Search results
1 – 10 of over 5000Xuhui Li, Yanqiu Wu, Xiaoguang Wang, Tieyun Qian and Liang Hong
The purpose of this paper is to explore a semantics representation framework for narrative images, conforming to the image-interpretation process.
Abstract
Purpose
The purpose of this paper is to explore a semantics representation framework for narrative images, conforming to the image-interpretation process.
Design/methodology/approach
This paper explores the essential features of semantics evolution in the process of narrative images interpretation. It proposes a novel semantics representation framework, ESImage (evolution semantics of image) for narrative images. ESImage adopts a hierarchical architecture to progressively organize the semantic information in images, enabling the evolutionary interpretation under the support of a graph-based semantics data model. Also, the study shows the feasibility of this framework by addressing the issues of typical semantics representation with the scenario of the Dunhuang fresco.
Findings
The process of image interpretation mainly concerns three issues: bottom-up description, the multi-faceted semantics representation and the top-down semantics complementation. ESImage can provide a comprehensive solution for narrative image semantics representation by addressing the major issues based on the semantics evolution mechanisms of the graph-based semantics data model.
Research limitations/implications
ESImage needs to be combined with machine learning to meet the requirements of automatic annotation and semantics interpretation of large-scale image resources.
Originality/value
This paper sorts out the characteristics of the gradual interpretation of narrative images and has discussed the major issues in its semantics representation. Also, it proposes the semantic framework ESImage which deploys a flexible and sound mechanism to represent the semantic information of narrative images.
Details
Keywords
Examines the use of shared semantics information to link concepts in an organizational memory to e‐mail communications. E‐mail is by far the dominant business application of the…
Abstract
Examines the use of shared semantics information to link concepts in an organizational memory to e‐mail communications. E‐mail is by far the dominant business application of the Internet, yet the use of e‐mail relies on a number of assumptions regarding the effectiveness of interpersonal communications. One of these assumptions is that of common meaning or shared semantics. Assuming shared semantics in electronic communications can lead to a breakdown in communication, and the very managerial improvements that e‐mail is intended to foster can be negated by the resultant lack of understanding. In this paper how shared semantics are created, maintained, and used to enhance e‐mail communications is discussed. A framework for determining shared semantics based on organizational and personal user profiles is presented. How shared semantics are used by the HyperMail system to help link OM content to e‐mail messages is illustrated.
Details
Keywords
Kamal Hamaz and Fouzia Benchikha
With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as…
Abstract
Purpose
With the development of systems and applications, the number of users interacting with databases has increased considerably. The relational database model is still considered as the most used model for data storage and manipulation. However, it does not offer any semantic support for the stored data which can facilitate data access for the users. Indeed, a large number of users are intimidated when retrieving data because they are non-technical or have little technical knowledge. To overcome this problem, researchers are continuously developing new techniques for Natural Language Interfaces to Databases (NLIDB). Nowadays, the usage of existing NLIDBs is not widespread due to their deficiencies in understanding natural language (NL) queries. In this sense, the purpose of this paper is to propose a novel method for an intelligent understanding of NL queries using semantically enriched database sources.
Design/methodology/approach
First a reverse engineering process is applied to extract relational database hidden semantics. In the second step, the extracted semantics are enriched further using a domain ontology. After this, all semantics are stored in the same relational database. The phase of processing NL queries uses the stored semantics to generate a semantic tree.
Findings
The evaluation part of the work shows the advantages of using a semantically enriched database source to understand NL queries. Additionally, enriching a relational database has given more flexibility to understand contextual and synonymous words that may be used in a NL query.
Originality/value
Existing NLIDBs are not yet a standard option for interfacing a relational database due to their lack for understanding NL queries. Indeed, the techniques used in the literature have their limits. This paper handles those limits by identifying the NL elements by their semantic nature in order to generate a semantic tree. This last is a key solution towards an intelligent understanding of NL queries to relational databases.
Details
Keywords
Hongmin Zhu, Dianliang Wu and Xiumin Fan
The purpose of this paper is to develop a modeling and interactive operating method for virtual assembly (VA) to support assembly process generation based on interactive operation.
Abstract
Purpose
The purpose of this paper is to develop a modeling and interactive operating method for virtual assembly (VA) to support assembly process generation based on interactive operation.
Design/methodology/approach
This paper puts forward an assembly semantic modeling method for interactive assembly and process generation after the analysis on requirements of operation process generation. Based on this semantic model, methods for semantic generation, semantic processing and assembly motion extraction from interactive operation are presented. Partial process generation of auto engine is proposed to verify the approaches in this paper.
Findings
The application shows that assembly semantic modeling and operating methods can support process generation based on VA operations.
Originality/value
The approaches presented in this paper improve the efficiency of assembly process, making assembly process intuitive and natural.
Details
Keywords
Zhoupeng Han, Rong Mo, Haicheng Yang and Li Hao
Three-dimensional computer-aided design (CAD) assembly model has become important resource for design reuse in enterprises, which implicates plenty of design intent, assembly…
Abstract
Purpose
Three-dimensional computer-aided design (CAD) assembly model has become important resource for design reuse in enterprises, which implicates plenty of design intent, assembly intent, design experience knowledge and functional structures. To acquire quickly CAD assembly models associated with specific functions by using product function requirement information in the product conceptual design phase for model reuse, this paper aims to find an approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model before functional semantic-based assembly retrieval.
