• Information Systems Review
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• v.23 no.3
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• pp.77-96
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• 2021

This research investigates the pivotal role of AI-enabled technologies in vitalizing the local economy. Collaborating with a leading search engine company, we examine the direct and indirect of an AI-based location search service on the success of sampled 7,035 local restaurants in Gangnam area in Seoul. We find that increased use of AI-enabled search and recommendation services significantly improved the selections of previously less-discovered or less-popular restaurants by users, and it also enhanced the stores' overall conversion rates. The main research findings have contributions to extant literature in theorizing the value of AI applications in local economy and have managerial implications for search businesses and local stores by recommending strategic use of AI applications in their businesses that are effective in highly competitive markets.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.247-264
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• 2016

With the rapid acceleration of low-birth rate and population aging, the employment of the neglected groups of people including the middle aged class is a crucial issue in South Korea. In particular, in the 2010s, the number of the middle aged who want to find a new job after retirement age is significantly increasing with the arrival of the retirement time of the baby boom generation (born 1955-1963). Despite the importance of matching jobs to this emerging middle aged class, private job portals as well as the Korean government do not provide any online job service tailored for them. A gigantic amount of job information is available online; however, the current recruiting systems do not meet the demand of the middle aged class as their primary targets are young workers. We are in dire need of a specially designed recruiting system for the middle aged. Meanwhile, when users are searching the desired occupations on the Worknet website, provided by the Korean Ministry of Employment and Labor, users are experiencing discomfort to search for similar jobs because Worknet is providing filtered search results on the basis of exact matches of a preferred job code. Besides, according to our Worknet data analysis, only about 24% of job seekers had landed on a job position consistent with their initial preferred job code while the rest had landed on a position different from their initial preference. To improve the situation, particularly for the middle aged class, we investigate a soft job matching technique by performing the following: 1) we review a user behavior logs of Worknet, which is a public job recruiting system set up by the Korean government and point out key system design implications for the middle aged. Specifically, we analyze the job postings that include preferential tags for the middle aged in order to disclose what types of jobs are in favor of the middle aged; 2) we develope a new occupation classification scheme for the middle aged, Korea Occupation Classification for the Middle-aged (KOCM), based on the similarity between jobs by reorganizing and modifying a general occupation classification scheme. When viewed from the perspective of job placement, an occupation classification scheme is a way to connect the enterprises and job seekers and a basic mechanism for job placement. The key features of KOCM include establishing the Simple Labor category, which is the most requested category by enterprises; and 3) we design MOMA (Middle-aged Occupation Matching Algorithm), which is a hybrid job matching algorithm comprising constraint-based reasoning and case-based reasoning. MOMA incorporates KOCM to expand query to search similar jobs in the database. MOMA utilizes cosine similarity between user requirement and job posting to rank a set of postings in terms of preferred job code, salary, distance, and job type. The developed system using MOMA demonstrates about 20 times of improvement over the hard matching performance. In implementing the algorithm for a web-based application of recruiting system for the middle aged, we also considered the usability issue of making the system easier to use, which is especially important for this particular class of users. That is, we wanted to improve the usability of the system during the job search process for the middle aged users by asking to enter only a few simple and core pieces of information such as preferred job (job code), salary, and (allowable) distance to the working place, enabling the middle aged to find a job suitable to their needs efficiently. The Web site implemented with MOMA should be able to contribute to improving job search of the middle aged class. We also expect the overall approach to be applicable to other groups of people for the improvement of job matching results.

• Journal of KIISE:Software and Applications
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• v.35 no.10
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• pp.608-615
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• 2008

In Knowledge Q&A services where information is created by unspecified users, document quality is an important factor of user satisfaction with search results. Previous work on quality prediction of Knowledge Q&A documents evaluate the quality of documents by using non-textual information, such as click counts and recommendation counts, and focus on enhancing retrieval performance by incorporating the quality measure into retrieval model. Although the non-textual information used in previous work was proven to be useful by experiments, data sparseness problem may occur when predicting the quality of newly created documents with such information. To solve data sparseness problem of non-textual features, this paper proposes new features for document quality prediction, namely text-confidence features, which indicate how trustworthy the content of a document is. The proposed features, extracted directly from the document content, are stable against data sparseness problem, compared to non-textual features that indirectly require participation of service users in order to be collected. Experiments conducted on real world Knowledge Q&A documents suggests that text-confidence features show performance comparable to the non-textual features. We believe the proposed features can be utilized as effective features for document quality prediction and improve the performance of Knowledge Q&A services in the future.

