• Title/Summary/Keyword: topic cluster

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Investigating the Combination of Bag of Words and Named Entities Approach in Tracking and Detection Tasks among Journalists

  • Mohd, Masnizah;Bashaddadh, Omar Mabrook A.
    • Journal of Information Science Theory and Practice
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    • v.2 no.4
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    • pp.31-48
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    • 2014
  • The proliferation of many interactive Topic Detection and Tracking (iTDT) systems has motivated researchers to design systems that can track and detect news better. iTDT focuses on user interaction, user evaluation, and user interfaces. Recently, increasing effort has been devoted to user interfaces to improve TDT systems by investigating not just the user interaction aspect but also user and task oriented evaluation. This study investigates the combination of the bag of words and named entities approaches implemented in the iTDT interface, called Interactive Event Tracking (iEvent), including what TDT tasks these approaches facilitate. iEvent is composed of three components, which are Cluster View (CV), Document View (DV), and Term View (TV). User experiments have been carried out amongst journalists to compare three settings of iEvent: Setup 1 and Setup 2 (baseline setups), and Setup 3 (experimental setup). Setup 1 used bag of words and Setup 2 used named entities, while Setup 3 used a combination of bag of words and named entities. Journalists were asked to perform TDT tasks: Tracking and Detection. Findings revealed that the combination of bag of words and named entities approaches generally facilitated the journalists to perform well in the TDT tasks. This study has confirmed that the combination approach in iTDT is useful and enhanced the effectiveness of users' performance in performing the TDT tasks. It gives suggestions on the features with their approaches which facilitated the journalists in performing the TDT tasks.

The Evaluation of Web Contents by User 'Likes' Count: An Usefulness of hT-index for Topic Preference Measurement

  • Song, Yeseul;Park, Ji-Hong;Shim, Jiyoung
    • Journal of the Korean Society for Library and Information Science
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    • v.49 no.2
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    • pp.27-49
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    • 2015
  • The purpose of this study is to suggest an appropriate index for evaluating preferences of Web contents by examining the h-index and its variants. It focuses on how successfully each index represents relative user preference towards topical subjects. Based on data obtained from a popular IT blog (engadget.com), subject values of the h-index and its variants were calculated using 53 subject categories, article counts and the 'Likes' counts aggregated in each category. These values were compared through critical analysis of the indices and Spearman rank correlation analysis. A PFNet (Pathfinder Network) of subjects weighted by $h_T$ values was drawn and cluster analysis was conducted. Based on the four criteria suggested for the evaluation of Web contents, we concluded that the $h_T$-index is a relatively appropriate tool for the Web contents preference evaluation. The $h_T$-index was applied to visually represent the relative weight (topic preference by user 'Likes' count) for each subject category of the real online contents after suggesting the relative appropriateness of the $h_T$-index. Applying scientometric indicators to Web information could provide new insights into, and potential methods for, Web contents evaluation. In addition, information on the focus of users' attention would help online informants to plan more effective content strategies. The study tries to expand the application area of the h-type indices to non-academic online environments. The research procedure enables examination of the appropriateness of the index and highlights considerations for applying the indicators to Web contents.

Analysis of Massive Scholarly Keywords using Inverted-Index based Bottom-up Clustering (역인덱스 기반 상향식 군집화 기법을 이용한 대규모 학술 핵심어 분석)

  • Oh, Heung-Seon;Jung, Yuchul
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.19 no.11
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    • pp.758-764
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    • 2018
  • Digital documents such as patents, scholarly papers and research reports have author keywords which summarize the topics of documents. Different documents are likely to describe the same topic if they share the same keywords. Document clustering aims at clustering documents to similar topics with an unsupervised learning method. However, it is difficult to apply to a large amount of documents event though the document clustering is utilized to in various data analysis due to computational complexity. In this case, we can cluster and connect massive documents using keywords efficiently. Existing bottom-up hierarchical clustering requires huge computation and time complexity for clustering a large number of keywords. This paper proposes an inverted index based bottom-up clustering for keywords and analyzes the results of clustering with massive keywords extracted from scholarly papers and research reports.

