Semantic Construction Research Articles

MAMSC: a semantic enhanced representation model for public opinion key node recognition based on multianchor mapping in semantic communities

PurposeInformation is presented in various modalities such as text and images, and it can quickly and widely spread on social networks and among the general public through key communication nodes involved in public opinion events. Therefore, by tracking and identifying key nodes of public opinion, we can determine the direction of public opinion evolution and timely and effectively control public opinion events or curb the spread of false information.Design/methodology/approachThis paper introduces a novel multimodal semantic enhanced representation based on multianchor mapping semantic community (MAMSC) for identifying key nodes in public opinion. MAMSC consists of four core components: multimodal data feature extraction module, feature vector dimensionality reduction module, semantic enhanced representation module and semantic community (SC) recognition module. On this basis, we combine the method of community discovery in complex networks to analyze the aggregation characteristics of different semantic anchors and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations.FindingsThe experimental results show that compared with its variants and the baseline models, the MAMSC model has better recognition accuracy. This study also provides more systematic, forward-looking and scientific decision-making support for controlling public opinion and curbing the spread of false information.Originality/valueWe creatively combine the construction of variant autoencoder with multianchor mapping to enhance semantic representation and construct a three-layer network module for public opinion node recognition in the SC with strong, medium and weak associations. On this basis, our constructed MAMSC model achieved the best results compared to the baseline models and ablation evaluation models, with a precision of 91.21%.

Path dependence in explanatory models of economic thinking: Practice of publications in business media

Based on the sample of publications in federal business periodicals for the period from 2000 to 2024, the article examines the specifics of explanatory models used in the information discourse and applied in the press for the essential characteristics of economic processes. Content analysis and discourse analysis show that the explanatory models used in the media are fully consistent with the path dependence effect, that is, they record the dependence of current and future development on past experience, and also appeal to this experience regardless of its correspondence to the real state of economic picture. The article outlines the prospects for using explanatory models in the information discourse, including the inertia of using outdated economic approaches, the coexistence of conflicting stereotypes, as well as the strengthening of semantic empty constructions that record only the external form of the explanatory model without relevant empirical subject. A conclusion is made about the strengthening of the path dependence effect in explanatory models of the media, and, consequently, about the increasing subjectivity in the presentation of economic information

Schema Representation, Semantic Network Construction and Construal of the English Direction Preposition “To” and “Toward(s)”

For a long time, prepositions have been a class of words that have attracted the attention of scholars. However, from the perspectives of Structural Linguistics, Transformational-generative Linguistics, and Functional Linguistics, different scholars have emphasized the collocation of prepositions with other parts of speech to form a conventional linguistic unit, but have not studied the prepositions themselves. So far, most studies on English prepositions from the perspective of cognitive linguistics have focused on the prepositions with obvious spatial conceptual meaning. Still, there has not been sufficient cognitive research for some prepositions without spatial conceptual meaning. Therefore, this article selects the direction prepositions “to” and “toward(s),” from the perspective of cognitive linguistics, using category theory, schema theory, and construal theory, and combining the metaphor and metonymy to extend the meaning, to analyze and distinguish, finally construct schema representation, semantic network and construal of the English direction preposition “to” and “toward(s)”.

The Mereological Basis of Truthmaker Semantics

AbstractThis articles explores the mereological foundation of truthmaker semantics. Building upon Kit Fine’s abstract theory of part in Fine [J Philos 107(11):559–589, 2010], we engage in an exploration of the mereological assumptions that determine the construction of truthmaker semantics. Our approach yields semantics for a diverse range of logics, including substructural logics such as the associative Lambek calculus, as well as the logics of analytic containment. Furthermore, we elucidate the philosophical implications that arise from this pioneering approach.

