• Title/Summary/Keyword: 순차패턴 분석

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Characterization of EXT4 Filesystem Accesses for Android Web Browser (안드로이드 웹 브라우저의 EXT4에 대한 파일시스템의 접근 특성 분석)

  • Lee, Joon-Woo;Kim, Kang-Hee
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06a
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    • pp.89-91
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    • 2012
  • 플래시 저장장치는 순차 쓰기패턴에 높은 성능을 보이고, 랜덤 쓰기패턴에 낮은 성능을 보인다고 알려져 있다. 그러나 실제 응용 프로그램은 동작 방식에 따라 복합적인 패턴을 보일 수 있다. 본 논문은 대표적인 모바일 응용으로서 웹 브라우저 응용의 파일시스템 접근 특성을 정량적으로 분석하고자 한다. 최근에 안드로이드 스마트 폰에 채택된 Ext4 파일시스템을 기준으로 웹 브라우저 응용의 파일시스템 요청들을 성능개선점을 지적하고자 한다.

Situational Awareness and User Intention system with Behavior patterns Analysis of Voice Phishing (보이스 피싱 행동 패턴 분석을 통한 상황 인지 및 사용자 의도 파악 시스템)

  • Cho, Dan-Bi;Kang, Seung-Shik
    • Proceedings of the Korea Information Processing Society Conference
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    • 2019.10a
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    • pp.855-857
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    • 2019
  • 개인 정보의 확산 및 유출의 문제점으로 인해 보이스 피싱의 피해 건수가 증가하고 있다. 이러한 보이스 피싱의 사회적 문제에 대하여 상황 인지 및 사용자 의도 파악 시스템을 적용하여 해결책으로 제안하고자 한다. 이 시스템은 음성 전화로 이루어지는 순차 정보를 텍스트 데이터에 기반하여 사기범의 문맥적 흐름에서 행위 동사를 추출한다. 추출된 행위 동사의 순차 정보를 통해 보이스 피싱의 상황임을 인지하고, 흐름의 행동 패턴을 분석하여 사기범의 의도를 파악한다. 이러한 상황 인지 및 사용자 의도 파악 시스템은 개인 정보의 문제뿐만 아니라 경제적 피해 규모를 축소시킬 것으로 예상된다.

T-Cache: a Fast Cache Manager for Pipeline Time-Series Data (T-Cache: 시계열 배관 데이타를 위한 고성능 캐시 관리자)

  • Shin, Je-Yong;Lee, Jin-Soo;Kim, Won-Sik;Kim, Seon-Hyo;Yoon, Min-A;Han, Wook-Shin;Jung, Soon-Ki;Park, Se-Young
    • Journal of KIISE:Computing Practices and Letters
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    • v.13 no.5
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    • pp.293-299
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    • 2007
  • Intelligent pipeline inspection gauges (PIGs) are inspection vehicles that move along within a (gas or oil) pipeline and acquire signals (also called sensor data) from their surrounding rings of sensors. By analyzing the signals captured in intelligent PIGs, we can detect pipeline defects, such as holes and curvatures and other potential causes of gas explosions. There are two major data access patterns apparent when an analyzer accesses the pipeline signal data. The first is a sequential pattern where an analyst reads the sensor data one time only in a sequential fashion. The second is the repetitive pattern where an analyzer repeatedly reads the signal data within a fixed range; this is the dominant pattern in analyzing the signal data. The existing PIG software reads signal data directly from the server at every user#s request, requiring network transfer and disk access cost. It works well only for the sequential pattern, but not for the more dominant repetitive pattern. This problem becomes very serious in a client/server environment where several analysts analyze the signal data concurrently. To tackle this problem, we devise a fast in-memory cache manager, called T-Cache, by considering pipeline sensor data as multiple time-series data and by efficiently caching the time-series data at T-Cache. To the best of the authors# knowledge, this is the first research on caching pipeline signals on the client-side. We propose a new concept of the signal cache line as a caching unit, which is a set of time-series signal data for a fixed distance. We also provide the various data structures including smart cursors and algorithms used in T-Cache. Experimental results show that T-Cache performs much better for the repetitive pattern in terms of disk I/Os and the elapsed time. Even with the sequential pattern, T-Cache shows almost the same performance as a system that does not use any caching, indicating the caching overhead in T-Cache is negligible.

A Sequential Pattern Analysis for Dynamic Discovery of Customers' Preference (고객의 동적 선호 탐색을 위한 순차패턴 분석: (주)더페이스샵 사례)

  • Song, Ki-Ryong;Noh, Soeng-Ho;Lee, Jae-Kwang;Choi, Il-Young;Kim, Jae-Kyeong
    • Information Systems Review
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    • v.10 no.2
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    • pp.195-209
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    • 2008
  • Customers' needs change every moment. Profitability of stores can't be increased anymore with an existing standardized chain store management. Accordingly, a personalized store management tool needs through prediction of customers' preference. In this study, we propose a recommending procedure using dynamic customers' preference by analyzing the transaction database. We utilize self-organizing map algorithm and association rule mining which are applied to cluster the chain stores and explore purchase sequence of customers. We demonstrate that the proposed methodology makes an effect on recommendation of products in the market which is characterized by a fast fashion and a short product life cycle.

