Modeling spatio-temporal constraints for multimedia objects

The presentation of multimedia data is not only characterized by precise temporal constraints; also spatial constraints must be taken into account. An important requirement in multimedia systems is thus the integrated modeling of spatio-temporal constraints. Moreover, it is important to devise methods for checking the consistency of the specified constraints. In this paper, we first propose a spatio-temporal object graph (STOG) model that provides an integrated and graphical representation of spatio-temporal constraints. Second, we investigate consistency conditions between spatial and temporal constraints expressed in the STOG model. Then, we present a prototype system implementing the proposed model.     

多种空间关系和时间结合的定性时空推理

空间实体之间存在多种时空关系,主要包含拓扑、方向、距离、尺寸和时间等.以往的研究工作主要集中于3种以下时空关系结合的表示和推理,而3种以上结合的研究很少.但多种时空关系之间是相互统一和相互约束的,所以,将它们全部综合起来研究是时空推理研究发展的必然趋势,也是实际应用的迫切需要.提出了采用矩形关系统一表示多种空间关系,以矩形关系变化次数表示时间的时空统一表示模型,并在此基础上,利用概念邻域图推导空间关系变化和时间变化.据此,结合矩形关系网络和路径一致性算法,提出了检验上述统一模型网络一致性的算法,并分析了算法复杂度.该研究成果提高了空间关系分析方法的准确性,减小了时间信息的冗余,对地理信息系统中空间实体间的空间关系以及时间变化的分析和查询等有一定的理论意义与应用价值.     

Ontologies for agents

An ontology is a computational model of some portion of the world. It is often captured in some form of a semantic network-a graph whose nodes are concepts or individual objects and whose arcs represent relationships or associations among the concepts. This network is augmented by properties and attributes, constraints, functions, and rules that govern the behavior of the concepts. Formally, an ontology is an agreement about a shared conceptualization, which includes frameworks for modeling domain knowledge and agreements about the representation of particular domain theories. Definitions associate the names of entities in a universe of discourse (for example, classes, relations, functions, or other objects) with human readable text describing what the names mean, and formal axioms that constrain the interpretation and well formed use of these names. For information systems, or for the Internet, ontologies can be used to organize keywords and database concepts by capturing the semantic relationships among the keywords or among the tables and fields in a database. The semantic relationships give users an abstract view of an information space for their domain of interest     

Spatio-temporal composition of video objects: representation andquerying in video database systems

A key characteristic of video data is the associated spatial and temporal semantics. It is important that a video model models the characteristics of objects and their relationships in time and space. J.F. Allen's (1983) 13 temporal relationships are often used in formulating queries that contain the temporal relationships among video frames. For the spatial relationships, most of the approaches are based on projecting objects on a two or three-dimensional coordinate system. However, very few attempts have been made formally to represent the spatio-temporal relationships of objects contained in the video data and to formulate queries with spatio-temporal constraints. The purpose of the work is to design a model representation for the specification of the spatio-temporal relationships among objects in video sequences. The model describes the spatial relationships among objects for each frame in a given video scene and the temporal relationships (for this frame) of the temporal intervals measuring the duration of these spatial relationships. It also models the temporal composition of an object, which reflects the evolution of object's spatial relationships over the subsequent frames in the video scene and in the entire video sequence. Our model representation also provides an effective and expressive way for the complete and precise specification of distances among objects in digital video. This model is a basis for the annotation of raw video     

基于状态和变化的统一时空数据模型

提出了一个基于状态和变化的统一时空数据模型SCUDM(state and change based unified spatio-temporial datamodel).时空数据库的状态是关于对象、空间和时间的三元组,时空数据库的变化就是状态的变化.按照对象域、空间域和时间域将时空数据库中的变化分别投影分解,显式地表达在对象、空间和时间上的变化.而事件是在某一时刻前后,时空实体的变化关系,在事件表达中蕴涵了空间实体之间的时间拓扑关系.SCUDM不仅支持状态和变化的表达,而且支持时间拓扑和空间拓扑的表达.     

