• Asia pacific journal of information systems
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• v.17 no.2
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• pp.49-81
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• 2007

Research in the IS (Information Systems) outsourcing has focused on the importance of legal contracts and partnerships between vendors and clients. Without detailed legal contracts, there is no guarantee that an outsourcing vendor would not indulge in self-serving behavior. In addition, partnerships can supplement legal contracts in managing the relationship between clients and vendors legal contracts by itself cannot deal with all the complexity and ambiguity involved with IS outsourcing relationships. In this paper, we introduce a psychological contract (between client and vendor) as an important variable for IS outsourcing success. A psychological contract refers to individual's mental beliefs about his or her mutual obligations in a contractual relationship (Rousseau, 1995). A psychological contract emerges when one party believes that a promise of future returns has been made, a contribution has been given, and thus, an obligation has been created to provide future benefits (Rousseau, 1989). An employmentpsychological contract, which is a widespread concept in psychology, refers to employer and employee expectations of the employment relationship, i.e. mutual obligations, values, expectations and aspirations that operate over and above the formal contract of employment (Smithson and Lewis, 2003). Similar to the psychological contract between an employer and employee, IS outsourcing involves a contract and a set of mutual obligations between client and vendor (Ho et al., 2003). Given the lack of prior research on psychological contracts in the IS outsourcing context, we extend such studies and give insights through investigating the role of psychological contracts between client and vendor. Psychological contract theory offers highly relevant and sound theoretical lens for studying IS outsourcing management because of its six distinctive principles: (1) it focuses on mutual (rather than one-sided) obligations between contractual parties, (2) it's more comprehensive than the concept of legal contract, (3) it's an individual-level construct, (4) it changes over time, (5) it affects organizational behaviors, and (6) it's susceptible to organizational factors (Koh et al., 2004; Rousseau, 1996; Coyle-Shapiro, 2000). The aim of this paper is to put the concept, psychological contract commitment (PCC), under the spotlight, by finding out its mediating effects between legal contracts/partnerships and IS outsourcing success. Our interest is in the psychological contract commitment (PCC) or commitment to psychological contracts, which is the extent to which a partner consistently and deeply concerns with what the counter-party believes as obligations during the IS project. The basic premise for the hypothesized relationship between PCC and success is that for outsourcing success, client and vendor should continually commit to mutual obligations in which both parties believe, rather than to only explicit obligations. The psychological contract commitment playsa pivotal role in evaluating a counter-party because it reflects what one party really expects from the other. If one party consistently shows high commitment to psychological contracts, the other party would evaluate it positively. This will increase positive reciprocation efforts of the other party, thus leading to successful outsourcing outcomes (McNeeley and Meglino, 1994). We have used matched sample data for this research. We have collected three responses from each set of a client and a vendor firm: a project manager of the client firm, a project member from the vendor firm with whom the project manager cooperated, and an end-user of the client company who actually used the outsourced information systems. Special caution was given to the data collection process to avoid any bias in responses. We first sent three types of questionnaires (A, Band C) to each project manager of the client firm, asking him/her to answer the first type of questionnaires (A).

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.147-157
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• 2010

With the immergence of the iPhone, the interest in Smartphones is getting higher as services can be provided directly between service providers and consumers without the network operators. As the number of international tourists increase, individual tourists are also increasing. According to the WTO's (World Tourism Organization) prediction, the number of international tourists will be 1.56 billion in 2020,and the average growth rate will be 4.1% a year. Chinese tourists, in particular, are increasing rapidly and about 100 million will travel the world in 2020. In 2009, about 7.8 million foreign tourists visited Korea and the Ministry of Culture, Sports and Tourism is trying to attract 12 million foreign tourists in 2014. A research institute carried out a survey targeting foreign tourists and the survey results showed that they felt uncomfortable with communication (about 55.8%) and directional signs (about 21.4%) when they traveled in Korea. To solve this inconvenience for foreign tourists, multilingual servicesfor traffic signs, tour information, shopping information and so forth should be enhanced. The appearance of the Smartphone comes just in time to provide a new service to address these inconveniences. Smartphones are especially useful because every Smartphone has GPS (Global Positioning System) that can provide users' location to the system, making it possible to provide location-based services. For improvement of tourists' convenience, Seoul Metropolitan Government hasinitiated the u-tour service using Kiosks and Smartphones, and several Province Governments have started the u-tourpia project using RFID (Radio Frequency IDentification) and an exclusive device. Even though the u-tour or u-tourpia service used the Smartphone and RFID, the tourist should know the location of the Kiosks and have previous information. So, this service did not give the solution yet. In this paper, I developed a new convenient service which can provide location based information for the individual tourists using GPS, WiFi, and 3G. The service was tested at Insa-dong in Seoul, and the service can provide tour information around the tourist using a push service without user selection. This self-tour service is designed for providing a travel guide service for foreign travelers from the airport to their destination and information about tourist attractions. The system reduced information traffic by constraining receipt of information to tourist themes and locations within a 20m or 40m radius of the device. In this case, service providers can provide targeted, just-in-time services to special customers by sending desired information. For evaluating the implemented system, the contents of 40 gift shops and traditional restaurants in Insa-dong are stored in the CMS (Content Management System). The service program shows a map displaying the current location of the tourist and displays a circle which shows the range to get the tourist information. If there is information for the tourist within range, the information viewer is activated. If there is only a single resultto display, the information viewer pops up directly, and if there are several results, the viewer shows a list of the contents and the user can choose content manually. As aresult, the proposed system can provide location-based tourist information to tourists without previous knowledge of the area. Currently, the GPS has a margin of error (about 10~20m) and this leads the location and information errors. However, because our Government is planning to provide DGPS (Differential GPS) information by DMB (Digital Multimedia Broadcasting) this error will be reduced to within 1m.