Semantic Analysis and Construction of English Discourse Based on Intelligent CAD Tutoring Systems

Semantic Analysis and Construction of English Discourse Based on Intelligent CAD Tutoring Systems

Model of Comparative Analysis of the Structure and Semantics of Causal Constructions in Multi-Structural Languages

This article explores the application of constructive grammar, a linguistic approach that integrates cognitive, syntactic, and semantic frameworks to analyse causative constructions in English and Russian languages. Constructive grammar interprets not only the form and content of linguistic components but also the structure itself, which influences and imposes constraints on these components. The study considers the methodological evolution from traditional syntactic theories to cognitive models, particularly the influence of Ch. Fillmore’s work. By focusing on causative constructions, specifically analytical causatives like "The police made him confess," the research draws upon the theories of V.P. Nedyalkov, G.G. Silnitsky, and A.A. Kholodovich, among others, to provide a comparative analysis of causative structures in different languages. Cognitive and generative grammar perspectives, including R. King's spatial metaphor and L. Talmy’s force dynamics, are integrated to establish a comprehensive framework for understanding the universal and language-specific properties of causative expressions. The findings highlight the importance of the cognitive interpretation of syntactic structures, the role of energy transfer between agents and patients, and the diverse semantic types of causative situations. The study concludes by suggesting future research directions in the syntactic classification and formal expression of causative components.

The purpose of metaphysics: Apology of excess

AbstractThis article consistently elaborates the extra‐contextual nature of metaphysical knowledge. Metaphysicsis seen as a semantic construction of culture that produces a certain type of thinking, memory, and identification: that is, subjectivity, and sociality as an ethical and axiological model of interaction with the world and the Other. The paper argues that metaphysics is a kind of orientation in space and that culture is a semiotic way of world orientation, or collection of spaces into an intelligible structure, a specific characteristic of human existence in the universe. Indeed, metaphysics through the space of culture allows one to experience the universe empirically as unity, to assume the presence of meaning. Based on the analysis, the paper summarizes the definition of the phenomenon of culture as a specifically human way of mastering space and controlling time, consciousness as a topology of reflective practices, and virtual reality technology as a space of pure metaphysics.

COGNITIVE PROCESS IN COMPREHENSION OF SENTENCE PROPOSITIONS AMONG THE UNDERGRADUATE EFL STUDENTS

English acquired by EFL learners is categorized as interlanguage, which means that their English is developing towards native like competence. In Indonesian context, the EFL learners’ vocabulary and sentence structure mastery is insufficient. Comprehending main propositions or sentence meanings require cognitive process of both semantic and structural construction. Within such insufficient mastery of English, the researchers intend to uncover the cognitive process EFL learners applied to comprehend main propositions of complex sentences. For this purpose of the study, the researches obtained the main propositions that the learners comprehended from three complex sentences assigned to them to read. Soon after completing the comprehension, the learners were assigned to write their retrospective introspection (mental process they were experiencing during the comprehension). The two types of data were analyzed qualitatively. The research findings show that 65.24% of the EFL learners applied semantic construction, 25.24% used discourse analysis, and 9.52% applied syntactical construction. This indicated that in comprehending sentence meaning, 90.48% EFL learners relied more on words and discourse meanings rather than on sentence structure or on their combination.

An improved SLAM algorithm for substation inspection robot based on the fusion of IMU and visual information

In the past, manual inspection was often used for equipment inspection in indoor environments such as substation rooms and chemical plant rooms. This way often accompanies high labor intensity, low inspection efficiency, and low safety, which is difficult to meet the increasingly stringent requirements of indoor equipment operation and maintenance management. For dealing with these issues, a VIORB-SLAM2 algorithm based on the integration of IMU and visual information, was proposed by this paper. Firstly, the IMU data and image data were integrated to restore scale information of cameras, and then an error function was established to enhance the algorithm’s robustness. Secondly, in order to improve the accuracy of the algorithm, the random sampling consensus method was used to eliminate the wrong matching points in feature point matching, and the normalized cross-correlation matching was employed to constrain key frame matching conditions. Finally, through the iterative closest point method to stitch the point clouds, a dense map for navigation was constructed. The experimental results show that the algorithm designed by this paper has solved the shortcomings of applying the ORB-SLAM2 algorithm to indoor inspection robots while achieving high positioning accuracy, which can be combined with other algorithms in the field of artificial intelligence for object detection and semantic map construction in the future.

