• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.145-165
• /
• 2023

Recommendation system plays a significant role on relieving difficulties of selecting information among rapidly increasing amount of information caused by the development of the Internet and on efficiently displaying information that fits individual personal interest. In particular, without the help of recommendation system, E-commerce and OTT companies cannot overcome the long-tail phenomenon, a phenomenon in which only popular products are consumed, as the number of products and contents are rapidly increasing. Therefore, the research on recommendation systems is being actively conducted to overcome the phenomenon and to provide information or contents that are aligned with users' individual interests, in order to induce customers to consume various products or contents. Usually, collaborative filtering which utilizes users' historical behavioral data shows better performance than contents-based filtering which utilizes users' preferred contents. However, collaborative filtering can suffer from cold-start problem which occurs when there is lack of users' historical behavioral data. In this paper, hybrid music recommendation system, which can solve cold-start problem, is proposed based on the playlist data of Melon music streaming service that is given by Kakao Arena for music playlist continuation competition. The goal of this research is to use music tracks, that are included in the playlists, and metadata of music tracks and playlists in order to predict other music tracks when the half or whole of the tracks are masked. Therefore, two different recommendation procedures were conducted depending on the two different situations. When music tracks are included in the playlist, LightFM is used in order to utilize the music track list of the playlists and metadata of each music tracks. Then, the result of Item2Vec model, which uses vector embeddings of music tracks, tags and titles for recommendation, is combined with the result of LightFM model to create final recommendation list. When there are no music tracks available in the playlists but only playlists' tags and titles are available, recommendation was made by finding similar playlists based on playlists vectors which was made by the aggregation of FastText pre-trained embedding vectors of tags and titles of each playlists. As a result, not only cold-start problem can be resolved, but also achieved better performance than ALS, BPR and Item2Vec by using the metadata of both music tracks and playlists. In addition, it was found that the LightFM model, which uses only artist information as an item feature, shows the best performance compared to other LightFM models which use other item features of music tracks.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.05a
• /
• pp.285-288
• /
• 2007

The use of commercial finite element analysis software to perform the entire process analysis and springback analysis has increased fast for last decade. Pamstamp2G is one of commercial software to be used widely in the world but it has still not been perfected in the springback prediction accuracy. We must select the combination of input parameters for the highest springback prediction accuracy in Pamstamp2G because springback prediction accuracy is sensitive to input parameters. Then we study the affect of input parameters to use member part for acquiring high springback prediction accuracy in Pamstamp2G. First, we choose important four parameters which are adaptive mesh level at drawing stage and cam flange stage, Gauss integration point number through the thickness and cam offset on basis of experiment. Second, we make a orthogonal array table L82[(7)] which is consist of 8 cases to be combined 4 input parameters, compare to tryout result and select main factors after analyzing affect factors of input parameters by Taguchi's method in 6 sigma. Third, we simulate after changing more detail the conditions of parameters to have big affect. At last, we find the best combination of input parameters for the highest springback prediction accuracy in Pamstamp2G. The results of the study provide the selection of input parameters to Pamstamp2G users who want to Increase the springback prediction accuracy.

• Journal of the HCI Society of Korea
• /
• v.9 no.2
• /
• pp.13-21
• /
• 2014

Jump-rope is a simple and effective exercise, but its intensive exercise load and monotonous pattern make it difficult to perform consistent workout. On the other hand, jumping rope accompanies large amount of kinetic energy which can be converted into electrical energy. In this study, we designed and implemented a self-powered jump-rope which can support the low-power embedded Bluetooth system inside it. The embedded system wirelessly transmits the acceleration data measured during jumping-rope exercise to a smartphone. We also developed a smartphone app which can count the number of jumps and provide real-time feedback with sound and animated graphic effects in a game context. Pilot test using the prototype smart jump-rope verified that it can be useful to motivation for the jump-rope exercise and make the exercise more effective by providing users with precise information about their exercise. We expect that the developed self-powered jump-rope will change the exercise from an intensive physical activity into electricity-generating fun experience combined with smartphone game, which maximize the benefit of the consistent jump-rope exercise.

• Journal of Advanced Navigation Technology
• /
• v.16 no.6
• /
• pp.988-996
• /
• 2012

Assuming perfect channel state information (CSI), the conventional interference alignment (IA) algorithm in the uplink cellular system suppresses inter-cell interference (ICI) by aligning ICI to a randomly selected reference vector. However, IA in practice relies on limited feedback between base stations and users, resulting in residual ICI. In this paper, we propose the optimization of the reference vector that minimizes the upper-bound of residual ICI power. Secondly, the iterative IA that designs the direction of transmit and receive filter is proposed to minimize the residual ICI as well as maximize the desired signals. Moreover, we propose the user scheduling method combined with proposed IA schemes which provides the multiuser diversity gain in multi-cell environments. Finally, the performance gain of the proposed IA algorithms compared with the existing IA are analyzed and demonstrated by simulation results.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.19 no.4
• /
• pp.352-358
• /
• 2013

The objective of this paper is to introduce on a mobile APP called MAMIS(Marine pollution Accident response Mobile Information System) and it's functions. MAMIS was developed by Korea Coast Guard for marine pollution responder in 2012. Users can get information on marine pollution response easily without being restricted by time and place. MAMIS can be operated by smart phones with Android OS and iOS, both of which are the most popular mobile operating systems in Korea. And it has been developed in the form of hybrid APP which combined the functions of mobile APP and mobile WEB. MAMIS is composed of 9 menus, 5 mobile-based ones and 4 web-based ones. The mobile-based menus are on substance information, clean-up skills, response measures, QR code scanning, and volunteer's safety, and the web-based ones on weather information, response equipment, clean-up materials, and SNS.