细粒度苹果病虫害知识图谱构建研究

鉴于现有农业知识图谱对病虫害防治相关实体、关系刻画不够细致的问题,以苹果病虫害知识图谱构建为例,研究细粒度农业知识图谱的构建方法。对苹果病虫害知识的实体类型和关系种类进行细粒度定义,共划分出19种实体类别和22种实体关系,以此为基础标注并构建了苹果病虫害知识图谱数据集AppleKG。使用APD-CA模型对苹果病虫害领域命名实体进行识别,使用ED-ARE模型对实体关系进行抽取。实验结果表明,该文模型在命名实体识别和关系抽取两项子任务中的F1值分别达到了93.08%和94.73%。使用Neo4j数据库对知识图谱进行了存储和可视化,并就细粒度苹果病虫害知识图谱可以为精准病虫害信息查询、智能辅助诊断等下游任务提供底层技术支撑进行了讨论。     

Representing topological relationships for spatiotemporal objects

Several representations have been created to store topological information in normal spatial databases. Some work has also been done to represent topology for 3D objects, and such representations could be used to store topology for spatiotemporal objects. However, using 3D models has some disadvantages with regards to retrieving snapshots of the database. This paper aims at creating a spatiotemporal version of the sliced representation that supports efficient retrieval of snapshots of the past and that supports enforcing topological relationships. This paper aims to extend an earlier representation of moving objects so that it can also store and enforce some of the topological relationships between the objects. One use of such a representation is storing a changing spatial partition. As part of the effort to construct the model, an analysis of the topological relationships has been carried out to see which need to be stored explicitly and which can be computed from geometry. Both a basic time slice model and a 3D model are examined to determine how suitable they are for storing topological relationships. An extension of the time slice model is then proposed that solves some of the problems of the basic time slice model. Some algorithms for constructing the new model from snapshots of the objects along with an adjacency graph have been created. The paper also contains a short analysis on how to handle current time, as the time slice model is best at handling historical data, and on ways to speed up searches in a database in which objects of many types are connected to one another and many files therefore potentially need to be accessed.     

Hair-oriented data model for spatio-temporal data representation

Having an effective data structure regards to fast data changing is one of the most important demands in spatio-temporal data. Spatio-temporal data have special relationships in regard to spatial and temporal values. Both types of data are complex in terms of their numerous attributes and the changes exhibited over time. A data model that is able to increase the performance of data storage and inquiry responses from a spatio-temporal system is demanded. The structure of the relationships between spatio-temporal data mimics the biological structure of the hair, which has a ‘Root’ (spatial values) and a ‘Shaft’ (temporal values) and undergoes growth. This paper aims to show the mathematical formulation of a Hair-Oriented Data Model (HODM) for spatio-temporal data and to demonstrate the model's performance by measuring storage size and query response time. The experiment was conducted by using more than 178,000 records of climate change spatio-temporal data that were implemented in implemented in an object-relational database using nested tables. The data structure and operations are implemented by SQL statements that are related to the concepts of Object-Relational databases. The performances of file storage and execution query are compared using a tabular and normalized entity relationship model that engages various types of queries. The results show that HODM has a lower storage size and a faster query response time for all studied types of spatio-temporal queries. The significances of the work are elaborated by doing comparison with the generic data models. The experimental results showed that the proposed data model is easier to develop and more efficient.     

Indexing of now-relative spatio-bitemporal data

Real-world entities are inherently spatially and temporally referenced, and database applications increasingly exploit databases that record the past, present, and anticipated future locations of entities, e.g., the residences of customers obtained by the geo-coding of addresses. Indices that efficiently support queries on the spatio-temporal extents of such entities are needed. However, past indexing research has progressed in largely separate spatial and temporal streams. Adding time dimensions to spatial indices, as if time were a spatial dimension, neither supports nor exploits the special properties of time. On the other hand, temporal indices are generally not amenable to extension with spatial dimensions. This paper proposes the first efficient and versatile index for a general class of spatio-temporal data: the discretely changing spatial aspect of an object may be a point or may have an extent; both transaction time and valid time are supported, and a generalized notion of the current time, now, is accommodated for both temporal dimensions. The index is based on the R-tree and provides means of prioritizing space versus time, which enables it to adapt to spatially and temporally restrictive queries. Performance experiments are reported that evaluate pertinent aspects of the index. Edited by T. Sellis. Received: 7 December 2000 / Accepted: 1 September 2001 Published online: 18 December 2001     

基于时空图的移动对象聚集模式挖掘方法

移动对象聚集模式是指由移动对象参与的一组群体事件,通常用来预测交通系统中出现的异常现象.然而由于海量移动轨迹数据的产生,已有的研究方法难以准确、高效地挖掘特定的聚集模式.为此,提出一种基于时空图的移动对象聚集模式挖掘方法.该方法首先通过改进的空间聚类算法(DBScan)分析轨迹数据,从而获得移动对象聚类;然后,利用时空图模型代替单独存储轨迹数据的方式,用于实时观测移动对象聚类的时空变化特征.最后提出基于最大完全子图查找的聚集检索算法及其改进算法,用于查找满足时空约束的最大完全子图.基于真实大规模轨迹数据集上的实验结果表明,所提出的方法在移动对象聚集模式挖掘的准确性和高效性方面优于其他方法.     

