Semantic Network Of Concepts Research Articles

Formation of a generalized semantic network of concepts

The subject of research is the features of formation of a generalized semantic network of concepts. The purpose of article is to substantiate the composition and main types of nodes and relationships characteristic of the semantic network of concepts, as well as the formation of a generalized semantic network of concepts for structural and linguistic recognition of images in computer systems and networks. Research methods: methods of the theory of mathematical logic, mathematical linguistics and set theory; methods of information visualization using graphs. Results: an approach to the formation of a generalized semantic network of structural and linguistic concepts of contour images of objects obtained at different shooting angles is proposed; the substantiation of the composition and types of nodes and relations, characteristic of the semantic network of concepts, has been carried out; the basic principles of constructing a semantic network of structural and linguistic concepts of recognition objects are formulated. Conclusions: To construct an image description that corresponds to the concept of semantic information processing and can be used in systems for collecting relevant images in computer systems and networks, it is advisable to use a structural-linguistic approach to recognition using a generalized semantic network of concepts. The use of this network in the classification and identification of objects can significantly expand the range of images accepted for consideration, taking into account different directions of shooting and different angles of camera deviation from nadir position.

The emergence of richly organized semantic knowledge from simple statistics: A synthetic review

As adults, we draw upon our ample knowledge about the world to support such vital cognitive feats as using language, reasoning, retrieving knowledge relevant to our current goals, planning for the future, adapting to unexpected events, and navigating through the environment. Our knowledge readily supports these feats because it is not merely a collection of stored facts, but rather functions as an organized, semantic network of concepts connected by meaningful relations. How do the relations that fundamentally organize semantic concepts emerge with development? Here, we cast a spotlight on a potentially powerful but often overlooked driver of semantic organization: Rich statistical regularities that are ubiquitous in both language and visual input. In this synthetic review, we show that a driving role for statistical regularities is convergently supported by evidence from diverse fields, including computational modeling, statistical learning, and semantic development. Finally, we identify a number of key avenues of future research into how statistical regularities may drive the development of semantic organization.

TOWARDS SEMANTIC NETWORK OF PHILOSOPHY TERMINOLOGIES FOR LEARNING IN UNIVERSITY IN VIETNAM

<p>Semantic network is so far an effective way for knowledge representation, especially if the matter deals with complexity of terminologies and concepts, which are not standalone, but connected by various relations. One among these fields of knowledge is philosophy, and one fact that the study students of university always face with difficulties when address the system of terminologies and concepts of philosophy. In practice, various tools are using by teachers for helping students understand philosophy terminologies and concepts, i.e. using mindmap tools. In this paper, we suggest a use of semantic network as a tool for representation of key terminologies in philosophy of Marxism that have been teaching in Vietnamese universities. For this purpose, the authors of the paper carefully investigate all materials of appropriate learning; make a selection and classification for setting up of terminologies; build a semantic network of these terminologies for a conceptional model. An effort is providing to design one software system with semantic updating, selecting and representing. These results are under the project “Studying and building semantic network of concepts in philosophy discipline for teaching and researching activities” ID: QG.18.46, in a University of Social Sciences and Humanities of Hanoi National University.
 
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Nobili on Mobile! When the scientific instruments exhibitions are at your fingertips

This paper presents a general view of a proposal for a digital reinterpretation of a collection of scientific instruments belonging to the Physics Cabinet of the Science Museum of the University of Coimbra. In this cataloging, the local and global aspects of each instrument are inventoried and represented by a semantic network of concepts, facts, ideas, and narratives, resulting in a knowledge base about scientific physics instruments. This knowledge base will be made available to students, researchers, and the general public through a mobile phone application. The article also offers a review of the transformations of the conceptual models of material culture studies related to scientific instruments and adds some contributions to this field of study.

Semantic Concept Network and Deep Walk-based Visual Question Answering

Visual Question Answering (VQA) is a hot-spot in the intersection of computer vision and natural language processing research and its progress has enabled many in high-level applications. This work aims to describe a novel VQA model based on semantic concept network construction and deep walk. Extracting visual image semantic representation is a significant and effective method for spanning the semantic gap. Moreover, current research has shown that co-occurrence patterns of concepts can enhance semantic representation. This work is motivated by the challenge that semantic concepts have complex interrelations and the relationships are similar to a network. Therefore, we construct a semantic concept network adopted by leveraging Word Activation Forces (WAFs), and mine the co-occurrence patterns of semantic concepts using deep walk. Then the model performs polynomial logistic regression on the basis of the extracted deep walk vector along with the visual image feature and question feature. The proposed model effectively integrates visual and semantic features of the image and natural language question. The experimental results show that our algorithm outperforms competitive baselines on three benchmark image QA datasets. Furthermore, through experiments in image annotation refinement and semantic analysis on pre-labeled LabelMe dataset, we test and verify the effectiveness of our constructed concept network for mining concept co-occurrence patterns, sensible concept clusters, and hierarchies.

