基于Hessian半监督特征选择的网络图像标注

针对半监督特征选择算法进行了研究,采用有标签图像和无标签图像的半监督特征选择方法来提升网络图像标注的性能。基于二阶Hessian能提出一个新的半监督特征选择方法,该方法具有更好的局部拓扑结构保持特性和推断能力,从而能够克服基于图拉普拉斯半监督学习方法的缺点。将所提出的半监督特征选择算法应用到网络图像标注任务中,在两个大规模网络图像数据库上进行了实验,结果表明Hessian半监督特征选择方法优于拉普拉斯半监督特征选择方法,适合大规模网络图像标注。     

服务器日志挖掘在电力业务系统功能推荐中的应用

提出了一种基于服务器日志挖掘的电力业务系统功能推荐服务,首先从电力业务系统服务器日志中获取用户日志数据,然后对含有"脏"数据的用户日志数据进行预处理,以适应数据挖掘与处理;接着由待处理的数据计算用户访问兴趣度,并基于改进的K均值聚类算法将用户访问兴趣度数据集划分为多个具有相近兴趣度的用户集合,最终为用户提供功能个性化推荐服务.实验结果证明该方法在实现电力业务系统信息推荐方面具有较好的效果.     

基于Android的健康管理信息系统

随着经济的快速发展和国民生活水平的提高, 人们对健康的需求在增加, 健康领域的人群消费在逐步的提高, 如何在不断加快的生活节奏下寻求一种动态便捷、流程简单的健康管理方式也成为人们普遍关注的焦点. 本文基于开源移动终端Android平台, 设计并研发了一个能够实时展现用户的重要身体指标走势的健康管理信息系统. 该系统将具有强大计算和存储能力的云端技术与移动终端相结合, 可以让用户随时随地进行查看; 同时把用户的各种健康信息图形化、数据化, 从用户出发, 最大限度节约用户使用成本, 最终实现系统、科学而友好的健康信息管理.     

An environment for End-User Development of Web mashups

End-User Development aims to find novel ways that are suitable and intuitive for end users to create their own applications. We present a graphical environment in which users create new mashups by directly selecting interaction elements, content and functionalities from existing Web applications without requiring the intervention of expert developers. Then, users just need to exploit a copy–paste metaphor to indicate how to compose the selected interactive content and functionalities in the new mashup. The environment is enabled by a Web-based platform accessible from any browser, and is suitable for users without particular programming skills. We describe the architecture of our platform and how it works, including its intelligent support, show example applications, and report the results of first user studies.     

Web news mining in an evolving framework

Online news has become one of the major channels for Internet users to get news. News websites are daily overwhelmed with plenty of news articles. Huge amounts of online news articles are generated and updated everyday, and the processing and analysis of this large corpus of data is an important challenge. This challenge needs to be tackled by using big data techniques which process large volume of data within limited run times. Also, since we are heading into a social-media data explosion, techniques such as text mining or social network analysis need to be seriously taken into consideration.In this work we focus on one of the most common daily activities: web news reading. News websites produce thousands of articles covering a wide spectrum of topics or categories which can be considered as a big data problem. In order to extract useful information, these news articles need to be processed by using big data techniques. In this context, we present an approach for classifying huge amounts of different news articles into various categories (topic areas) based on the text content of the articles. Since these categories are constantly updated with new articles, our approach is based on Evolving Fuzzy Systems (EFS). The EFS can update in real time the model that describes a category according to the changes in the content of the corresponding articles. The novelty of the proposed system relies in the treatment of the web news articles to be used by these systems and the implementation and adjustment of them for this task. Our proposal not only classifies news articles, but it also creates human interpretable models of the different categories. This approach has been successfully tested using real on-line news.     

基于Web的网上作业系统设计与实现

按照网上作业平台系统实现目标,完成了系统功能性需求分析。对文件的数据库方式存储和文件系统方式的存储进行了比较,并分析、设计了本系统的存储结构。完成了数据库概念模型设计和数据表物理模型设计,详细给出了数据库关系图。设计并实现了基于Internet的课程网上作业子系统、个人网络硬盘子系统、课程资源库共享等子系统。该系统已经应用到日常的教学管理中,并取得了不错的效果。     

Understanding user intent on the web through interaction mining

Predicting the goals of internet users can be extremely useful in e-commerce, online entertainment, and many other internet-based applications. One of the crucial steps to achieve this is to classify internet queries based on available features, such as contextual information, keywords and their semantic relationships. Beyond these methods, in this paper we propose to mine user interaction activities to predict the intent of the user during a navigation session. However, since in practice it is necessary to use a suitable mix of all such methods, it is important to exploit all the mentioned features in order to properly classify users based on their common intents. To this end, we have performed several experiments aiming to empirically derive a suitable classifier based on the mentioned features.     

基于内容分析的网络新闻中社会网络自动抽取

本文针对网络新闻报道,提出了一种基于文本内容分析的社会网络自动抽取方法。此方法在对输入文章进行分词标注、共指消解等预处理之后,通过名词合并及主动词识别,得到存在关系的命名实体之间的关系指向和关系描述,最后通过有向图把存在关系的命名实体进行连接,形成由命名实体、实体间关系指向、实体间关系描述构成的关系网络。试验结果表明该方法对新闻中的命名实体关系抽取比较有效。     

基于Flex和SOA的防洪调度管理信息系统开发

由于体系规模、软件架构模式、系统集成技术的不同,现有的水利信息系统在应用过程中往往存在数据难以整合、功能难以共享等问题,形成所谓的“信息孤岛”。面向服务架构（SOA）具有低耦合性、跨平台、易维护和可扩充性等优点,可通过良好的接口和服务实现数据整合和功能共享,可有效克服“信息孤岛”问题。基于Flex平台和SOA架构,开发了防洪调度管理信息系统,实现了地理信息服务、水文监测数据管理、防洪调度方案比选、洪水演进模拟等功能。从系统架构、关键技术、功能界面3个方面详细论述了系统设计与实现过程,可为今后水利信息化系统建设提供借鉴和参考。