• Journal of the Korea Society of Computer and Information
• /
• v.28 no.9
• /
• pp.167-176
• /
• 2023

In this paper, we designed and implemented a graph assessment module that can evaluate graphs in an programming assessment system based on text and numbers. The assessment method of the graph assessment module is self-evaluation that outputs two graphs generated by codes submitted by learners and by answers, automatic-evaluation that converts each graph image into an array, and gives feedback if it is wrong. The data used to generate the graph can be inputted directly or used from external data, and the method of generatng graph that can be evaluated is MATLAB style in matplotlib, and the graph shape that can be evaluated is presented in mathematics and curriculum. Through expert review, it was confirmed that the content elements of the assessment module, the possibility of learning, and the validity of the learner's needs were met. The graph assessment module developed in this study has expanded the evaluation area of the programming automatic asssessment system and is expected to help students learn data visualization.

• Journal of Korea Multimedia Society
• /
• v.12 no.7
• /
• pp.893-902
• /
• 2009

Many People are collecting and managing variable information(Image, Graphic, Animation, Text, music files etc.) about personal interests and holding them in common. Most users are using Microsoft Explorer to make a folder and classify many files. but It's difficult to understand the relation of the data instinctively. To resolve this problem, we adopt information visualization method (especially tree-graph control interface). We suggest an interface that all user can drawing a Graph easily and rapidly. So user can see the relations of their data instinctively and control the relation directly with our sketch-based interface.

• Journal of Convergence for Information Technology
• /
• v.10 no.7
• /
• pp.41-48
• /
• 2020

Recently, the spreading business of AMI (Advanced Metering Infrastructure) remote metering systems in various regions of the country has been activated, and it provides various metering functions such as two-way communication and security plan functions for power demand management. Current AMI system is difficult to analyze based on the existing RDB(Relational Database) due to the increase in the size of new internal IoT devices and networks. This study proposes a new GDB(Graph Database) based failure analysis method that utilizes existing RDB data. It analyzes the correlation of new failure patterns through accumulated data such as internal thresholds and status values. As a result of GDB-based simulation, it was confirmed that RDB can predict to a new obstacle pattern that was difficult to analyze.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.1
• /
• pp.33-45
• /
• 2011

In this paper, we present a method for extracting video objects efficiently by using the modified graph cut algorithm based on contour information. First, we extract objects at the first frame by an automatic object extraction algorithm or the user interaction. To estimate the objects' contours at the current frame, motion information of objects' contour in the previous frame is analyzed. Block-based histogram back-projection is conducted along the estimated contour point. Each color model of objects and background can be generated from back-projection images. The probabilities of links between neighboring pixels are decided by the logarithmic based distance transform map obtained from the estimated contour image. Energy of the graph is defined by predefined color models and logarithmic distance transform map. Finally, the object is extracted by minimizing the energy. Experimental results of various test images show that our algorithm works more accurately than other methods.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.2
• /
• pp.179-186
• /
• 2021

We have been developed the smart tourism app and the Instagram and YouTube contents to provide personalized tourism information and travel product information to individual tourists. In this paper, we develop a rule-based smart tourism chatbot with the khaiii (Kakao Hangul Analyzer III) morphological analyzer and Neo4J graph database. In the proposed chatbot system, we use a morpheme analyzer, a proper noun dictionary including tourist destination names, and a general noun dictionary including containing frequently used words in tourist information search to understand the intention of the user's question. The tourism knowledge base built using the Neo4J graph database provides adequate answers to tourists' questions. In this paper, the nodes of Neo4J are Area based on tourist destination address, Contents with property of tourist information, and Service including service attribute data frequently used for search. A Neo4J query is created based on the result of analyzing the intention of a tourist's question with the property of nodes and relationships in Neo4J database. An answer to the question is made by searching in the tourism knowledge base. In this paper, we create the tourism knowledge base using more than 1300 Jeju tourism information used in the smart tourism app. We plan to develop a multilingual smart tour chatbot using the named entity recognition (NER), intention classification using conditional random field(CRF), and transfer learning using the pretrained language models.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.24 no.5
• /
• pp.567-575
• /
• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39A no.12
• /
• pp.729-738
• /
• 2014