Design and Analysis of Efficient Operation Sequencing in FMC Robot Using Simulation and Sequential Patterns (시뮬레이션과 순차 패턴을 이용한 FMC 로봇의 효율적 작업 순서 설계 및 분석)

  • Kim, Sun-Gil;Kim, Youn-Jin;Lee, Hong-Chul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.6
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    • pp.2021-2029
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    • 2010
  • This paper suggested the method to design and analyze FMC robot's dispatching rule using the Simulation and Sequential Patterns. To do this, first of all, we built FMC using simulation and then, extracted signals that facilities call a robot, saved it as the log type. Secondly, we built robot's optimal path using the Sequential Pattern Mining with the results of analyzing the log and relationship between machine and robot actions. Lastly, we adapted it to the A corp.'s manufacturing line for verifying its performance. As a result of applying the new dispatching rule in FMC, total throughput and total flow time decrease because of decreasing material loss time and increasing robot utility. Furthermore, because this method can be applied for every manufacturing plant using simulation, it can contribute to advance total FMC efficiency as well.

Mining Maximal Frequent Contiguous Sequences in Biological Data Sequences (생물학적 데이터 서열들에서 빈번한 최대길이 연속 서열 마이닝)

  • Kang, Tae-Ho;Yoo, Jae-Soo
    • The KIPS Transactions:PartD
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    • v.15D no.2
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    • pp.155-162
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    • 2008
  • Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

Study on the Usability Based on Web Mining in Army College Library Homepage (웹마이닝을 통한 도서관 홈페이지의 사용편의성에 관한 연구 - 육군대학 도서관 홈페이지를 중심으로 -)

  • 손용배;이응봉
    • Proceedings of the Korean Society for Information Management Conference
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    • 2001.08a
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    • pp.213-218
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    • 2001
  • 본 연구는 육군대학 도서관 홈페이지의 웹서버에 저장되어 있는 로그파일을 실험 데이터로 사용하여, 기존 데이터마이닝(data mining)의 기법들 중에서 연관규칙(association rules) 탐사 기법을 적용함으로써, 사용자들의 웹 항행에 대한 순차패턴을 추출하였다. 이를 분석하여 실제 사용자들이 효과적으로 사용할 수 있는 웹사이트 디자인을 제안하고 나아가 대상 웹사이트의 사용편의성을 평가하였다.

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A Study on Baby Boomer's Job Mobility using Sequential Analysis (순차분석을 활용한 베이비붐 세대의 직업이동 분석)

  • Lim, Jung-Yeon;Lee, Young-Min
    • The Journal of the Korea Contents Association
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    • v.15 no.3
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    • pp.146-159
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    • 2015
  • The purpose of this study was to investigate the influential factors on the job mobility types and patterns of baby boomers over the past 15 years. Sequential analysis was conducted to analyze the data that were derived from Wave 1~15(1998~2013) of Korean Labor and Income Panel Study(KLIPS). In particular, we analyzed the job mobility types and frequency, conversion analysis, probability, and significance rate. The results were as follows: firstly, proportional rates of male baby boomer workers such as technical, functional, and agriculture workers were higher than those of professionals and semi-professionals, whereas in case of female baby boomer workers, proportional rate of office workers were lower than those of service and sales workers. It was showed that functional and labor workers significantly higher than others. We found that after retiring, they left their job to search for farming job or choose to work in secondary labor markets. We suggested that the retirement support system and management system should be designed and conducted in a good manner.

A Study of Progressive Parameter Calibrations for Rainfall-Runoff Models (강우-유출모형을 위한 매개변수 순차 보정기법 연구)

  • Kwak, Jae-Won;Kim, Duk-Gil;Hong, Il-Pyo;Kim, Hung-Soo
    • Journal of Wetlands Research
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    • v.11 no.2
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    • pp.107-121
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    • 2009
  • Many rainfall-runoff models have been used for the flood forecasting. However, the determination of rainfall-runoff model parameters is very difficult. In this study, we investigated the efficiency of flood forecasting models by studying the optimization techniques for parameter calibration of SFM, Tank, and SSARR models. We analyzed the correlations between parameters in optimization techniques, then classified the parameters into parameter groups. For this we applied the sequential calibration method through the sensitivity analysis. As the results of the analysis, the parameter groups clibration method showed better result for peak flow and clibtation time.

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Analyzing Patterns in News Reporters' Information Seeking Behavior on the Web (기자직의 웹 정보탐색행위 패턴 분석)

  • Kwon, Hye-Jin;Jeong, Dong-Youl
    • Journal of the Korean Society for information Management
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    • v.27 no.4
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    • pp.109-130
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    • 2010
  • The purpose of this study is to identify th patterns in the news reporters' information seeking behaviors by observing their web activities. For this purpose, transaction logs collected from 23 news reporters were analyzed. Web tracking software was installed to collect the data from their PCs, and a total of 39,860 web logs were collected in two weeks. Start and end pattern of sessions, transitional pattern by step, sequence rule model was analyzed and the pattern of Internet use was compared with the general public. the analysis of pattern derived a web information seeking behavior modes that consists of four types of behaviors: fact-checking browsing, fact-checking search, investigative browsing and investigative search.