• Title/Summary/Keyword: 데이터 편중

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Methods Comparison: Enhancing Diversity for Personalized Recommendation with Practical E-Commerce Data

  • Paik, Juryon
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.9
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    • pp.59-68
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    • 2022
  • A recommender system covers users, searches the items or services which users will like, and let users purchase them. Because recommendations from a recommender system are predictions of users' preferences for the items which they do not purchase yet, it is rarely possible to be drawn a perfect answer. An evaluation has been conducted to determine whether a prediction is right or not. However, it can be lower user's satisfaction if a recommender system focuses on only the preferences, that is caused by a 'filter bubble effect'. The filter bubble effect is an algorithmic bias that skews or limits the information an individual user sees on the recommended list. It is the reason why multiple metrics are required to evaluate recommender systems, and a diversity metrics is mainly used for it. In this paper, we compare three different methods for enhancing diversity for personalized recommendation - bin packing, weighted random choice, greedy re-ranking - with a practical e-commerce data acquired from a fashion shopping mall. Besides, we present the difference between experimental results and F1 scores.

Comparative Analysis of Low Fertility Response Policies (Focusing on Unstructured Data on Parental Leave and Child Allowance) (저출산 대응 정책 비교분석 (육아휴직과 아동수당의 비정형 데이터 중심으로))

  • Eun-Young Keum;Do-Hee Kim
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.5
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    • pp.769-778
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    • 2023
  • This study compared and analyzed parental leave and child allowance, two major policies among solutions to the current serious low fertility rate problem, using unstructured data, and sought future directions and implications for related response policies based on this. The collection keywords were "low fertility + parental leave" and "low fertility + child allowance", and data analysis was conducted in the following order: text frequency analysis, centrality analysis, network visualization, and CONCOR analysis. As a result of the analysis, first, parental leave was found to be a realistic and practical policy in response to low fertility rates, as data analysis showed more diverse and systematic discussions than child allowance. Second, in terms of child allowance, data analysis showed that there was a high level of information and interest in the cash grant benefit system, including child allowance, but there were no other unique features or active discussions. As a future improvement plan, both policies need to utilize the existing system. First, parental leave requires improvement in the working environment and blind spots in order to expand the system, and second, child allowance requires a change in the form of payment that deviates from the uniform and biased system. should be sought, and it was proposed to expand the target age.

Development of Overseas Construction Big Issues based on Analysis of Big Data (빅 데이터 분석을 통한 해외건설 빅 이슈 개발)

  • Park, Hwanpyo;Han, Jaegoo
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.3
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    • pp.89-96
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    • 2018
  • This study derived big issues in overseas construction through big data analysis. To derive big issues in overseas construction, candidate groups of big issues were identified through big data analysis targeting 53,759 issues including 39,436 issues from major portal sites, 10,387 issues from daily newspapers, and 336 issues in construction magazines from Oct. 1, 2016 to Sep. 30, 2017. The main results are as follows: First, the main issues of overseas construction for the past one year showed that markets were concentrated in Middle East Asia and most of them were low-price order plant projects, which revealed the limitations. Although orders of overseas construction were slightly upward in the first half of 2017 compared to previous year, overseas construction orders are still unstable due to uncertainties in the international affairs and drops in oil prices. Second, the interest topics based on the 8th core keywords of overseas construction among the overseas construction issues for the past one year showed that region (29.9%), corporation environment (22.0%), profitability (17.0%), organizations (15.1%), projects (5.2%), market environment (3.6%), policy and system (3.6%), and education (3.5%) in the order of interest. Third, 10 core issues that have expandability and persistence of discourse were extracted out of 30 issue candidates with regard to eight keywords. Based on the extracted issues, detailed analysis on each of the core issues in overseas construction and correlation analysis between 10 core issues were conducted.

Critical Consideration on the Women Leaders DB System -Focusing on Incheon case- (여성 인재 DB에 대한 비판적 고찰 -인천 사례를 중심으로-)

  • Hong, Hee-Jeong;Hong, Sung-Hyun
    • The Journal of the Korea Contents Association
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    • v.17 no.4
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    • pp.478-487
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    • 2017
  • In recent years, developed countries have begun to pay attention to female workers through work-family balance in order to solve the problem of low fertility and aging. Korea has been building and running a women leaders database (hereafter, women leaders DB) centered on the female professionals since 2011. In particular, the Incheon women leader DB, which was built by Incheon city in 2009, is a classic example. As of 2015, about 2,735 people are registered in Incheon Women Leaders DB and it is systematically creating the database such as age, education, career years, major, occupation, and certification. However, there are administrative problems such as unspecified definition on professionalism and data trust issues including data entry, and DB personnels are concentrated in specific fields. Also, in the case of certification proving expertise, the utilization problem has been revealed including inclusion of private certification not yet verified. In order to solve these problems, we first need to clarify the concept of women leaders and establish the standard. The second is the improvement of data consistency through DB reorganization, and third is to build a system through continuous and active public relations that is used by both job seekers and recruiters.