In this paper, we propose interference avoidance resource allocation scheme based on graph-coloring algorithm to introduce performance gain using spatial reuse in D2D (Device-to-Device) system. By assigning multiple D2D pairs to a single D2D resource, interference from neighboring D2D pairs is inevitable, which leads to performance degradation. Therefore, we first introduce the feedback information and the method considering the amount of information that can be practically provided by a D2D pair. Then, we propose how to construct a graph, which is corresponding to the D2D system, using the feedback information and adopt a graph-coloring algorithm to efficiently avoid interference. Simulation results show that the proposed resource allocation scheme outperforms traditional resource allocation schemes in both overall sum rate and spectral efficiency of D2D system while reducing the outage probability. Moreover, the outage probability, which indicates a failure rate of D2D communication, can be reduced by adopting the proposed scheme.

• Journal of KIISE
• /
• v.42 no.10
• /
• pp.1222-1230
• /
• 2015

Segmentation of the anterior cruciate ligament (ACL) in knee MRI remains a challenging task due to its inhomogeneous signal intensity and low contrast with surrounding soft tissues. In this paper, we propose a multi-atlas-based segmentation of the ACL in knee MRI with locally-aligned probabilistic atlas (PA) in an iterative graph cuts framework. First, a novel PA generation method is proposed with global and local multi-atlas alignment by means of rigid registration. Second, with the generated PA, segmentation of the ACL is performed by maximum-aposteriori (MAP) estimation and then by graph cuts. Third, refinement of ACL segmentation is performed by improving shape prior through mask-based PA generation and iterative graph cuts. Experiments were performed with a Dice similarity coefficients of 75.0%, an average surface distance of 1.7 pixels, and a root mean squared distance of 2.7 pixels, which increased accuracy by 12.8%, 22.7%, and 22.9%, respectively, from the graph cuts with patient-specific shape constraints.

• Journal of Korea Spatial Information System Society
• /
• v.9 no.2
• /
• pp.25-34
• /
• 2007

Existing approaches that select an order for the join of three or more data streams have always used the simple heuristics. For their disadvantage - only one factor is considered and that is join selectivity or arrival rate, these methods lead to poor performance and inefficiency In some applications. The graph-based sliding window multi -join algorithm with optimal join sequence is proposed in this paper. In this method, sliding window join graph is set up primarily, in which a vertex represents a join operator and an edge indicates the join relationship among sliding windows, also the vertex weight and the edge weight represent the cost of join and the reciprocity of join operators respectively. Then the optimal join order can be found in the graph by using improved MVP algorithm. The final result can be produced by executing the join plan with the nested loop join procedure, The advantages of our algorithm are proved by the performance comparison with existing join algorithms.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.5
• /
• pp.564-568
• /
• 2011

Microblogs became popular information delivery ways due to the spread of smart phones. They have the characteristic of reflecting the interests of users more quickly than other medium. Particularly, in case of the subject which attracts many users, microblogs can supply rich information originated from various information sources. Nevertheless, it has been considered as a hard problem to obtain useful information from microblogs because too much noises are in them. So far, various methods are proposed to extract and track some subjects from particular documents, yet these methods do not work effectively in case of microblogs which consist of short phrases. In this paper, we propose a graph-based topic extraction and partitioning method to understand interests of users about a certain keyword. The proposed method contains the process of generating a keyword graph using the co-occurrences of terms in the microblogs, and the process of splitting the graph by using a network partitioning method. When we applied the proposed method on some keywords. our method shows good performance for finding a topic about the keyword and partitioning the topic into sub-topics.