The locust plagues of the Ming Dynasty in Shandong Province, China

In today’s era of unprecedented climate change, research on environmental changes and natural disasters remains crucial. Locust plagues, among the most devastating agricultural disasters, had a profound impact on ancient China, especially during the Little Ice Age. This study utilizes historical records of locust plagues, employing semantic quantification, index construction and spatial analysis, to explore their temporal distribution, spatial patterns, migration characteristics, and associations with climate factors in Shandong during the Ming Dynasty. Key findings include: (1) Locust plagues in Shandong were severe, with 599 documented occurrences, primarily in summer and autumn, especially from April to August. The frequency and intensity of these outbreaks increased significantly during the mid to late Ming Dynasty, peaking in the late Ming period. (2) Geographically, locust plagues were concentrated in the northern river regions of Shandong, particularly in cities like Jinan, Dezhou, and Weifang, with marked clustering, spatial heterogeneity, and positive spatial correlation. (3) Locust plagues were strongly linked to droughts, showing significant temporal and spatial synchrony, but had no significant correlation with floods. These plagues were more likely to occur during cooler and drier periods, with both temperature and precipitation significantly influencing their occurrence.

Discursive and institutional standards of justice in the modern world-system

In the article the essence of standards of justice in the modern world-system is outlined in a general way. It is shown that these standards emerged in the European capitalist world-economy in consequence of the French Revolution. Standards of justice are interpreted as ideological semantic constructions that have been institutionalized simultaneously with establishment, first, of the ideology of liberalism as the geoculture of the modern world-system and, second, — of model of liberal state. Standards of justice are considered within theoretical theses and methodological guiding lines of I. Wallerstein's theory of the modern world-system. However, some theoretical theses of J. Alexander's civil society theory are also used to supplement and concretize considered in the article problems with some new arguments. For instance, Alexander's conceptual toolkit helped to distinguish discursive and institutional standards of justice. Reasons and peculiarities of establishment of standards of justice are considered and role these standards played in the providing of development of the modern world-system is shown. In particular, it is elucidated that owing to these standards elites of the core countries of the modern world-system managed to redirect the rebellion energy of the lower strata from antisystemic revolutions to struggle for inclusion to liberal state. This helped to calm the lower strata down and to guard structures of the modern world-system against essential damages. Standards of justice contributed to legitimation of social order of the modern world-system. Full integration of the lower strata to newly created national societies reinforced social solidarity, and this strengthened the core states even more. It is shown that for today in particular countries of periphery and semi-periphery trends of revision of current standards of justice and their replacement by alternative semantic constructions become visible.

Cross-domain zero-shot learning for enhanced fault diagnosis in high-voltage circuit breakers

Ensuring the stability of high-voltage circuit breakers (HVCBs) is crucial for maintaining an uninterrupted supply of electricity. Existing fault diagnosis methods typically rely on extensive labeled datasets, which are challenging to obtain due to the unique operational contexts and complex mechanical structures of HVCBs. Additionally, these methods often cater to specific HVCB models and lack generalizability across different types, limiting their practical applicability. To address these challenges, we propose a novel cross-domain zero-shot learning (CDZSL) approach specifically designed for HVCB fault diagnosis. This approach incorporates an adaptive weighted fusion strategy that combines vibration and current signals. To bypass the constraints of manual fault semantics, we develop an automatic semantic construction method. Furthermore, a multi-channel residual convolutional neural network is engineered to distill deep, low-level features, ensuring robust cross-domain diagnostic capabilities. Our model is further enhanced with a local subspace embedding technique that effectively aligns semantic features within the embedding space. Comprehensive experimental evaluations demonstrate the superior performance of our CDZSL approach in diagnosing faults across various HVCB types.

Representation of concepts associated with the digital environments of Chilean students

Introduction: The construction of digital identity is a negotiation process that involves a link between the self, identity, and cultural models. This process is affected by the incursion of technology, which incorporates new verbal forms and traces permanently connected spaces where digital identity is co-constructed. The objective was to determine the conceptual and social representations that construct digital identity in a group of Chilean students by sex.Method: Qualitative research with an analytical descriptive design. The sample included 509 Chilean students aged 18 to 27 from 21 higher education institutions. They were asked to write the first word they associated with the concepts of personal identity, digital identity, digital reputation, and privacy. The results were processed in the Atlas.Ti program, creating word clouds differentiated by sex.Results: Both men and women associated personal identity with "personality." For "digital identity," both groups agreed on the concept of "projection." However, regarding the concept of “digital reputation” men associated it with the term “followers” ​​and women with “prestige”. Regarding “visibility” men associated it with “privacy” and women with “exposure”.Conclusions: the concepts of identity (personal and digital) converge towards common social semantic constructions. However, in concepts such as reputation and visibility, stereotypical gender constructions are evident, with women associating them with prestige and exposure and men with followers and privacy.