Axiomatization of the Evolution of XML Database Schema

Database schema consists of constructs that model relationships between its entities. Changes made to the schema with time are called the schema evolution. An axiomatic model of the XML database schema is suggested that automatically maintains its integrity when basic changes are made to the schema. A classification of changes is described.     

An Event-Based Approach to Spatio-Temporal Data Modeling in Land Subdivision Systems

The spatio-temporal database for a collaborative decision making system supporting land subdivision is event-driven. Both various states of spatial objects and the events causing the objects change need to be recorded and manipulated in the database. To achieve this, the authors analyzed the characteristics of events in land subdivision process and studied how events affect the states of spatial objects. An event-based approach was proposed to develop the spatio-temporal data model for the GIS-based computer-supported collaborative work (CSCW) land subdivision system. A formal specification of event and its operators was introduced for describing the execution of events and their sequence. The spatio-overlap and time-meet constraints between parent-child parcels are proposed to represent the linkage between different states of land parcels. With this approach, events and the causal relations between events and states can be recorded and managed in the spatio-temporal database in a land subdivision system. In addition, a new way for simulating system work-flow is also suggested.     

Representing moving objects in computer-based expert systems: the overtake event example

Qualitative formalisms suited to express qualitative temporal or spatial relationships between entities, have gained wide acceptance as a useful way of abstracting from the real world. The question remains how to describe spatio-temporal concepts, such as the interaction between moving objects, adequately within a qualitative calculus and more specifically how to use this in expert systems. With this in mind, the Qualitative Trajectory Calculus (QTC) has been introduced. QTC enables comparisons between positions of objects at different time points to be made. By reducing the continuum to the qualitative values −, 0 and +, continuous movements can be described qualitatively. To illustrate the naturalness of QTC, the overtake event is studied. An overtake event is a typical example of objects moving in a particular domain and can become important, for example in the study of traffic engineering. A so-called conceptual animation is represented, being a sequence of QTC-relations, following the constraints imposed by qualitative reasoning. It is shown that different kinds of behaviour having certain common characteristics are reflected by the structure (e.g. symmetrical aspects) of the conceptual animations.     

Representing moving objects in computer-based expert systems: the overtake event example

Qualitative formalisms suited to express qualitative temporal or spatial relationships between entities, have gained wide acceptance as a useful way of abstracting from the real world. The question remains how to describe spatio-temporal concepts, such as the interaction between moving objects, adequately within a qualitative calculus and more specifically how to use this in expert systems. With this in mind, the Qualitative Trajectory Calculus (QTC) has been introduced. QTC enables comparisons between positions of objects at different time points to be made. By reducing the continuum to the qualitative values −, 0 and +, continuous movements can be described qualitatively. To illustrate the naturalness of QTC, the overtake event is studied. An overtake event is a typical example of objects moving in a particular domain and can become important, for example in the study of traffic engineering. A so-called conceptual animation is represented, being a sequence of QTC-relations, following the constraints imposed by qualitative reasoning. It is shown that different kinds of behaviour having certain common characteristics are reflected by the structure (e.g. symmetrical aspects) of the conceptual animations.     

基于多时空图卷积网络的交通流预测

交通流预测在交通管理和城市规划的应用中具有重要意义,然而现有的预测方法无法充分挖掘其潜在的复杂时空相关性,为进一步挖掘路网道路网络数据的时空特性以提高预测精度,提出一种多时空图卷积网络(multi-spatial-temporal graph convolutional network,MST-GCN)模型。首先,利用切比雪夫图卷积(ChebNet)结合门控循环单元(GRU)构建时空组件以深度挖掘节点的时空相关性;其次,分别提取周相关、日相关、邻近时间的序列数据,输入三个时空组件以深度挖掘不同时间窗口间的时间相关性;最后,将时空组件与编码器—解码器网络结构(encoder-decoder)融合组建MST-GCN模型。利用加利福尼亚州交通局(Caltrans)性能评估系统中高速公路数据集PEMS04和PEMS08进行实验,结果表明新模型的性能明显优于门控循环单元模型和最近提出的扩散卷积循环神经网络(DCRNN)、时间图卷积网络(T-GCN)、基于注意力机制的时空图卷积神经网络(ASTGCN)和时空同步图卷积网络(STSGCN)模型。     

