• Journal of the Korea Convergence Society
• /
• v.12 no.7
• /
• pp.53-60
• /
• 2021

LOD-based recommender systems usually leverage the data available within LOD datasets, such as DBpedia, in order to recommend items(movies, books, music) to the end users. These systems use a semantic similarity algorithm that calculates the degree of matching between pairs of Linked Data resources. In this paper, we proposed a new approach to measuring semantic distance in an LOD-based recommender system by assigning weights converted from user ratings to links in the LOD graph. The semantic distance measurement model proposed in this paper is based on a processing step in which a graph is personalized to a user through weight calculation and a method of applying these weights to LDSD. The Experimental results showed that the proposed method showed higher accuracy compared to other similar methods, and it contributed to the improvement of similarity by expanding the range of semantic distance measurement of the recommender system. As future work, we aim to analyze the impact on the model using different methods of LOD-based similarity measurement.

• Korean Journal of Cognitive Science
• /
• v.3 no.1
• /
• pp.1-24
• /
• 1991

This paper presents the Lexical Ambiguity Resolution System of Korean Language. This system uses Dependency grammar and Collative Semantics. Dependency grammar is used to analyze Korean syntactic dependency. A robust way to analyze a sentence is to establish links between individual words. Collative Semantics investigates the interplay between lexical ambiguity and semantics relations. Collative Semantics consists of sense-frame, semantic vector, collation, and screening. Our system was implemented by C programming language. This system analyzes sentences, discriminates the kinds of semantic relation between pairs of words senses in those sentences, and resolves lexical ambiguity.

• Knowledge Management Research
• /
• v.19 no.3
• /
• pp.47-61
• /
• 2018

A knowledge map, a taxonomy of knowledge repositories, must have capabilities supporting and enhancing knowledge user's activity to search and select proper knowledge for problem-solving. Conventional knowledge maps, however, have been hierarchically categorized, and could not support such activity that must coincide with the user's cognitive process for knowledge utilization. This paper, therefore, aims to verify and develop a methodology to build a networked knowledge map that can support user's activity to search and retrieve proper knowledge based on the referential navigation between content-relevant knowledge. This paper deploys keywords as the semantic information between knowledge, because they can represent the overall contents of a given document, and because they can play the role of semantic information on the link between related documents. By aggregating links between documents, a document network can be formulated: a keyword-based networked knowledge map can be finally built. Domain expert-based validation test was also conducted on a networked knowledge map of 50 research papers, which confirmed the performance of the proposed methodology to be outstanding with respect to the precision and recall.

• The KIPS Transactions:PartD
• /
• v.14D no.1 s.111
• /
• pp.35-44
• /
• 2007

Recently, an increasing in quantity of multimedia data have brought a new problem that expected data should be retrieved fast and exactly. The adequate representation for the multimedia data is the key element for efficient retrieval. For this reason, MPEG-7 standard was established for description of multimedia data. In this paper, we propose a new approach to metadata production. The user can decompose a given content into units and easily annotate each unit by adding basic Information such as time, place, etc. as well as classification information such as event, relationship, etc. according to the MPEG-7 standard. The objective is to build automatically a pure semantic description; the nodes are the events and the links are the graphs which describe the relationships among the events. Finally, we have implemented an annotation tool(SMAT) for semantic description based on proposed technique and assess some of the experiment results. In conclusion, we ran say that the proposod annotation tool is characterized by two important proprieties : reusability and extendibility.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.3
• /
• pp.586-593
• /
• 2009

As most of the data configuration at distributed environment has a tree structure following the hierarchical classification, relative data retrieve is limited. Among these data, the data stored in a database has a problem in integration and efficient retrieve. Accordingly, we suggest the system that uses XMDR for distributed database integration and links XMDR to TopicMap for efficient retrieve of knowledge expressed hierarchically. We proposes a plan for efficient integration retrieve through using the XMDR which is composed of Meta Semantic Ontology, Instance Semantic Ontology and meta location, solves data heterogeneity and metadata heterogeneity problem and integrates them, and replaces the occurrence of the TopicMap with the Meta Location of the XMDR, which expresses the resource location of TopicMap by linking Meta Semantic Ontology and Instance Semantic Ontology of XMDR to the TopicMap.