Profiling analytic causative construction in Chinese: a multifactorial analysis of diachronic change

Abstract Taking a multifactorial approach, this article profiles the formal and semantic changes of Chinese analytic causative construction (CACC for short) and its jiao 1 , jiao 2 , ling, rang and shi micro-constructions. It is found that CACC micro-constructions have undergone two types of formal change. Building on a data-driven periodization of diachronic data, this study analyzes semantic changes of CACC and its micro-constructions from semasiological and onomasiological perspectives and at local constituent and global construction levels. Major findings are as follows: six stages are identified in the semantic development of CACC micro-constructions. Semasiologically, diachronic semantic prototypicality of CACC remains constant while that of its micro-constructions changes with time. A general polysemization route is followed by CACC and its micro-constructions, with the superordinate CACC governing the subordinate micro-constructions in semantic change pathway. Onomasiologically, diachronic semantic division of labor among CACC micro-constructions varies over time. For CACC micro-constructions, semantics of local causer, causee and effected predicate tends to change in concert with global constructional semantics at early and late periods of semantic development, whereas local and global semantic changes during the intermediary stages are usually partially coordinated. This study has demonstrated the application of collostructional analysis in investigating diachronic semantic change of a construction.

Hierarchical visual semantic guidance for enhanced relationship recognition in domain knowledge graphs

Multi-modal entity relationship recognition is a crucial foundation for constructing accurate and comprehensive domain knowledge graphs. However, due to the sparse and diverse nature of textual semantic information and the semantic differences exhibited by multi-modal data, existing methods often suffer from issues such as information loss and noise features. In this paper, the Hierarchical Visual Semantic Guidance (HVSG) Network is proposed, which utilizes images to furnish visual semantic information for text, facilitating the identification of implicit relationships between entities. Specifically, salient local instance objects are initially extracted from the global image, followed by the use of a hierarchical visual semantic construction module to establish multi-level visual semantics. The integration of multi-level visual and textual features is then achieved through a visual semantic guidance module. This work constructed a Chinese multi-modal entity relation classification dataset in the domain of unmanned vessels and conducted experiments on two datasets. Compared to state-of-the-art (SOTA) models, HVSG achieved the best performance, with F1 scores improved by 1.05% and 0.58% respectively, indicating that HVSG can offer better performance in exploring implicit relationships between textual entities.

Research on the construction and mapping model of knowledge organization system driven by standards

With the rapid development of artificial intelligence and enterprise digital transformation, the standardization organization, storage and management of semantic knowledge in computers have become the current research focus. As the core theory of knowledge system construction, knowledge organization (KO) provides theoretical support for the study of semantic knowledge organization and representation, among which knowledge organization system (KOS) is the important tool of semantic organization. At present, many scholars have carried out research from different perspectives of KOS based on theory, which provides the direction for the sustainable development of KOS. However, most of these studies focus on some aspects of KOS, which are in a "scattered" state, lacking systematic analysis of the basic principles of KOS construction and semantic organization based on theories and international standards. Therefore, this paper firstly constructs KOS theoretical models in the conceptual world and computer world respectively through a comprehensive study of multi-disciplinary basic theories such as semantics, logic, system theory, and international standards such as ISO 1087:2019, ISO 25964:2013, and ISO 11179:2023, and traces the iterative construction, organization and mapping process from "concept" in the conceptual world to "metadata" knowledge and semantics in the computer world. The semantic organization based on metadata is realized in computer. Secondly, on this basis, in order to realize ontology representation of domain knowledge, the ontology construction method based on MDR metadata is proposed. Finally, taking the semantic organization and ontology construction of Epicentre model in petroleum field as an example, the feasibility of the ideas and methods proposed in this paper is verified. The model and method proposed in this paper is independent of the specific type of KOS, so it is innovative and universal. The methodology is also applicable to other fields of conceptual system modeling, metadata standard construction, and data model modeling.

The legacy of Luhmann’s sociology of law

This paper aims to map the possibilities of adopting social systems theory in order to couple three usually isolated domains: social theory, jurisprudence and empirical research. It argues that these different uses would be the distinctive legacy of Luhmann’s work for legal research. The text suggests that investigations interested in adopting a systemic approach for discussions in each of these three domains (or in all of them) should focus on the entanglement among interactional, decisional and functional systems. However, this presupposes some enhancements in Luhmann’s own description of law as a social system. The core hypothesis presented here is that a functional system’s out-differentiation (its specialisation in face of other communications happening in the societal environment) depends on the inner-differentiation of this system – that is, on operations backed by the very construction of specific functional-systemic institutions and semantics (including decisional programs and self-descriptions).