Development of a Knowledge Base in the “Smart Farming” System for Agricultural Enterprise Management

Increasing the efficiency of agricultural production is a very important task. To solve this problem, it is proposed to use the “Smart Farming” cloud system for precision farming management. The novelty of the proposed approach lies in using the knowledge base and multi-agent technology to develop coordinated decisions on management of agricultural enterprises. The paper focuses on development of the knowledge base in the "Smart Farming" system on precision agriculture. Information storage is organized in the form of a semantic network of concepts and relations on the "All about the concept" principle in a single repository, which facilitates the work of farmers with this resource. The paper covers storage, editing, verification, and visualization of knowledge representation about the domain of crop production, production resources, agricultural machinery, equipment and other material resources, as well as peculiarities of the tasks of precision farming. The knowledge base of plant production, built on ontological principles, will be useful to enterprise managers, agronomists, machine operators, planning services and other specialists of large, medium and small farms, as well as to individual farmers.

Cognitive Models of Grammatical Competence of Students

The article is based on the precepts of cognitive science and considers grammar competence of language learners as a semantic network of concepts, categories, prototypes, frames, scripts, schemata acquired as knowledge and grammar skills. The author examines students’ grammatical competence in the light of cognitive approach and presents the cognitive model of grammatical competence. The model shows what components are needed for the students’ to know how an English sentence is grammatically organized. This makes cognitive model of grammatical competence of students a useful tool for students and teachers.

Объединение автоматизированных учебных пособий на основе семантической сети понятий

Объединение автоматизированных учебных пособий на основе семантической сети понятий

Intelligence Analysis and Processing System for Semantic Concept Network Based-on State Identification

In this paper, we present an intelligence analysis and processing system based on state classify for the Semantic Concept Network (SCN). We argue that due significant change in costs of computation and resource distribution, our system is particularly suitable for the SCN environment with important resources. One of the interesting natures of our system is that it provides time-sharing distribution of the offline resource, which allows the user to reuse the offline pre-computed information in assembly time, in contrast to one-time distribution in all previous Intelligence Analysis and Processing (IAP) classify systems. As evidence of the feasibility and practicality of our system to be used in the SCN environment, we provide an real implementation result of our system on the Micro-V platform.

The effect of knowledge and context in the elicitation of inferences in class-inclusion reasoning

Abstract Two experiments were carried out with adult subjects to investigate the conditions of production of inferences in a problem-solving task involving reasoning about class inclusion. We tested the hypothesis that the production of appropriate inferences is facilitated whenever pieces of information are stored in memory that can be matched at least in part with the conclusion resulting from the inference. In Experiment 1, problems involving the same inferential pattern but belonging to three different domains were compared. The inclusion relations were of the type “is a kind of” (semantic domain), “more than” (being 8 years old is being more than 7 years old: logico-mathematical domain) or “what I have received on a given day is a part of what I have in the evening” (possession domain). In the semantic domain, the critical inference may be facilitated by the semantic network of concepts stored in memory. In the logico-mathematical domain, there is no information that corresponds to the critical infer...

Expert/consultation system for a retrieval data-base with semantic network of concepts

This paper describes a development and implementation of an expert/consultation system for a retrieval data-base, that interfaces between the user and a retrieval system. The system's objective is to perform the information consultant's job in assisting a user to select the right vocabulary terms for his query. It is particularly useful for a novice user of a controlled-vocabulary, index-based retrieval system, who is not familiar with the vocabulary and the system Thesaurus. The user will enter his terms/keywords, that represent his information need, and the system will apply search procedures on its knowledge-base, and will find relevant concepts to be used as query-terms. The system is interactive; it can explain to the user why/how a concept was discovered/suggested, and it can back-track and try to find alternatives in case the user rejects a suggested concept. Two versions of the system were developed, utilizing two search and interaction strategies. Experiments will be conducted with the two alternatives in order to find out user preference and to compare performance. Performance will also be compard with an alternative "conventional" approach, which is an On-Line-Thesarus - developed as part of this study.