Reasoning on Class Relations: An Overview

The facilitation of interoperability requires a clear distinction if a relation refers to classes of individuals or to specific instances, in particular when it comes to the logical properties of the involved relations. Class relations are defined whenever the semantics of entire classes are described, independently of single instances. Typical examples are spatial semantic integrity constraints or ontologies of entity classes. The paper continues research on spatial class relations by deepening the analysis of the reasoning properties of class relations. The work is based on a set of 17 abstract class relations defined in [11]. The paper provides a complete composition table for the 17 abstract class relations and redefines the concept of conceptual neighbourhood for class relations. This approach can be used to find conflicts and redundancies in sets of semantic integrity constraints or other applications of spatial class relations.

A model and a language for specifying spatial integrity constraints in pictorial databases are presented. Spatial integrity constraints are assertions about the correct behavior of database systems that specify acceptable database states and state transitions. They also serve as restrictions on positions occupied by objects in a picture. The language presented primarily uses pictures to specify constraints. The constraint pictures depict unacceptable database states. A data model provides the basic semantics for picture interpretation.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

This paper intends to classify, review, and compare the existing languages for the specification of spatial integrity constraints at the conceptual level. We classify these languages into natural, visual, first-order logic, and hybrid and review their syntax and semantics. We compare these language categories based on expressiveness and pragmatics qualities. The results of this study show that controlled natural languages and natural hybrid languages with pictograms are good candidates for expressing spatial integrity constraints at the conceptual level of spatial databases. At the end, we identify new research challenges that should be addressed in this domain in order to facilitate spatial integrity constraint specification and representation.

Directional relations, topological relations and metric relations are the basic spatial constraint in the geometric space. The three kinds of spatial relations are not isolated and restrict each other. In this paper, we focus on the effect of topology and distance on the representation of directional relations and present a description mechanism of directional relations considering topology and distance. In this new model, (1)topological constraint is analyzed as the basis of directional relations categories; (2)distance relations is the other factor of representation of directional relations and distinguish the directional relations of different positions in the same ray line; (3)depending on the analysis of the capability of exiting directional relations models to represent the restraint from the topological relations and distance, a category mechanism based on the topological relations and distance is proposed to improve the accuracy of the directional description. This model combines the restraint from topological and distance relations and consummates the representation of directional relations. Experiments show excellent efficiency in view of directional description.

In this paper Semantic-Enhanced Entity Relationship (SEER) and Semantic – Relational Database (SRD) diagrams are proposed. SEER and SRD are extensions of Enhanced Entity Relationship (EER) and Relational Database (RD) diagrams respectively that are based on dealing with Semantic Integrity Constraints. EER and RD do not take semantic constraints in matter. A lots of information are lost because of the shortage of documentations. The proposed SEER and SRD models embed the semantic constraints using a new notations and pseudo code to give a full diagram for a database system. The proposed models handle the documentation shortage problem.

In the domain of GIS, large amounts of geographic data are increasingly shared, interchanged and analyzed in many different applications. Mobile GIS technologies bring lots of advantages for field survey and the datasets acquired by field based data collection in Mobile GIS are often employed for many purposes. Therefore, to ensure the quality of the collected datasets and tell the data users information about how reliable the datasets are, more concerns have to be contributed to spatial data quality issues. This paper will describe the open architecture of field based Mobile GIS and show the importance of spatial data quality issues. Then it explains how the spatial data quality concerns are considered for Mobile GIS aligning with international standards in geoinformatics, like ISO and OGC standards. Geographic data modeling with emphasis of spatial integrity constraints will be introduced here. In order that field users can simultaneously receive the warning of errors when they are entering the data in the field and correct them through seeing the reality, the data quality assurance work should be seamlessly integrated into the Mobile GIS. Therewith, the method of applying the spatial integrity constraints into the data collection work will also be explained.

This paper reviews the key features of an environment to support domain users in spatial information system (SIS) development. It presents a full design and prototype implementation of a repository system for the storage and management of metadata, focusing on a subset of spatial data integrity constraint classes. The system is designed to support spatial system development and customization by users within the domain that the system will operate.

Object SLAM introduces the concept of objects into Simultaneous Localization and Mapping (SLAM) and helps understand indoor scenes for mobile robots and object-level interactive applications. The state-of-art object SLAM systems face challenges such as partial observations, occlusions, unobservable problems, limiting the mapping accuracy and robustness. This letter proposes a novel monocular Semantic Object SLAM (SO-SLAM) system that addresses the introduction of object spatial constraints. We explore three representative spatial constraints, including scale proportional constraint, symmetrical texture constraint and plane supporting constraint. Based on these semantic constraints, we propose two new methods - a more robust object initialization method and an orientation fine optimization method. We have verified the performance of the algorithm on the public datasets and an author-recorded mobile robot dataset and achieved a significant improvement on mapping effects. We will release the code here. <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup>

The features of a compiler for a Taxis design language are described and discussed. Taxis offers an entity-based framework for designing interactive information systems and a data model which supports generalization, classification and aggregation as abstraction mechanisms. Its features include multiple inheritance of attributes, isA hierarchies of transactions, metaclasses, typed attributes, a procedural exception-handling mechanism, an iteration construct based on the abstraction mechanisms supported, semantic integrity constraints, including time-dependent ones, and communicating Petri net-like processes (called scripts). Designing and implementing a compiler for the language requires tackling the problem of efficiently representing and accessing a large collection of entities, performing (static) type checking and representing is A hierarchies of transactions. The compiler has also been designed to deal with semantic integrity constraints and scripts, although these features have not yet been implemented.