Design/methodology/approach
An approach for structure-function correlations analysis and functional semantic annotation of CAD assembly model is proposed. First, the product knowledge model is constructed based on ontology including design knowledge and function knowledge. Then, CAD assembly model is represented by part attributed adjacency graph and partitioned into multiple functional regions. Assembly region and flow-activity region are defined for structure-function correlations analysis of CAD assembly model. Meanwhile, the extraction process of assembly region and flow-activity region is given in detail. Furthermore, structure-function correlations analysis and functional semantic annotation are achieved by considering comprehensively assembly structure and assembled part shape structure in CAD assembly model. After that, a structure-function relation model is established based on polychromatic sets for expressing explicitly and formally relationships between functional structures, assembled parts and functional semantics.
Findings
The correlation between structure and function is analyzed effectively, and functional semantics corresponding to structures in CAD assembly model are labeled. Additionally, the relationships between functional structures, assembled parts and functional semantics can be described explicitly and formally.
Practical implications
The approach can be used to help designers accomplish functional semantic annotation of CAD assembly models in model repository, which provides support for functional semantic-based CAD assembly retrieval in the product conceptual design phase. These assembly models can be reused for product structure design and assembly process design.
Originality/value
The paper proposes a novel approach for structure-function correlations analysis and functional semantic annotation of mechanical CAD assembly model. Functional structures in assembly model are extracted and analyzed from the point of view of assembly structure and function part structure. Furthermore, the correlation relation between structures, assembled parts and functional semantics is expressed explicitly and formally based on polychromatic sets.
Details
Keywords
In a context of critical transition such as the COVID-19 pandemic, moral semantics take a prominent role as a form of self-description of society. However, they are not usually…
Abstract
Purpose
In a context of critical transition such as the COVID-19 pandemic, moral semantics take a prominent role as a form of self-description of society. However, they are not usually observed, but rather assumed as self-evident and necessarily “good.” The purpose of the article is to summarize the theory of morality from the social systems' perspective and illustrate with concrete examples the polemogenous nature of moral communication.
Design/methodology/approach
This article presents an analysis of the role of morality in the context of the COVID-19 pandemic, from the perspective of Niklas Luhmann’s social systems theory. Applying the method of second-order observation, it describes three cases of moral semantics disseminated via mass media and social media, and it examines their connection with the structural situation of subsystems of society during the pandemic crisis (particularly healthcare, politics and science).
Findings
Second-order observation of moral communication demonstrates to be fruitful to describe the conditions and consequences in which moralization of communication occurs, particularly in a situation of critical transition around the healthcare crisis. The three examples examined, namely, the hero semantics directed to healthcare workers, the semantics of indiscipline and the controversies around pseudo-sciences and conspiracy theories, show how they are based on social attribution of esteem and disesteem, how they try to answer to troublesome situations and contradictions that seem difficult to cope, and how they are close related to the emergence of conflicts, even when they seem positive oriented and well intentioned.
Originality/value
This paper is an attempt to test the usefulness of Luhmann's theory of society to understand the ongoing COVID-19 crisis and particularly the role of moral communication in concrete examples.
Details
Keywords
Nurlaila, Syahron Lubis, Tengku Sylvana Sinar and Muhizar Muchtar
Purpose – This paper is aimed at describing semantics equivalence of cultural terms in meurukon texts translated from Acehnese into Indonesian. A qualitative descriptive approach…
Abstract
Purpose – This paper is aimed at describing semantics equivalence of cultural terms in meurukon texts translated from Acehnese into Indonesian. A qualitative descriptive approach is used to analyze the context of semantics equivalence in these texts: varied semantics structure, especially the ones caused by the cultural gap between the two languages.
Design/Methodology/Approach – This research is designed to be of qualitative descriptive nature, wherein data are documented and analyzed using various methods proposed by Miles, Huberman, and Saldana (2014), such as data condensation, data display, drawing and verifying conclusions. The researcher is considered the key instrument in the whole process. The source of the data collected is from meurukon texts and its translation that consists of 623 sentences: they mainly comprise words and phrases that contain semantics equivalence of cultural terms.
Findings – The result of the research shows that there are 129 cultural terms found in 623 sentences. Of the analyzed data, it is seen that only 16.66% of the data is not equivalent with the target text, while 83.34% words and phrases of meurukon text are equivalent. This suggests that as a result of translation, the meurukon text has high semantics or lexical equivalences with the target text.
Research Limitations/Implications – This research is focused on semantics equivalence found in meurukon texts. The semantic equivalence here only pertains to lexical meaning of nouns and adjectives by using componential analysis.
Practical Implications – The result can be used in a sample of ways for the analysis of semantics equivalence of cultural terms in meurukon text translated from Acehnese into Indonesian using componential analysis.
Originality/Value – This research identifies meurukon as an oral tradition of Acehnese culture, which is in the question and answer format about Islamic law in Aceh, specifically North Aceh.
