基于张量图卷积的多视图聚类

针对多视图聚类进行的数据表示学习, 通常采用浅层模型与线性函数实现数据嵌入, 该方式无法有效挖掘多种视图间丰富的数据关系. 为充分表示不同视图间的一致性信息与互补性信息, 本文提出基于张量图卷积的多视图聚类方法(TGCNMC). 该方法首先将传统的平面图拼接为张量图, 并采用张量图卷积学习各视图中数据的近邻结构; 接着利用图间卷积进行多视图间的信息传递, 从而捕获多视图数据间的协同作用, 揭示多视图数据中的一致性与互补性信息; 最后采用自监督方式进行数据聚类. 通过在标准数据集上进行的广泛实验, 聚类效果优于现有的方法, 表明该方法可以更全面的描述多视图数据、更有效地挖掘视图间的关系并具有更好的处理下游聚类任务的能力.     

基于三支决策的多视图低秩稀疏子空间聚类算法

多视图子空间聚类是一种从子空间中学习所有视图共享的统一表示, 挖掘数据潜在聚类结构的方法. 作为一种处理高维数据的聚类方法, 子空间聚类是多视图聚类领域的研究热点之一. 多视图低秩稀疏子空间聚类是一种结合了低秩表示和稀疏约束的子空间聚类方法. 该算法在构造亲和矩阵过程中, 利用低秩稀疏约束同时捕捉了数据的全局结构和局部结构, 优化了子空间聚类的性能. 三支决策是一种基于粗糙集模型的决策思想, 常被应用于聚类算法来反映聚类过程中对象与类簇之间的不确定性关系. 本文基于三支决策的思想, 设计了一种投票制度作为决策依据, 将其与多视图稀疏子空间聚类组成一个统一框架, 从而形成一种新的算法. 在多个人工数据集和真实数据集上的实验表明, 该算法可提高多视图聚类的准确性.     

IRP用户视图间依赖关系的度量

用户视图间的依赖关系对于信息资源规划中的数据分析和数据建模有着重要的意义。该文对用户视图间的依赖关系进行了定义和说明，并细分其为数据依赖和操作依赖，在此基础上，对用户视图间的依赖关系进行了度量，提出了依赖度和被依赖度2种度量方法，为规范用户视图提供了依据。     

基于正交基的多视图迁移谱聚类

挖掘多视图一致性是提升多视图聚类性能的关键,为更好地从多视图数据中学习一致性表示,提出一种新的多视图聚类算法OMTSC。OMTSC算法同时学习每个视图的聚类分配矩阵和特征嵌入,并将聚类分配矩阵分解为共享正交基矩阵和聚类编码矩阵。正交基矩阵可捕获并储存多视图一致性信息形成潜在聚类中心,经过加权融合的多视图聚类编码矩阵可更好地平衡不同视图的质量差异。引入基于二部图的协同聚类,实现正交基、聚类编码和特征嵌入3个矩阵的知识相互迁移,以提升多视图数据一致性和多样性,并利用特征嵌入的多样性最大化多视图一致性学习最优的潜在聚类中心,从而提高多视图聚类的性能。此外,基于群稀疏约束的特征嵌入可有效消除多视图数据中的噪声,提升算法的鲁棒性。在WikipediaArticles、COIL20和ORL数据集上的实验结果表明,与SC-Best、Co-Reg等先进的多视图聚类算法相比,OMTSC算法在ACC、NMI、ARI 3个评价指标上整体取得最优值,其中在COIL20和ORL数据集中的NMI评价指标均高于0.9。     

基于自适应邻域的鲁棒多视图聚类算法

针对现存的基于自适应邻域的多视图聚类算法没有考虑噪声和共识图信息损失的问题,提出一种基于自适应邻域的鲁棒多视图聚类（RMVGC）算法。首先,为了避免噪声和异常值对数据的影响,通过鲁棒主成分分析模型（RPCA）从原始数据中学习多个干净的低秩数据;其次,用自适应邻域学习直接融合多个干净的低秩数据来得到一个干净的共识关系图,从而减少图融合过程中的信息丢失。实验结果表明,所提RMVGC算法的标准化互信息（NMI）在MRSCV1、BBCSport、COIL20、ORL和UCI digits数据集上比目前流行的多视图聚类算法分别提升了5.2、1.36、27.2、4.66和5.85个百分点。同时,该算法保持了数据局部结构,增强了对原始数据的鲁棒性,提高了关系图质量,在多视图数据集上具有较好的聚类性能。     

安全数据库的推理控制

首先对按元素划分安全级的多级数据库上由函数依赖(FD)和多值函数依赖(MVD)引起的推理问题进行了研究,所提出的推理控制算法在很大程度上提高了数据的可用性.为进一步有效防范推理所导致的敏感信息泄露,给出了基于视图的推理控制方法.该方法能够处理多视图合谋带来的安全问题.最后给出了视图依赖基划分原理,它是以后有关视图推理控制的基础.     