• The Journal of Natural Sciences
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• v.10 no.1
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• pp.209-216
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• 1998

The results of the study of diving the 21st century's Korea fashion market into consumer market, fashion market, and a new marketing strategy are as follows. The 21st consumer market is First, a fashion democracy phenomenon. As many people try to leave unconditional fashion following, consumer show a phenomenon to choose and create their own fashion by subjective judgements. Second, a phenomenon of total fashion pursuit. Consumer in the future are likely to put their goals not in differentiating small item products, but considering various fashion elements based on their individuality and sense of value. Third, world quality-oriented. With the improvement of life level, it accomplishes to emphasize consumers' fashion mind on the world wide popular use of materials, quality, design and brand image. Fourth, with the entrance of neo-rationalism, consumers show increasing trends to emphasize wisdom, solidity in goods strategy pursuing high quality fashion and to demand resonable prices. Fifth, concept-oriented. Consumers are changing into pursuing concept appropriate to individual life scene. Prospecting the composition of the 21st century's fashion market, First, sportive casual zone will draw attention more than any other zone. This is because interest in sports will grow according to the increase of leisure time and the expasion of time and space in the 21st century, and also ecology will become the important issue of sports sense because of human beings's natural habit toward nature. Second, the down aging phenomenon will accelerate its speed as a big trend. Third, a retro phenomenon, a concept contrary to digital and high-tech, will become another big trend for its remake, antique, and classic concept in fashion market with ecology trend. New marketing strategy to cope with changing fashion market is as follows. First, with the trend of borderless concept, borders between apparels are becoming vague, for example, they offer custom-made products to consumers. Second, as more enterprises take the way of gorilla and guerrilla where guerrillas who aim at niche market show up will develop. Basically, they think highly of individual creative study, and pursue the scene adherence with high sensitiveness. However this polarization becomes mutually-supplementing relationship showing gorilla's guerilla movement, and guerilla's gorilla high-tech. Third with the development of value retailing, enterprises pursuing mass merchandising of groups called category killers are expanded and amplified to new product fields, and expand business' share. Fourth, using outsourcing, the trend to use exterior function leaving each enterprise's strength by inspecting its own work is gradually strong. Fifth, with the expansion of none store sale, the entrance of the internet and the CD-ROM sales added to communication sales such as catalogues are specified. An eminent American think tank expect that 5-5% of the total sale of clothes and home goods in 2010 will be done by none store sale. Accordingly, to overcome the problems, First international, global level marketing, Second, the improvement of technology, Third, knowledge-creating marketing are needed.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.59-69
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• 2012