• Spatial Information Research
• /
• v.18 no.5
• /
• pp.83-92
• /
• 2010

Recently, as the Geospatial Web is combined with the Semantic Web in order to keep pace with the recent trends of information technology emphasizing interoperability, intelligence and individualization, the Geo Semantic Web was proposed, which is an intelligent geographical information Web service technology that can provide users with suitable information by connecting and integrating various types of spatial information and extensive aspatial information on the Web efficiently. For the Geo Semantic Web service, we need to develop Geo Ontology processing technologies that enable computers to process knowledge and information scattered around in the Web environment automatically. However, standards for Geo Ontology processing technologies have nod been established yet, and standardization organizations and various groups and agencies are conducting relevant studies. This paper analyzed various base theories and technologies related to Geo Ontology and developed a Geo Semantic Web system. The Geo Semantic Web system comprises Query Processing Manager that analyzes and processes Geo Semantic queries and manages sessions, Ontology Manager that generates and queries Geo Ontology and extracts spatial/aspatial data, and Clients. Finally, this paper proved the utility of the Geo Semantic Web system by applying it to a hypothetical scenario where Geo Semantic queries are required.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.3
• /
• pp.73-80
• /
• 2020

In this paper, we propose a robust execution scheme for Ethereum blockchain application services which provide continuous services and support recovery even in the case of failures of those services. As of now, blockchain services are rapidly expanding to all industries and being combined with various infrastructure services of public institutions. But if these services fail in disastrous situations such as earthquakes, floods and terrors or various hacking attacks, the aftermath is very serious and its side effects are difficult to assess. To resolve this issue, we develop the service registry as a smart contract of the Ethereum blockchain, which provides useful information on the services to users even in disasters. With the help of the service registry, we also present a method of replicating services on the basis of the ETCD distributed storage system. The proposed scheme is confirmed by the test service developed by the proposed techniques.

• Journal of Internet Computing and Services
• /
• v.16 no.6
• /
• pp.79-88
• /
• 2015

The web search engines are exposed to the issue of uncertainty because of ambiguous queries, being input for retrieving the accurate results. Ambiguous queries constitute a significant fraction of such instances and pose real challenges to web search engines. Moreover, web search has created an interest for the researchers to deal with search by considering context in terms of location perspective. Our proposed disambiguation approach is designed to improve user experience by using context in terms of location relevance with the document relevance. The aim is that providing the user a comprehensive location perspective of a topic is informative than retrieving a result that only contains temporal or context information. The capacity to use this information in a location manner can be, from a user perspective, potentially useful for several tasks, including user query understanding or clustering based on location. In order to carry out the approach, we developed a Java based prototype to derive the contextual information from the web results based on the queries from the well-known datasets. Among those results, queries are further classified in order to perform search in a broad way. After the result provision to users and the selection made by them, feedback is recorded implicitly to improve the web search based on contextual information. The experiment results demonstrate the outstanding performance of our approach in terms of precision 75%, accuracy 73%; recall 81% and f-measure 78% when compared with generic temporal evaluation approach and furthermore achieved precision 86%, accuracy 71%; recall 67% and f-measure 75% when compared with web document clustering approach.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.23 no.1
• /
• pp.70-78
• /
• 2011

At Haeundae Beach in Busan, people were swept away by the fast-moving rip current and rescued, on August 13th and 15th, 2009 & July 29th and 30th, 2010. In predicting the wave-induced current and consequent tube movement for public safety, the coastal flows and waves are calculated at each time step and grid point by means of systematic interfacing of hydrodynamic and wave models (Lee, 2001). To provide a user-friendly simulation tool for end-users, the forecasting system has been built in a software package called HAECUM. Outputs from the system are viewed as graphs of tube positions with combined current vectors for easy decision of emergency management officials. The tube-wave interaction is taken into account and the traces of swim tube are simulated by using a Lagrangian random walk (Chorin, 1978; Lee, 1994). In this study, we use the Lee's approach (Lee, 1993) in estimating the surface onshore currents due to wave breaking.

• Journal of Korea Multimedia Society
• /
• v.13 no.4
• /
• pp.582-593
• /
• 2010

Recently the commercial value of GIS(geographic information system) has been increased with growing application demands of spatial information in life space. Also, GIS has been expanded to the integrated information system that provides the ease access to map information by public users and also the combined service of GIS map data and various multimedia contents. But several security problems of GIS map data have brought up at GIS industries, such as the illegal copy and distribution of GIS map data. Furthermore, the copyright protection of GIS map data has not been researched yet compared with image and video contents. This paper presents a polyline based watermarking scheme for the copyright protection of GIS vector map. The proposed scheme analyzes the structure of vector map and embeds adaptively the watermark by using the distance distribution of polyline components. From experimental results, we verified that the proposed scheme satisfies the invisibility and the robustness of geometrical attacks.