特征直连与结构化约束的多视图子空间聚类

多视图子空间聚类作为处理多视图数据的聚类算法，其目的在于学习到一个共识的子空间后用于聚类。但是，现存的多视图子空间聚类算法只是将目标放在了原有的多个视图上，忽略了通过特征直连得到的数据。提出的FSMC算法使原有的多个视图与特征直连视图相互学习，通过误差重构和结构化约束子空间得到一个更加合适的子空间表示，同时还考虑了多视图与特征直连视图的权重关系。最后，在4个基准数据集上进行实验，验证了算法的有效性。     

改进的自步深度不完备多视图聚类

随着数据量的增大,多视图聚类中出现带有缺失视图数据的情况愈发常见,此问题被称为不完备多视图聚类,而引入深度模型进行聚类通常可以获得比浅层模型更为出色的表现。本文提出一种新颖的深度不完备多视图聚类模型,称为改进的自步深度不完备多视图聚类。在该模型中,充分考虑多视图数据之间的互补性,利用基于多视图特性的最近邻填充方案将缺失视图补全。使用多个自编码器分别获取多个视图数据的低维潜在特征,同时引入图嵌入策略保持潜在特征之间的几何结构。运用一致性原则将来自不同的视图潜在特征融合以获得一致潜在特征,在此基础上运用自步学习的方法来增强聚类效果。实验结果表明,对比现有的不完备多视图聚类模型,本文模型可以更加灵活且高效地应对各种不完备多视图聚类情况,提升了不完备多视图聚类的鲁棒性与表现效果。     

生成式不完整多视图数据聚类

基于自表示子空间聚类的多视图聚类引起越来越多的关注. 大多数现有算法假设每个样本的所有视图都可获得, 然而在实际应用中, 由于各种因素, 可能会导致某些视图缺失. 为了对视图不完整数据进行聚类, 本文提出了一种在统一框架下同时执行缺失视图补全和多视图子空间聚类的方法. 具体地, 缺失视图是由已观测视图数据约束的隐表示生成的. 此外, 多秩张量应用于挖掘不同视图之间的高阶相关性. 这样通过隐表示和高阶张量同时挖掘了不同视图以及所有样本(即使是不完整视图样本)之间的相关性. 本文使用增广拉格朗日交替方向最小化(AL-ADM)方法求解优化问题. 在真实数据集上的实验结果表明, 我们的方法优于最新的多视图聚类算法, 具有更好的聚类准确度和鲁棒性.     

一种改进的多视图K-均值聚类算法

近几年来,随着互联网的发展以及大数据时代的来临,具有多种表示即多视图数据越来越多,如何将传统的单一表示的数据聚类方法应用在多视图数据被广泛研究。其中传统的K-均值聚类算法因为有效性以及对于大数据的高效性而被扩展到了多视图数据领域,本文针对最近提出的一个新的多视图K-均值聚类方法,结合co-training的思想,提出了一个改进的多视图K-均值聚类算法,并在三个标准数据集上进行了实验,同时和已有的一些方法进行了比较,结果表明了算法的有效性。     

Accumulator-based inexact matching using relational summaries

We are building a system that can rapidly determine the pose of a known object in an unknown view using a view class model of the object. The system inputs a three-dimensional CAD model; converts it to a three-dimensional vision model that contains the surfaces, edges, vertices, and topology of the object; and uses the vision model to determine the view classes or representative views of the object. In this paper we define therelational pyramid structure for describing the features in a particular view or view class of an object and thesummary structure that is used to summarize the relational information in the relational pyramid. We then describe an accumulator-based method for rapidly determining the view class(es) that best match an unknown view of an object.This research was partially supported by the National Aeronatics and Space Administration (NASA) through a subcontract from Machine Vision International.     

View creation for queries in object oriented databases

A view in object oriented databases corresponds to virtual schema with restructured generalization and decomposition hierarchies,Numbers of view creation methodologies have been proposed.A major drawback of existing methodologies is that they do not maintain the closure property.That is,the result of a query does not have the same semantics as embodied in the object oriented data model.Teherefore,this paper presents a view creation methodology that derives a class in response to a user‘s query,integrates derived class in global schema (i.e., considers the problem of classes moving in class hierarchy)and selects the required classes from global schema to create the view for user‘s query.Novel idea of view creation includes:(a) an object algebra for class derivation and customization(where the derived classes in terms of object instances and procedure/methods are studied),(b)maintenance of closure property,and (c)classification algorithm which provides mechanism to deal with the problem of a class moving in a class hierarchy.     

