基于标签自适应选择的矩阵分解推荐算法

将标签融入矩阵分解方法是当前推荐系统研究的热点。提出了一种基于标签自适应选择的矩阵分解推荐算法。首先,提出了标签 评分稀疏系数,较好地平衡了推荐过程中潜在特征与标签的使用问题。其次,利用标签的次数来计算标签向量,体现了标签的不同频率对不同物品的影响。最后,给出了算法的总体描述。实验结果表明,算法具有较高的推荐精度和较快的收敛速度。     

融合用户属性信息的冷启动推荐算法

协同过滤算法广泛应用于个性化推荐系统中。现有的基于社群相似性的协同过滤算法在新用户新商品的冷启动场景中难以使用,性能较差。对此,提出了一种基于矩阵分解和神经网络映射的冷启动推荐算法。首先,使用矩阵分解方法求出用户在潜在兴趣空间的向量表示;然后,训练神经网络学习从用户属性数据到潜在兴趣向量的映射关系;最后,融合用户的历史评分数据与属性数据各自生成的兴趣向量,给出平滑的推荐预测值。实验表明,当用户的评分记录很少时,预测性能有明显提升,融合用户的属性信息能较好地改善"冷启动"情况下推荐系统的性能。     

基于改进带偏置概率矩阵分解算法的研究

针对个性化推荐过程中高维稀疏性问题,本文提出一种将奇异值分解技术和带偏置概率矩阵分解相结合的推荐方法。 首先利用SVD算法初始化用户项目潜在因子向量,避免因随机赋值而使得函数陷入局部最优解,接着将用户项目的偏置信息融入到概率矩阵分解算法中,同时为了提升训练速度和推荐精度,通过动量加速的迷你批量梯度下降（mini Batch Gradient Descent,miniBGD）来训练,最后利用分解后的两个低维矩阵对原矩阵中的未知评分进行预测,在三个公开数据集的实验结果表明,本文提出的算法相对于传统的算法能够有效的提高推荐精度,进一步缓解由数据高维稀疏性带来的推荐质量不高的问题。     

融合标签信息的卷积矩阵分解推荐算法

当今各类推荐系统中存在着冷启动、数据稀疏性的问题,严重影响其推荐质量。为了有效缓解由于数据不完整导致的推荐效果不理想,提出一种融合标签信息的卷积矩阵分解推荐算法TaSoConvMF(Convolutional Matrix factorization Recommendation Algorithm Fusing Social Tagging)。该算法将卷积神经网络融合进概率矩阵分解模型,并利用评分矩阵和标签矩阵联合监督,运用联合概率矩阵分解计算用户-资源、用户-标签、资源-标签三个矩阵的隐式向量,根据评分矩阵多次对模型参数进行优化。该算法通过在豆瓣评分数据集和MovieLens10M数据集上进行多次实验,采用RMSE指标进行评估,预测结果表明推荐效果有所提升。     

融合层次聚类和粒子群优化的鲁棒推荐算法

针对现有的推荐算法面对托攻击时鲁棒性差的情况,提出一种融合层次聚类和粒子群优化的鲁棒推荐算法.首先,根据用户评分矩阵,使用层次聚类将用户聚为两类,并根据平均类内距离进行类别判定,对攻击概貌进行标记;然后,基于矩阵分解技术,引入粒子群优化技术进行特征矩阵初始化,为模型训练提供初始最优解;最后,根据攻击概貌标识结果构造标记函数,降低对模型训练过程的影响,实现对目标用户的鲁棒推荐.在公共数据集上将本文提出的算法和其他算法进行了实验对比分析,结果显示提出的算法在鲁棒性方面有很大的提升,推荐精度也有提高.     

基于社交信任的概率矩阵因子分解推荐算法

针对评分矩阵和信任矩阵的稀疏性以及推荐精度不高等问题，提出基于社交信任的概率矩阵因子分解推荐算法PMFTrustSVD。该文采用概率矩阵分解算法对信任矩阵进行分解，分别获得用户作为信任者和被信任者的潜在社交偏好；根据用户在作为信任者或被信任者时的偏好不同，将TrustSVD算法中的无向信任矩阵修正为有向矩阵；融合两种算法来预测用户的评分矩阵。在FilmTrust数据集上实验结果表明，该算法优于现有基准算法，能有效缓解用户信任矩阵稀疏的问题并提高推荐精度。     

基于改进贝叶斯概率模型的推荐算法

针对现有基于矩阵分解的协同过滤推荐系统预测精度与推荐精度较低的问题,提出一种改进的矩阵分解方法与协同过滤推荐系统。首先,将评分矩阵分解为两个非负矩阵,并对评分做归一化处理,使其具有概率语义;然后,采用变分推理法计算贝叶斯概率模型实部后验的分布;最后,搜索相同偏好的用户分组并预测用户的偏好。此外,基于用户向量的稀疏性设计一种低计算复杂度、低存储成本的推荐结果决策算法。基于3组公开数据集的实验结果表明,本算法的预测性能以及推荐系统的效果均优于其他预测算法与推荐算法。     

基于高阶偏差的因子分解机推荐算法

在推荐系统中,因评分尺度差异而造成的偏差问题一直影响着协同过滤算法的预测准确性。其中针对矩阵因子分解算法中的偏差问题,本文提出一种基于高阶偏差的因子分解机算法。该算法首先按照评分偏差的现实特征对用户和项目进行划分,再将偏差类别作为辅助特征集成到因子分解机中,实现了评分预测中不同偏差用户、项目的高阶交互。在Movielens数据集上的实验结果表明,相比传统矩阵因子分解算法,本文提出的算法具有更低的预测误差,体现了其更好的推荐性能。     

基于LU分解和交替最小二乘法的分布式奇异值分解推荐算法

针对当前分布式潜在因子推荐算法存在时间复杂度较高、运行时间较长的问题,文中提出基于LU分解和交替最小二乘法(ALS)的分布式奇异值分解推荐算法,利用ALS利于分布式求解目标函数的特点,提出网格状分布式粒度分割策略,获取相互独立不相关的特征向量.在更新特征矩阵时,使用LU分解求逆矩阵,加快算法的运行速度.在KDD CUP 2012 Track1中的腾讯微博数据集上的实验表明,文中算法在确保一定推荐精度的前提下,大幅提升推荐速度和算法效率.     

基于LDA的隐式标签协同过滤推荐算法

固定标签协同过滤推荐算法,未充分考虑标签因子的多样化,主要依靠人工标记,扩展性不强,主观因素多。本文从用户的喜好特征因素角度出发,在固定标签协同过滤推荐算法的基础上,提出一种隐式标签协同过滤推荐算法。该算法利用LDA主题模型生成项目文本的隐式标签,得到项目-标签特征权重,根据算法性能优化的要求选择标签数量,将项目-标签矩阵与用户评分矩阵结合得到用户对标签的偏好矩阵,最后通过协同过滤算法产生推荐。实验结果表明,本文提出的基于LDA的隐式标签协同过滤推荐算法缓解了数据稀疏性问题,项目推荐的召回率、准确度和F1值有较大提升。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。