As exhibition industry, which is a part of 17 new growth engines of the government, is related to other industries such as tourism, transportation and financial industries. So it has a significant ripple effect on other industries. Exhibition is a knowledge-intensive, eco-friendly and high value-added Industry. Over 13,000 exhibitions are held every year around the world which contributes to getting foreign currency. Exhibition industry is closely related with culture and tourism and could be utilized as local and national development strategies and improve national brand image as well. Many countries try various efforts to invigorate exhibition industry by arranging related laws and support system. In Korea, more than 200 exhibitions are being held every year, but only 2~3 exhibitions are hosted with over 400 exhibitors and except these exhibitions most exhibitions have few foreign exhibitors. The main reason of weakness of domestic trade show is that there are no agencies managing exhibitionrelated statistics and there is no specific and reliable evaluation. This might cause impossibility of providing buyer or seller with reliable data, poor growth of exhibitions in terms of quality and thus service quality of trade shows cannot be improved. Hosting a lot of visitors (Public/Buyer/Exhibitor) is very crucial to the development of domestic exhibition industry. In order to attract many visitors, service quality of exhibition and visitor's satisfaction should be enhanced. For this purpose, a variety of real-time customized services through digital media and the services for creating new customers and retaining existing customers should be provided. In addition, by providing visitors with personalized information services they could manage their time and space efficiently avoiding the complexity of exhibition space. Exhibition industry can have competitiveness and industrial foundation through building up exhibition-related statistics, creating new information and enhancing research ability. Therefore, this paper deals with customized service with visitor's smart-phone at the exhibition space and designing mobile framework which enables exhibition devices to interact with other devices. Mobile server framework is composed of three different systems; multi-server interaction, server, client, display device. By making knowledge pool of exhibition environment, the accumulated data for each visitor can be provided as personalized service. In addition, based on the reaction of visitors each of all information is utilized as customized information and so the cyclic chain structure is designed. Multiple interaction server is designed to have functions of event handling, interaction process between exhibition device and visitor's smart-phone and data management. Client is an application processed by visitor's smart-phone and could be driven on a variety of platforms. Client functions as interface representing customized service for individual visitors and event input and output for simultaneous participation. Exhibition device consists of display system to show visitors contents and information, interaction input-output system to receive event from visitors and input toward action and finally the control system to connect above two systems. The proposed mobile framework in this paper provides individual visitors with customized and active services using their information profile and advanced Knowledge. In addition, user participation service is suggested as well by using interaction connection system between server, client, and exhibition devices. Suggested mobile framework is a technology which could be applied to culture industry such as performance, show and exhibition. Thus, this builds up the foundation to improve visitor's participation in exhibition and bring about development of exhibition industry by raising visitor's interest.

• (The) Research of the performance art and culture
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• no.36
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• pp.693-724
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• 2018

This article was started to find a way for creating a performance out of Gut. In order to find such way, the first thing that had to be done was to organize the Gut performances that had been made until now. It was to organize the existing study on the performances and to seek a different way from it, believing that the virtue of a performance is to 'create diversity'. However, it was not easy to organize the Gut performances, which became full-scale in the 1980s, because they were never organized before. Therefore, based on my direct and indirect experience, I have organized the most important performances in chronological order. Most importantly, as the planners of the performances (can sometimes be a group or an organization instead of an individual) are the ones who make the show possible, I have noted on them with keen interest. The National Folk Art Performance Contests in Korea, Theater 'Space Sarang', The Association of Gut, Theater 'Madangsesil', Seoul Nori Madang, and National Gugak center were the center space and planning body of the Gut performances. Recording the history of Gut is a worthwhile work of its own. However, it is a substantial amount of task to be done with individual effort, and it has to be progressed as a public project in order to promote and spread its value. Therefore, this article raises the need for it. Meanwhile, as stated earlier, this article has recorded the history of Gut performances as a precondition to finding a way to create a performance out of Gut. From the experimental organization of the Gut performances history, I could find out that most of the performances had the people who did Gut as the main body and the method of the Gut performance did not significantly deviate from just reenacting the original Gut at the time of when it was performed. Therefore, I have introduced Shinmyeong, the Nori-Pae (troupe), and TheGwangdae, the Korean Traditional Performance troupe, who create Madangguk from various Gut materials. By refining the wholly complicated performance elements of the Gut, it could escape from the 'reenacting' performance to becoming a material or a metaphor for a whole new performance.

• (The)Study of the Eastern Classic
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• no.50
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• pp.89-120
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• 2013

The concept of virtue seems to be one of the rare cases where the European and the Chinese traditions coincide. The meaning of the Latin word virtus and of Greek $aret{\acute{e}}$ seems to be similar to the Chinese $d{\acute{e}}$德. Most striking in virtue is that it is a capacity for self-realisation through action which is unique to man. On the other hand, there is something physical about it. It is the strength to do something. This strength overcomes the resistance of what is naturally given, it transforms the world, turns the natural world into a human one. In the Chinese tradition, $d{\acute{e}}$ 德, i.e. virtue, is therefore always connected with $da{\grave{o}}$ 道, the totality of natural forces. In the Chinese tradition, as opposed to the European one, virtue is itself considered to be a natural force that is present in man. This force sustains man's connectedness, unity and harmony with the surrounding world. Things exist through the unity of principle理 and ether氣. But the knowledge of this unity is due to principle. Moral and legal norms are shifted totally to the sphere of principle. Therefore their have found the final dissolution from a heroic models. Above all the classical Confucians, but also the other schools, would reply to this that there is nothing more precise than a concrete successful action. Its result fits the world perfectly. The difference is due to the differing interest of ethical thought. In the case of the Confucians the path is more direct. The actor establishes a precise pattern for other actions. Education therefore lies in detailed knowledge about forms of behaviour, not so much in conceptual differentiation. It is quite possible that generalisation may be a methodical prerequisite for success in this endeavour. That problem, too, is discussed. But the success of conceptualisation lies in the successful performance of individual actions, not in shaping actions in accordance with normative concepts.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.65-82
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• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

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