View specification and manipulation for a semantic data model

Semantic data models are increasing in popularity and use, but they are also becoming increasingly complex and difficult to manage. In this paper we extend the definition of a semantic data model to give users the power to specify and manipulate views. Our model supports both high-level object-class views and high-level relationship-set views. To define these views, we extend the traditional method of view definition (through query formulation) to also include view definition by a dominant object class, by an independent object class, and by a relational object class. A set of operators to specify and manipulate views is also defined. These operators allow a user to create and destroy views, implode and explode views, hide and expose semantic-model elements. We also provide algorithms to extract an instance graph for a high-level object in a semantic-model view and to transform a semantic-model view hierarchy into an equivalent atomic model. Implications and applications of views in our model are also discussed.     

OODB延迟视图维护模型

针对面向对象数据库中视图的特点，提出了一个延迟视图维护的模型以及相关的更新算法，在视图更新时，要考虑导出它的类的改动，以有以此类为根的继承和类组成子层次结构中的所有类的改动，因此，为每个类添加一个修改列表，为依赖于它的视图保存修改信息。     

Learning to generate novel views of objects for class recognition

Multi-view object class recognition can be achieved using existing approaches for single-view object class recognition, by treating different views as entirely independent classes. This strategy requires a large amount of training data for many viewpoints, which can be costly to obtain. We describe a method for constructing a weak three-dimensional model from as few as two views of an object of the target class, and using that model to transform images of objects from one view to several other views, effectively multiplying their value for class recognition. Our approach can be coupled with any 2D image-based recognition system. We show that automatically transformed images dramatically decrease the data requirements for multi-view object class recognition.     

Recognition by prototypes

A scheme for recognizing 3D objects from single 2D images under orthographic projection is introduced. The scheme proceeds in two stages. In the first stage, the categorization stage, the image is compared to prototype objects. For each prototype, the view that most resembles the image is recovered, and, if the view is found to be similar to the image, the class identity of the object is determined. In the second stage, the identification stage, the observed object is compared to the individual models of its class, where classes are expected to contain objects with relatively similar shapes. For each model, a view that matches the image is sought. If such a view is found, the object's specific identity is determined. The advantage of categorizing the object before it is identified is twofold. First, the image is compared to a smaller number of models, since only models that belong to the object's class need to be considered. Second, the cost of comparing the image to each model in a class is very low, because correspondence is computed once for the whole class. More specifically, the correspondence and object pose computed in the categorization stage to align the prototype with the image are reused in the identification stage to align the individual models with the image. As a result, identification is reduced to a series of simple template comparisons. The paper concludes with an algorithm for constructing optimal prototypes for classes of objects.     

Extending the ODMG standard with views

Views are an important functionality provided by the relational database systems. However, commercial object-oriented database systems do not support a view mechanism because defining the semantics of views in the context of an object-oriented model is more difficult than in the relational model. Indeed, views are not included in the ODMG standard. In this paper, we present a proposal aimed at including views in the ODMG, by extending the object model and the object definition language (ODL). We consider object-oriented views as having the same functionality as relational views. Views are included in the object model in such a way that (i) views make a new kind of data type definition, just as are classes, interfaces and literals, (ii) an IS-VIEW relationship is introduced in order to specify the derivation of a view from its base class, and (iii) a view instance preserves the identity of its base instance. A view can import attributes, relationships and operations from its base class, and it can also add new operations, derived attributes and derived relationships. The extent of the view is defined by an object query language (OQL) predicate. We also describe a C++ binding showing the practicability of the proposed model.     

面向对象交互式图形系统的层次模型

本文从面向对象的观点出发，通过动态地建立聚合对象，讨论了面向对象的交互式图形系统的层次模型。首次提出将交互式图形系统中各种图形对象类划分为基本图元类，静态聚合对象类和动态聚合对象类的分类方法。     

面向对象的语义关联数据模型理论

本文提出了“面向对象的语义关联数据模型(CIM-OSA DM)”理论,在扼要介绍CIM-OSA DM的基础上,侧重于形式化地定义“对象”、“对象类”及类之间的“语义关联”,按照“对象”和“对象类”统一的观点,又进一步形式化地定义了“对象相等”、“对象类相等”、“子对象类关系”以及“子对象关系”,并采用严格的数学证明论证了它们具有的重要性质,最后提出“对象代数”并形式化地定义对象可执行的几种代数运算。     

面向对象类型理论的比较研究

人们已提出各种支持面向对象程序设计的类型理论。但每种类型理论的侧重点不足相同，它们均能解决面向对象程序设计的某些方面的问题。本文从对象、类、类型和继承角度，着重分析讨论抽象数据类型、记录演算和对象演算，为进一步研究关于面向对象程序设计的类型理论提供基础。