Lifetime-based Clustering Communication Protocol for Wireless Sensor Networks (무선 센서 네트워크를 위한 잔여 수명 기반 클러스터링 통신 프로토콜)

  • Jang, Beakcheol
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.4
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    • pp.2370-2375
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    • 2014
  • Wireless sensor networks (WSNs) have a big potential for distributed sensing for large geographical area. The improvement of the lifetime of WSNs is the important research topic because it is considered to be difficult to change batteries of sensor nodes. Clustering communication protocols are energy-efficient because each sensor node can send its packet to the cluster head near from itself rather than the sink far from itself. In this paper, we present an energy-efficient clustering communication protocol, which chooses cluster heads based on the expected residual lifetime of each sensor node. Simulation results show that our proposed scheme increases average lifetimes of sensor nodes as much as 20% to 30% in terms of the traffic quantity and as much as 30% to 40% in terms of the scalability compared to the existing clustering communication protocol, LEACH.

Application of Parallel Processing System for free drop simulation of IT-related modules (IT 모듈의 자유 낙하 모사를 위한 병렬처리시스템의 적용)

  • Park Y.J.;Lee J.S.;Ko H.O.;Chang Y.S.;Choi J.B.;Kim Y.J.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.405-406
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    • 2006
  • Recently, the flat display modules such as plasma or TFT-LCD employ thin crystallized panels which are normally weak to high level transient mechanical energy inputs. As a result, anti-shock performance is one of the most important design specifications for TFT-LCD modules. However, most of large display module designs are generated based on engineers own experiences. Also, a large-scale analysis to evaluate complex material and structural behaviors is one of interesting topic in diverse engineering and scientific fields. The utilization of massively parallel processors has also been a recent trend of high performance computing. The objective of this paper is to introduce a parallel process system which consists of general purpose finite element analysis solver as well as parallelized PC cluster. The parallel processing system is constructed using thirty-two processing elements and the finite element program is developed by adopting hierarchical domain decomposition method. In order to verify the efficiency of the established system, an impact analysis on thin and complex sub-parts of flat display modules is performed. The evaluation results showed a good agreement with the corresponding reference solutions, and thus, the parallel process system seems to be a useful tool fur the complex structural analysis such as IT related products.

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Multi-document Summarization Based on Cluster using Term Co-occurrence (단어의 공기정보를 이용한 클러스터 기반 다중문서 요약)

  • Lee, Il-Joo;Kim, Min-Koo
    • Journal of KIISE:Software and Applications
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    • v.33 no.2
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    • pp.243-251
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    • 2006
  • In multi-document summarization by means of salient sentence extraction, it is important to remove redundant information. In the removal process, the similarities and differences of sentences are considered. In this paper, we propose a method for multi-document summarization which extracts salient sentences without having redundant sentences by way of cohesive term clustering method that utilizes co-occurrence Information. In the cohesive term clustering method, we assume that each term does not exist independently, but rather it is related to each other in meanings. To find the relations between terms, we cluster sentences according to topics and use the co-occurrence information oi terms in the same topic. We conduct experimental tests with the DUC(Document Understanding Conferences) data. In the tests, our method shows better performance of summarization than other summarization methods which use term co-occurrence information based on term cohesion of document or sentence unit, and simple statistical information.