• Journal of the Korean Society of Food Culture
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• v.16 no.2
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• pp.147-157
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• 2001

In order to investigate the eating out behavior of university students, this survey was conducted using the questionaires for 710 students(369 male, 341 female) from 11 universities in Seoul. It was revealed that 39.4% of the subjects spent $60,000{\sim}100,000$ won for monthly eating out cost and 57.8% of them ate out more than once a day. Most of them expended less than 3,500 won for lunch, while 36.5% of them spent $4,000 {\sim}5,000$ won for dinner. Dinner was regarded more important than lunch. Korean foods were the most preferred menu for eating out with friends and fast foods were the second. But Boonsik(snack bar foods), Chinese foods and Japanease foods were rarely selected. Frequency of selecting fast foods was 8 times greater than that of Boonsik. This indicates that the preference of western flavor and the pursuit of convenience is getting more obvious. While dating, western foods were preferred, followed by Korean foods, fast foods. The 80 kinds of foods were reported as favored eating out foods. Although 50 among 80 were Korean foods, the rest of them were Koreanized foreign foods most of those were western style. This may suggest that when the students become adults, they will be much fond of western dish for their dinning out. This tendency of preferring western flavor were much apparent in foods for dinner compared with lunch. In both sexes, the standard of food choice was in the order of taste, price, mood, hygiene, service and brand name. But male students were more conscious of price and service while female students were more concerned about taste and hygiene. Most unsatisfying feature in restaurant was unstable atmosphere for both sexes. Taste was the most important sensory factor in selecting the foods, followed by appearance, smell and texture. Major source of restaurant information was recommendation by friends or relatives. But the use of internet or magazine was negligible. Female students had more positive attitude, compared with male students, in using restaurant information and pursuing eating out for gourmet. The dining out menu of which price ranges about $3,000{\sim}5,000$ won could be preferable foods for most people. Therefore, instead of blaming them for eating too much fast foods, new menus which fit the food preference and affordability of the students should be developed.

• Journal of KIISE:Databases
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• v.37 no.6
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• pp.343-350
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• 2010

We can get answers we want to know via questioning in Knowledge Search Service (KSS) based on Q&A Community. However, it is getting more difficult to find credible documents in enormous documents, since many anonymous users regardless of credibility are participate in answering on the question. In previous works in KSS, researchers evaluated the quality of documents based on textual information, e.g. recommendation count, click count and non-textual information, e.g. answer length, attached data, conjunction count. Then, the evaluation results are used for enhancing search performance. However, the non-textual information has a problem that it is difficult to get enough information by users in the early stage of Q&A. The textual information also has a limitation for evaluating quality because of judgement by partial factors such as answer length, conjunction counts. In this paper, we propose the QualityRank algorithm to improve the problem by textual and non-textual information. This algorithm ranks the relevant and credible answers by considering textual/non-textual information and user centrality based on Social Network Analysis(SNA). Based on experimental validation we can confirm that the results by our algorithm is improved than those of textual/non-textual in terms of ranking performance.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.1-23
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• 2011

The contextual subjective well-being (SWB) of context-aware system users can be very helpful in recommending relevant mental health services, especially for those who struggle with mental illness due to a metabolic syndrome or melancholia. Self-surveying measuring or auto-sensing methods have been suggested to monitor users' SWB. However, self-surveying measuring method is not inappropriate for a context-aware service due to requesting personal data in a manual and hence obtrusive manner. Moreover, auto-sensing methods still suffer from accuracy problem to be applied in mental health services. Hence, the purpose of this paper is to propose a contextual SWB estimation method to estimate the user's mental health in unobtrusive and accurate manners. This method is timely in that it acquires context data from the user's literal responses, which expose their temporal feeling. In particular, we developed a measuring method based on exposed feeling verbs and degree adverbs in chat and other text-based communications which show anger or negative feelings. Based on the proposed contextual SWB degree estimation method, we developed an idea of well-being life care recommendation. From the experiment with actual drivers, we demonstrated that the proposed method accurately estimate the user's degree of negative feelings even though it does not require a self-survey.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.309-314
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• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Journal of the Korean Society for Railway
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• v.10 no.6
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• pp.723-729
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• 2007