Entity resolution for media metadata based on structural clustering

An increasing amount of media metadata are published by different organizations on the Web which leads to a fragmented dataset landscape. Identifying media metadata from disparate datasets and integrating heterogeneous datasets have many applications but also pose significant challenges. To tackle this problem, entity resolution methods are commonly used as an essential prerequisite for integrating media information from different sources and effectively foster the re-use of existing data sources. While the amount of media metadata published on the Web grows steadily, how to scale it well to large media knowledge bases while maintaining a high matching quality is a critical challenge. This article investigates the relationships between media entities. To that end, the media database is formulated as a knowledge graph with entities as nodes and the associations between related entities as edges. Thus, media entities are grouped into communities by how they share neighbors. Then, a structural clustering-based model is proposed to detect communities and discover anchor vertices as well as isolated vertices. Specifically, an initial seed set of matched anchor vertex pairs is obtained. Furthermore, an iterative propagation approach for identifying the matched entities in the whole graph is developed, where community similarity is introduced into the measure function to control the total measurement of candidate pairs. Therefore, starting with the elements of the initial seed set, the entity resolution algorithm updates the matching information over the whole network along with the neighbor relationships iteratively. Extensive experiments are conducted on real datasets to evaluate how the seed set impacts the matching process and performance. The experiment results show this model can achieve an excellent balance between accuracy and efficiency and is a clear improvement compared to state-of-the-art methods.

     

Graph-based representation for similarity retrieval of symbolic images

Image retrieval from an image database by the image objects and their spatial relationships has emerged as an important research subject in these decades. To retrieve images similar to a given query image, retrieval methods must assess the similarity degree between a database image and the query image by the extracted features with acceptable efficiency and effectiveness. This paper proposes a graph-based model SRG (spatial relation graph) to represent the semantic information of the contained objects and their spatial relationships in an image with no file annotation. In an SRG graph, the image objects are symbolized by the predefined class names as vertices and the spatial relations between object pairs are represented as arcs. The proposed model assesses the similarity degree between two images by calculating the maximum common subgraph of two corresponding SRG’s through intersection, which has quadratic time complexity owing to the characteristics of SRG. Its efficiency remains quadratic regardless of the duplication rate of the object symbols. The extended model SRG_T is also proposed, with the same time complexity, for the applications that need to consider the topological relations among objects. A synthetic symbolic image database and an existing image dataset are used in the conducted experiments to verify the performance of the proposed models. The experimental results show that the proposed models have compatible retrieval quality with remarkable efficiency improvements compared with three well-known methods LCS_Clique, SIM_R, and 2D Be-string, where LCS_Clique utilizes the number of objects in the maximum common subimage as its similarity function, SIM_R uses accumulation-based similarity function of similar object pairs, and 2D Be-string calculates the similarity of 2D patterns by the linear combination of two 1D similarities.     

MEER—An EER model enhanced with structure methods

Entity relationship (ER) schemas include cardinality constraints, that restrict the dependencies among entities within a relationship type. The cardinality constraints have direct impact on the application maintenance, since insertions or deletions of entities or relationships might affect related entities. Indeed, maintenance of a system or of a database can be strengthened to enforce consistency with respect to the cardinality constraints in a schema. Yet, once an ER schema is translated into a logical database schema, or translated within a system, the direct correlation between the cardinality constraints and maintenance transactions is lost, since the components of the ER schema might be decomposed among those of the logical database schema or the target system.In this paper, a full solution to the enforcement of cardinality constraints in EER schemas is given. We extend the enhanced ER (EER) data model with structure-based update methods that are fully defined by the cardinality constraints. The structure methods are provably terminating and cardinality faithful, i.e., they do not insert new inconsistencies and can only decrease existing ones. A refined approach towards measuring the cardinality consistency of a database is introduced. The contribution of this paper is in the automatic creation of update methods, and in building the formal basis for proving their correctness.     

统一时空电网数据模型与访问技术

在电网的地理信息系统发展过程中,存在着多种不同的文件或空间数据库格式,也产生了大量的电网时空数据.为解决数据集中或各个系统间数据交互时,面临的异构数据问题以及时空数据应用问题,特提出统一时空电网数据模型与访问技术.本文从实际应用出发,利用元数据思想及软件插件模式,从数据及访问层面解决了异构数据和时态数据的使用.通过应用证明,采用统一空间数据模型与访问技术方式,能够有效地减少数据准备、系统开发的工作量,并且可以整合利用不同数据源各自的优点.     

基于角色的时空访问控制模型

在RBAC模型基础上,提出了一种新的基于角色的时空访问控制模型（ST-RBAC）。ST-RBAC对RBAC中的用户、客体、许可、角色等要素进行了时空化,使之具备时空属性。与RBAC相比,该模型在不增加规则的前提下,通过要素之间的时空关系隐性地实现模型的时空约束。在计算和存储能力受限的移动计算、普适计算环境中,该模型可以得到应用。