Details
Keywords
Ahmed Elragal and Nada El-Gendy
Trajectory is the path a moving object takes in space. To understand the trajectory movement patters, data mining is used. However, pattern analysis needs semantics to be…
Abstract
Purpose
Trajectory is the path a moving object takes in space. To understand the trajectory movement patters, data mining is used. However, pattern analysis needs semantics to be understood. Therefore, the purpose of this paper is to enrich trajectories with semantic annotations, such as the name of the location where the trajectory has stopped, so that the paper is able to attain quality decisions.
Design/methodology/approach
An experiment was conducted to explain that the use of raw trajectories alone is not enough for the decision-making process and detailed pattern extraction.
Findings
The findings of the paper indicates that some fundamental patterns and knowledge discovery is only obtainable by understanding the semantics underlying the position of each point.
Research limitations/implications
The unavailability of data are a limitation of the paper, which would limit its generalizability. Additionally, the lack of availability of tools for automatically adding semantics to clusters posed as a limitation of the paper.
Practical implications
The paper encourages governments as well as businesses to analyze movement data using data mining techniques, in light of the surrounding semantics. This will allow, for example, solving traffic congestions, since by understanding the movement patterns, the traffic authority could make decisions in order to avoid such congestions. Moreover, it could also help tourism authorities, at national levels, to know tourist movement patterns and support these patterns with the required logistical support. Additionally, for businesses, mobile operators could dynamically enhance their services, voice and data, by knowing the semantically enriched patterns of movement.
Originality/value
The paper contributes to the already rare literature on trajectory mining, enhanced with semantics. Mainstream literature focusses on either trajectory mining or semantics, therefore the paper claims that the approach is novel and is needed as well. By integrating mining outcomes with semantic annotation, the paper contributes to the body of knowledge and introduces, with lab evidence, the new approach.
Details
Keywords
Montserrat Batet and David Sánchez
To overcome the limitations of purely statistical approaches to data protection, the purpose of this paper is to propose Semantic Disclosure Control (SeDC): an inherently semantic…
Abstract
Purpose
To overcome the limitations of purely statistical approaches to data protection, the purpose of this paper is to propose Semantic Disclosure Control (SeDC): an inherently semantic privacy protection paradigm that, by relying on state of the art semantic technologies, rethinks privacy and data protection in terms of the meaning of the data.
Design/methodology/approach
The need for data protection mechanisms able to manage data from a semantic perspective is discussed and the limitations of statistical approaches are highlighted. Then, SeDC is presented by detailing how it can be enforced to detect and protect sensitive data.
Findings
So far, data privacy has been tackled from a statistical perspective; that is, available solutions focus just on the distribution of the data values. This contrasts with the semantic way by which humans understand and manage (sensitive) data. As a result, current solutions present limitations both in preventing disclosure risks and in preserving the semantics (utility) of the protected data.
Practical implications
SeDC captures more general, realistic and intuitive notions of privacy and information disclosure than purely statistical methods. As a result, it is better suited to protect heterogenous and unstructured data, which are the most common in current data release scenarios. Moreover, SeDC preserves the semantics of the protected data better than statistical approaches, which is crucial when using protected data for research.
Social implications
Individuals are increasingly aware of the privacy threats that the uncontrolled collection and exploitation of their personal data may produce. In this respect, SeDC offers an intuitive notion of privacy protection that users can easily understand. It also naturally captures the (non-quantitative) privacy notions stated in current legislations on personal data protection.
Originality/value
On the contrary to statistical approaches to data protection, SeDC assesses disclosure risks and enforces data protection from a semantic perspective. As a result, it offers more general, intuitive, robust and utility-preserving protection of data, regardless their type and structure.
Details
Keywords
Faisal Alkhateeb and Jerome Euzenat
The paper aims to discuss extensions of SPARQL that use regular expressions to navigate RDF graphs and may be used to answer queries considering RDFS semantics (in particular…
Abstract
Purpose
The paper aims to discuss extensions of SPARQL that use regular expressions to navigate RDF graphs and may be used to answer queries considering RDFS semantics (in particular, nSPARQL and our proposal CPSPARQL).
Design/methodology/approach
The paper is based upon a theoretical comparison of the expressiveness and complexity of both nSPARQL and the corresponding fragment of CPSPARQL, that we call cpSPARQL.
Findings
The paper shows that nSPARQL and cpSPARQL (the fragment of CPSPARQL) have the same complexity through cpSPARQL, being a proper extension of SPARQL graph patterns, is more expressive than nSPARQL.
Research limitations/implications
It has not been possible to the authors to compare the performance of our CPSPARQL implementation with other proposals. However, the experimentation has allowed to make interesting observations.
Practical implications
The paper includes implications for implementing the SPARQL RDFS entailment regime.
Originality/value
The paper demonstrates the usefulness of cpSPARQL language. In particular, cpSPARQL, which is sufficient for capturing RDFS semantics, admits an efficient evaluation algorithm, while the whole CPSPARQL language is in theory as efficient as SPARQL is. Moreover, using such a path language within the SPARQL structure allows for properly extending SPARQL.
Details