Federated database systems [SL90] provide a uniform and transparent interface to distributed and heterogeneous databases. Such an interface consists of a federated database schema which is an integrated view onto different database schemata. This federated database schema should correctly reflect the semantics of the component database schemata of which it is composed. Since the semantics of a database schema is also determined by a set of semantic integrity constraints, a correct schema integration has to deal with integrity constraints existing in the different component database schemata.

Affordance region represents potential interaction positions between objects and actors. Previous weakly supervised methods learned object affordance regions from interaction videos using one-hot encoded action class labels as supervision, which overlooked the relationships between different action classes and lacked focused attention on critical information within video frames, resulting in inaccurate affordance region prediction and affecting interactions. To address these issues, this study introduces an Affordance Region Prediction Network grounded in Semantic and Spatial Constraints (ARP-Net), which leverages word vectors and spatial attention mechanisms to constrain the network's learning process. Word vectors consider relationships between different action classes, while spatial attention mechanisms automatically capture crucial information within video frames, thus enhancing affordance region prediction accuracy. On both EPIC-kitchens and OPRA datasets, ARP-Net attains better prediction results.

This paper proposes an efficient image retrieval system. When users wish to retrieve images with semantic and spatial constraints (e.g., a horse is located at the center of the image, and a person is riding on the horse), it is difficult for conventional text-based retrieval systems to retrieve such images exactly. In contrast, the proposed system can consider both semantic and spatial information, because it is based on semantic segmentation using fully convolutional networks (FCN). The proposed system can accept three types of images as queries: a segmentation map sketched by the user, a natural image, or a combination of the two. The distance between the query and each image in the database is calculated based on the output probability maps from the FCN. In order to make the system efficient in terms of both the computational time and memory usage, we employ the product quantization (PQ) technique. The experimental results show that the PQ is compatible with the FCN-based image retrieval system, and that the quantization process results in little information loss. It is also shown that our method outperforms a conventional text-based search system.

This work introduces an ontology-based spatio-temporal data model to represent entities evolving in space and time. A dynamic phenomenon generates a complex relationship network between the entities involved in the process. At the abstract level, the relationships can be identity or topological filiations. The existence of an identity filiation depends on whether the object changes its identity or not. On the other hand, topological filiations are based exclusively on the spatial component, like in the case of growth, reduction, merging or splitting. When combining identity and topological filiations, six filiation relationships are obtained, forming a second abstract level. Upper-level filiation relationships provide better semantic vocabulary to describe the modeled phenomena, thus allowing the implementation of spatial, temporal and identity constraints. In this paper, we present a method based on identity and topological filiation relationships, to improve the capabilities of standard knowledge bases using Semantic Web technologies. Our method enables us to check the consistency of spatio-temporal and semantic data. An example is given in the field of urban growth to show the capabilities of the model.

Global semantic integrity constraints ensure integrity and consistency of data spanning multiple databases. In this paper, we take initial steps towards representing global semantic integrity constraints for XML databases. We also provide a general framework for checking global semantic integrity constraints for XML databases. Furthermore, we set forth an efficient algorithm for checking global semantic integrity constraints across multiple XML databases. Our algorithm is efficient for three reasons: (1) the algorithm does not require the update statement to be executed before the constraint check is carried out; hence, we avoid any potential problems associated with rollbacks, (2) sub constraint checks are executed in parallel, and (3) most of the processing of algorithm could happen at compile time; hence, we save time spent at run-time. As a proof of concept, we present a prototype of the system implementing the ideas discussed in this paper.

This paper proposes an algorithm of mining spatial topology association rules with constraint condition based on Apriori, which is used to mining spatial multilayer transverse association rules with constraint condition from large spatial database. This algorithm generates candidate frequent topological item sets via up search strategy similar to Apriori, which is suitable for mining short spatial topological frequent item sets with constraint condition. This algorithm compresses storage structure of spatial topological relation to create an integer. Via this method, firstly, the algorithm may efficiently reduce some storage space of mining database. Secondly, the algorithm is effortless to distinguish topological relation of two spatial objects, namely, it may fast compute support of candidate item sets. Finally, the algorithm is fast to connect (k+1)-candidate item sets of k-frequent item set by up search strategy. The result of experiment indicates that the algorithm of mining spatial topology association rules with constraint condition based on Apriori is able to extract spatial multilayer transverse association rules with constraint condition from spatial database via efficient data store, and it is very efficient to extract short frequent topology association rules with constraint condition.