T-Commerce Sale Prediction Using Deep Learning and Statistical Model (딥러닝과 통계 모델을 이용한 T-커머스 매출 예측)

  • Kim, Injung;Na, Kihyun;Yang, Sohee;Jang, Jaemin;Kim, Yunjong;Shin, Wonyoung;Kim, Deokjung
    • Journal of KIISE
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    • v.44 no.8
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    • pp.803-812
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    • 2017
  • T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.

A Cell-based Indexing for Managing Current Location Information of Moving Objects (이동객체의 현재 위치정보 관리를 위한 셀 기반 색인 기법)

  • Lee, Eung-Jae;Lee, Yang-Koo;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.11D no.6
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    • pp.1221-1230
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    • 2004
  • In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.

A Study on the Production of Science and Technology Knowledge in North Korea through International Academic Papers (국제학술논문을 통해 본 북한의 과학기술 지식생산에 관한 연구)

  • Noh, Kyung-Ran;Kim, Eun-Jeong;Choi, Hyun-Kyoo
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.27 no.4
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    • pp.205-227
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    • 2016
  • The research analyzed the collaborative research network based on the data of international academic papers in order to understand the structure of production of scientific knowledge by North Korean scientists. According to the analysis results, the subject areas of research were concentrated on basic science fields such as physics, mathematics and chemistry. The main collaborative research collaboration with North Korea is China, and the phenomenon has become stronger since Kim Jong Eun era. Major joint research in physics has moved from Germany to China. Among the research institutions that actively engaged in academic activities, KIM IL SUNG UNIV, ACAD SCI DPRK, KIM CHAEK UNIV TECHNOL, and UNIV SCI among 32 research institutes belonging to North Korean researchers who published international academic papers.

An Analysis on the Change Pattern of Spatio-Temporal Land Price in Gongju City Using the Geostatistical Methods (공간통계를 이용한 공주시의 시공간적 지가변화패턴 분석)

  • Kim, Jung-Hee
    • Journal of Korean Society for Geospatial Information Science
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    • v.20 no.1
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    • pp.93-99
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    • 2012
  • This study aims to identify spatio-temporal land price change pattern in Gongju city including the area incorporated and surrounding area depending on the Multifunctional Administrative City Construction. For this, GIS data was built by calculating the average land price each 209 Dong and Ri by the time of the year 2000, 2005 and 2010 based on. The first, the change in the land price was to identify in the 5-year intervals through a kriging interpolation as a kind of geostatistical techniques. The second, a trend analysis was conducted to know directional change pattern of the east-west axis and the north-south axis. Finally, the weighted mean center was calculated by the land price at a weight to examine moving direction on the center point of land price, point of view. The result is that the land price change pattern appeared visible higher growth on the eastern built in the Multifunctional Administrative City, moving direction on the center point of the land price appeared that the phenomenon was concentrated in the northeastern area.

A Study on the Navigation Signal Characteristics of China Beidou Satellite Navigation System (중국의 BeiDou 위성항법시스템의 항법신호 분석에 관한 연구)

  • Ko, Kwang-Soob;Choi, Chang-Mook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.8
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    • pp.1951-1958
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    • 2015
  • The paper is focused on not only the system characteristics of BeiDou, China GNSS, but also the statistic analysis based on its real data received from the BeiDou's satellite navigation messages. The 6-7 satellites, which are more than minimum number of 4 satellites to obtain 3-D position, are available for receiving navigation signal in stable case. It was also verified that the available satellites are deviated to specific coordinate and their signals are still unstable. Only as long as the received signal with the high stability, the precision of the BeiDou navigation satellite navigation system was identified with 5m level in deviation. The Beidou system is expected to be rising as a darkhorse in the future of the global satellite navigation area.

A Cyclic Sliced Partitioning Method for Packing High-dimensional Data (고차원 데이타 패킹을 위한 주기적 편중 분할 방법)

  • 김태완;이기준
    • Journal of KIISE:Databases
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    • v.31 no.2
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    • pp.122-131
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    • 2004
  • Traditional works on indexing have been suggested for low dimensional data under dynamic environments. But recent database applications require efficient processing of huge sire of high dimensional data under static environments. Thus many indexing strategies suggested especially in partitioning ones do not adapt to these new environments. In our study, we point out these facts and propose a new partitioning strategy, which complies with new applications' requirements and is derived from analysis. As a preliminary step to propose our method, we apply a packing technique on the one hand and exploit observations on the Minkowski-sum cost model on the other, under uniform data distribution. Observations predict that unbalanced partitioning strategy may be more query-efficient than balanced partitioning strategy for high dimensional data. Thus we propose our method, called CSP (Cyclic Spliced Partitioning method). Analysis on this method explicitly suggests metrics on how to partition high dimensional data. By the cost model, simulations, and experiments, we show excellent performance of our method over balanced strategy. By experimental studies on other indices and packing methods, we also show the superiority of our method.