• KIPS Transactions on Computer and Communication Systems
• /
• v.12 no.8
• /
• pp.243-252
• /
• 2023

Satellite imageries are at a greatest importance for land cover examining. Numerous studies have been conducted with satellite images and uses semantic segmentation techniques to extract information which has higher altitude viewpoint. The device which is taking these images must employee wireless communication links to send them to receiving ground stations. Wireless communications from a satellite are inevitably affected due to transmission errors. Evidently images which are being transmitted are distorted because of the information loss. Current semantic segmentation techniques are not made for segmenting distorted images. Traditional image enhancement methods have their own limitations when they are used for satellite images enhancement. This paper proposes an auto-encoder based image pre-enhancing method for satellite images. As a distorted satellite images dataset, images received from a real radio transmitter were used. Training process of the proposed auto-encoder was done by letting it learn to produce a proper approximation of the source image which was sent by the image transmitter. Unlike traditional image enhancing methods, the proposed method was able to provide more applicable image to a segmentation model. Results showed that by using the proposed pre-enhancing technique, segmentation results have been greatly improved. Enhancements made to the aerial images are contributed the correct assessment of land resources.

• Language and Information
• /
• v.12 no.1
• /
• pp.27-65
• /
• 2008

This paper presents a set of methodologies for aligning hypernym-hyponym noun pairs between Korean and English, based on the EuroWordNet approach. Following the methods conducted in EuroWordNet, our approach makes extensive use of WordNet in four steps of the building process: 1) Monolingual dictionaries have been used to extract proper hypernym-hyponym noun pairs, 2) bilingual dictionary has converted the extracted pairs, 3) Word Net has been used as a backbone of alignment criteria, and 4) WordNet has been used to select the most similar pair among the candidates. The importance of this study lies not only on enriching semantic links between two languages, but also on integrating lexical resources based on a language specific and dependent structure. Our approaches are aimed at building an accurate and detailed lexical resource with proper measures rather than at fast development of generic one using NLP technique.

• The Journal of Korean Association of Computer Education
• /
• v.7 no.6
• /
• pp.47-58
• /
• 2004

To generate individualized and adaptive course, it's required to have the foundation structure in which learning objects are connected with each other with logical relevances. Each learner can have peculiar learning path at each point of time of learning through the logical relevancy between those learning objects and various links, considering individual learner. The purpose of this study is to design a learning object-basis individualized learning system structure, considering semantic sequencing by learning task types. It is our understanding that the individualized learning system design model of this study, considering the relevancy between learning objects, can be a fresh trial to accommodate semantic learning and true educational spirits in e-Learning at this point of time when criticism, such as the learning object based course design is simply a collection of meaningless objects, etc., is becoming influential.

• Journal of Korean Academy of Nursing
• /
• v.51 no.1
• /
• pp.68-79
• /
• 2021

Purpose: This study aimed to analyze the mass and social media contents and structures related to particulate matter before and after the policy enforcement of the comprehensive countermeasures for particulate matter, derive nursing implications, and provide a basis for designing health policies. Methods: After crawling online news articles and posts on social networking sites before and after policy enforcement with particulate matter as keywords, we conducted topic and semantic network analysis using TEXTOM, R, and UCINET 6. Results: In topic analysis, behavior tips was the common main topic in both media before and after the policy enforcement. After the policy enforcement, influence on health disappeared from the main topics due to increased reports about reduction measures and government in mass media, whereas influence on health appeared as the main topic in social media. However semantic network analysis confirmed that social media had much number of nodes and links and lower centrality than mass media, leaving substantial information that was not organically connected and unstructured. Conclusion: Understanding of particulate matter policy and implications influence health, as well as gaps in the needs and use of health information, should be integrated with leadership and supports in the nurses' care of vulnerable patients and public health promotion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.589-590
• /
• 2010

All these images consist a considerable database. What's more, the semantic meanings of images are well presented by the surrounding text and links. But only a small minority of these images have precise assigned keyphrases, and manually assigning keyphrases to existing images is very laborious. Therefore it is highly desirable to automate the keyphrases extraction process. In this paper, we first introduce WWW image annotation methods, based on low level features, page tags, overall word frequency and local word frequency. Then we put forward our method of multi-cues integration image annotation. Also, show multi-cue image annotation method is more superior than other method through an experiment.