The Ministry of Environment established a guide line in December 2006, "Indoor Air Quality Management guidelines in Public Facilities." As the items of the guideline, $CO_2$ (Carbon dioxide) and PM10 (particulate matter) is shown to Level 1 and 2. Therefore trains and subways are included. There are a lot of tunnels by the lay of mountains on KTX (Korean Train Express) service. HVAC (Heating Ventilating and Air-conditioning)-pressurization equipment on KTX is various functioning flaps blocking outside pressure waves. At that time, the fresh air is blocked by flap operation and the air is circulated by return air. In this study, we measured the time series of $CO_2$ and PM10 concentrations in the KTX passenger cabin during the train service of Gyongbu line (Seoul-Busan) and Honan line (Yongsan-Mokpo) from July 2006. Also, analyzed the air quality by operation of KTX HVAC-pressurization equipment in tunnel passing point. As a result, PM10 concentration was totally lower than the regulation values. However, $CO_2$ was highly correlated with several tunnels, such as Oksan-Otan, Godeung-Hyudae and Gaechak-Iijik tunnel. but, the indoor air quality of KTX train have been proved satisfy the recommendation the Ministry of Environment guidelines.

• The Korean Society of Law and Medicine
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• v.10 no.2
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• pp.343-405
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• 2009

This paper is to discuss essential business of hospital business. While the labor world and ILO made continuous recommendation for improvements towards the compulsory arbitration system along with the controversy over unconstitutionality of the system, the Constitutional Court ruled that the system is constitutional on December 23, 1996(90hunba19) and on May 15, 2003 (2001hunga31). Despite this decision from the Constitutional Court, there has been much controversy over whether the compulsory arbitration system infringes the rights of collective action against the principle of trade union & labor relations adjustment which allows Commissioner of the Labor Relations Commission to decide on submission of arbitration by virtue of his/her authority in case where industrial disputes take place in the essential public-service businesses. The revision on the above provision was closely examined from the year 2003 and an agreement was made on the abolition of the compulsory arbitration system and the introduction of essential business with a grand compromise among labor unions, employers and the government on September 11, 2006 followed by revision(Essential business system enacted on January 1, 2008) of the Trade Union & Labor Relations Adjustment Act on December 30 in the same year. Accordingly, in order to perform the essential business, parties to labor relations must have an agreement or obtain a decision by the Labor Relations Commission before taking industrial actions. This paper firstly examined the concept of essential public-service businesses and essential business, legal meaning of essential business, procedures for making agreement and decision and legal effects. Secondly it intensively explored a theory against the principle of the legality which was raised from some part of society. In other words, it is claimed that a theory against the principle of the legality is not consistent with the rule of legislation and some abstract wording is against void for vagueness doctrine because part of crime constitution requirements is delegated to the Presidential Decree or to consultation among parties to labor relations. But analysis on the rule of legislation and void for vagueness doctrine reflected in the decision by the Constitutional Court led that argument for a theory against the principle of the legality is not reasonable. Close examination was done on a formal act of essential business agreement and necessity of prior agreement before submission of decision to the Labor Relations Commission which might have difficulties in performing work. In addition, an example agreement on hospital essential business is attached to help you understand this paper better.

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.141-148
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• 2014

As the quality of the medical treatment service provided by large hospitals grow, the number of patients utilizing the facilities is increasing dramatically. Various studies such as order communication system and treatment guidance system are under their process in order to shorten the waiting time for patients. However, the existing methods assign the treatments in successive order without recognizing the situation of each treatment, therefore increasing a patient's standby time at a hospital. This paper proposes a context-aware treatment guidance system, which recognizes the previously undermined estimated waiting time of each treatment for a patient and recommends a treatment with shorter estimated sojourn time first. This context-aware treatment guidance system provides detailed information of treatment services based on the recommended order of treatments to a patient's smartphone. By utilizing the context-aware treatment guidance system introduced in this paper, patients can reduce their standby time at hospitals to the minimum while hospitals can efficiently service more patients at the same amount of time. The proposed context-aware treatment guidance system proves to be outstanding in treatment order recommendation through comparisons to previously used methods.