game-related method   empirical study   computer science   software engineering   SQL  

摘要： Gamification, defined as the integration of game elements into non-gaming environments, is a promising approach to increase student engagement, motivation, and performance in Computer Science and Software Engineering education. This viewpoint encouraged the creation of QueryCompetition, a web system that allows students to practice SQL in a competitive environment. Our goal was to obtain empirical evidence on how gamifying elements, such as challenges, points, and leaderboards, integrated into QueryCompetition, affect student performance, motivation, and user experience. We carried out a quasi-experimental study with two groups in a Database course. One group used a gamified version of QueryCompetition having access to points and leaderboards, while the other used a non-gamified version with no access to the above mentioned elements. Quantitative and qualitative datawere collected through tests and a survey. The results showed that there was a statistically significant improvement in student performance in the gamified group as compared to the non-gamified group. In addition, a higher motivationwas observed in the gamified group. The empirical evidence presented in this article supports the claim that inclusion of challenges, points, and leaderboards, together with the competitive nature of QueryCompetition, impacts positively on student performance and motivation to practice SQL.