Sustainability Strategic Framing in Corporate Communication: Contextual Semantics of Twitter in the Energy Sector

Sustainability has become the prevailing paradigm, a model of conduct, and a central theme in social and media discourses within the past decade. However, it is still a marginal development concept in the interdisciplinary research field dealing with sustainability communication, especially with meaning-making processes in relevant communicative, for example, in corporate and industry contexts. This paper focuses on how the idea of sustainability is framed, anchored, and disseminated in energy companies' communication via social media channels and how the linguistic methods used by energy corporations concerning sustainability co -create theirsymbolic value. Specifically, this study has aimed to understand how the sustainability topic was discussed in the Twitter sphere of the most prominent energy companies in 2020. This study makes a three -fold contribution to sustainable research and practice. First, the study identifies the framing structure of sustainability content in social media communication in the energy sector. Secondly, the study identifies social media data as a viable source of sustainability conceptualization and its understanding through communication. Finally, this study illustrates how text mining and natural language processing (NLP) can be used as a research method for managing big text data and a tool for discovering latent communication structures. Sustainability is present and visible in the communication of the energy industry identified by (1) the semantic construction of phrases in communication that show a future, green, and clean orientation, but it is also strongly declarative, referring to what will be and can be done, and with positive emotions related to the communicated messages; and (2) decoupling from climate change and thus avoiding the industry's responsibility for the impact of global warming but promising clean, sustainable energy transformation and to avoid negative emotional connotation. However, one gets the impression that it takes on the character of a rhetorical art form related to the concept of decorum. In this view, the idea of sustainability is interpreted and shaped through the needs of the industry and as a rhetorical tool in building a positive narrative about companies and is used to gain legitimacy.

Modeling Principles to Moderate the Growth of Technical Debt in Descriptive Models

AbstractModel‐Based Systems Engineering (MBSE) is the next step in the evolution of systems engineering (SE) in which documents are replaced by descriptive models as the authoritative embodiment of SE knowledge. These descriptive models possess a unique combination of the features and characteristics of documents, software, and data. Conscientiously applying appropriate modeling principles and practices is essential to make informed decisions to moderate the accumulation of model technical debt. This paper briefly explains the concept of technical debt and its adaptation to the domain of descriptive models for MBSE. The paper then describes 18 foundational modeling principles that model architects should consider when making architectural and implementation decisions about their models and describes some of the key model technical debt tradeoffs that result when these principles are not followed. These principles address commonly observed challenges regarding model federation architecture, the selection and use of model layers, the modeling of the domain, and the semantics of modeling constructs. Applying disciplined model architecting practices to conscientiously manage the accrual and payoff of technical debt can make the difference between an enduring model that provides substantial value throughout the life cycle of the modeled entity and a model whose value collapses under the weight of uncontrolled technical debt.

Emotion Semantics Construction in Industrial Product Application

The theory of emotion semantics constitution put forward in this study aims to explore on how to convey emotions in product design. First, the development of emotion expression methods is reviewed, to point out the trend from physiological aspect to psychological activities and bring up a double-layer research framework composed of expression communication and sensory reception. The study has made a profound discussion on how to convey emotions in product design with sensory elements such as vision, hearing and touch, and to rouse the users’ emotional resonance with multiple elements in product design. On theoretical level, this study has discussed how to construct visual symbols and apply concepts such as “emotional bionics” and product semantics, so as to optimize the function of sensory elements in regulating emotions by combining morphological aesthetics and semantic representations. In terms of practice, this study puts forward the visual modelling construction theory for “allomorphic” product, corresponds visual symbols such as product modelling, color design and material with emotional conveyance semantics, and highlights the users’ unique emotional experience facilitated by art and sensory experience, so that the viewers can be greatly impressed by the product. The study also emphasizes the key role of design in promoting emotional resonance and sensory experience, and brings forward a series of design methods and technological innovation including emotion analysis, multimedia interaction, multi-element integration, introduction of cultural symbols and the incorporation of knowledge of applied psychology and physiology, aiming at enhancing positive interaction in the users’ emotion and psychology via a full range of sensory stimulation.