Classifying and Characterizing the Types of Gentrified Commercial Districts Based on Sense of Place Using Big Data: Focusing on 14 Districts in Seoul (빅데이터를 활용한 젠트리피케이션 상권의 장소성 분류와 특성 분석 -서울시 14개 주요상권을 중심으로-)

  • Young-Jae Kim;In Kwon Park
    • Journal of the Korean Regional Science Association
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    • v.39 no.1
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    • pp.3-20
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    • 2023
  • This study aims to categorize the 14 major gentrified commercial areas of Seoul and analyze their characteristics based on their sense of place. To achieve this, we conducted hierarchical cluster analysis using text data collected from Naver Blog. We divided the districts into two dimensions: "experience" and "feature" and analyzed their characteristics using LDA (Latent Dirichlet Allocation) of the text data and statistical data collected from Seoul Open Data Square. As a result, we classified the commercial districts of Seoul into 5 categories: 'theater district,' 'traditional cultural district,' 'female-beauty district,' 'exclusive restaurant and medical district,' and 'trend-leading district.' The findings of this study are expected to provide valuable insights for policy-makers to develop more efficient and suitable commercial policies.

A Systematic Review on Smart Manufacturing in the Garment Industry

  • Kim, Minsuk;Ahn, Jiseon;Kang, Jihye;Kim, Sungmin
    • Fashion & Textile Research Journal
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    • v.22 no.5
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    • pp.660-675
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    • 2020
  • Since Industry 4.0, there is a growing interest in smart manufacturing across all industries. However, there are few studies on this topic in the garment industry despite the growing interest in implementing smart manufacturing. This paper presents the feasibility and essential considerations for implementing smart manufacturing in the garment industry. A systematic review analysis was conducted. Studies on garment manufacturing and smart manufacturing were searched separately in the Scopus database. Key technologies for each manufacturing were derived by keyword analysis. Studies on key technologies in each manufacturing were selected; in addition, bibliographic analysis and cluster analysis were conducted to understand the progress of technological development in the garment industry. In garment manufacturing, technology studies are rare as well as locally biased. In addition, there are technological gaps compared to other manufacturing. However, smart manufacturing studies are still in their infancy and the direction of garment manufacturing studies are toward smart manufacturing. More studies are needed to apply the key technologies of smart manufacturing to garment manufacturing. In this case, the progress of technology development, the difference in the industrial environment, and the level of implementation should be considered. Human components should be integrated into smart manufacturing systems in a labor-intensive garment manufacturing process.

A Study on the Structural Model and Evaluation of National Maritime Power System(I) (국가해양력시스템의 구조모델과 평가에 관한 연구(I))

  • 임봉택;이철영
    • Journal of Korean Port Research
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    • v.14 no.1
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    • pp.57-64
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    • 2000
  • For composing the structure model of national maritime power system by system structural modeling, in this study, the 50 basic factors are selected by survey of the extensive and through literatures on maritime, sea, maritime power and sea power. And the basic factors are classified into 36 component factors by cluster method. The 9 attributes are extracted by the application of the principle component analysis method, one of the factor analysis method in system engineering, to component factors. In this study, we define the attributes composing the national maritime power system by integrating the result of this study and existed our studies relating to this topic. Which are showed in Table 2. and we show the structure model of national maritime power system in Fig. 3. In Table 2, the 9 attributes are as follows : the fundamental power of maritime, shipping and port power, naval power, fishing power, shipbuilding power, the power of ocean research and development, dependency on seaborne trade, the protection power of ocean environment and the will and inclination of govemment. Also, in the case of evaluating this system, we conform the importance of considering the interactions among the attributes which have strong interactions in structure model of national maritime power system.

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An Efficient Directional MAC Protocol for Vehicular Ad-hoc Networks (차량 Ad-hoc에서 효율적인 메시지 전달을 위한 지향성 MAC 프로토콜)

  • Ji, Soonbae;Kim, Junghyun;You, Cheolwoo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.4
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    • pp.9-16
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    • 2015
  • Quick and safe message transmission is an important research topic of vehicular ad hoc networks (VANET). Most studies assume that the periodic broadcast of beacon-frames between vehicles increases the safety of the driver. In this paper, we propose a medium access control (MAC) protocol and location-based clustering for the VANET to support reliable data transfer. In our proposal, the cluster heade (CH) manage the access and allocate the resources of the node. Our proposal uses simulation to confirm the reduction of the transmission delay and the collision rate of the signal.