• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3041-3063
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• 2018

Community search aims at finding a meaningful community that contains the query node and also maximizes (minimizes) a goodness metric. This problem has recently drawn intense research interest. However, most metric-based algorithms tend to include irrelevant subgraphs in the identified community. Apart from the user-defined metric algorithm, how can we search the natural community that the query node belongs to? In this paper, we propose a novel community search algorithm based on the concept of the k-hop and local distance dynamics model, which can naturally capture a community that contains the query node. The basic idea is to envision the nodes that k-hop away from the query node as an adaptive local dynamical system, where each node only interacts with its local topological structure. Relying on a proposed local distance dynamics model, the distances among nodes change over time, where the nodes sharing the same community with the query node tend to gradually move together, while other nodes stay far away from each other. Such interplay eventually leads to a steady distribution of distances, and a meaningful community is naturally found. Extensive experiments show that our community search algorithm has good performance relative to several state-of-the-art algorithms.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.321-326
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• 2009

Since the existing Web search engines don't sufficiently reflect user's search intent, it is very difficult to find out accurate information that users want to find. Therefore, a lot of researches, study for personalized search, to enhance satisfaction of Web search results by analyzing search pattern and applying it to search are in progress in these days. Web searchers can more efficiently find information and easily obtain appropriate information through the personalized search. In this paper, we propose the personalized search based on community through the analysis of web users' query patterns and interest. Consequently, when applying query frequency, interest and community to web search, we are able to the confirm that the search results which hit to the search intent of the individual are provided.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.230-237
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• 2022

The Community Social Service Investment project started as a state subsidy project in 2007 and has grown very rapidly in quantitative terms in a short period of time. It is a bottom-up project that discovers the welfare needs of people and plans and provides services suitable for them. The purpose of this study is to analyze using big data to determine the social response to local community service investment projects. For this, data was collected and analyzed by crawling with a specific keyword of community service investment project on Google and Naver sites. As for the analysis contents, monthly search volume, related keywords, monthly search volume, search rate by age, and gender search rate were conducted. As a result, 10 items were found as related keywords in Google, and 3 items were found in Naver. The overall results of Google and Naver sites were slightly different, but they increased and decreased at almost the same time. Therefore, it can be seen that the community service investment project continues to attract users' interest.

• Journal of Agricultural Extension & Community Development
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• v.8 no.2
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• pp.201-208
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• 2001

The purpose of this study was to review the current studies on community attachment and its related variables to suggest directions for community attachment studies in Korea. Specific objectives of the study were to search the current studies on community attachment, to search for the significant variables related to community attachment, and to draw implications for community development in Korea. The major findings of the study were as follows; 1) Current studies on community attachment used individual characteristic variables such as length of residence in the community, age, size of population and density as major independent variables. 2) Studies on community attachment used community participation, social and cultural environment as major dependent variables, however, both independent variables and dependent variables were used interchangeably in many cases. 3) Recent studied on community attachment employed community economic and cultural variables, however, studies on community attachment in Korea was relatively limited in terms of quantity as well as quality. 4) Further research on community attachment should be conducted by utilizing various independent and dependent variables in various communities to increase the community attachment in rural and urban communities to further strengthen community development in Korea.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.143-158
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• 2011

This study suggests a framework which extracts features of collective intelligence from social Q&A community sites and takes advantage of those features upon vertical search for domain specific knowledge or information retrieval. One source of collective intelligence on the internet is the question and answer(Q&A) data available from many Q&A sites. Vertical search is focused on searching special areas or specific domains. This paper proposes a framework for extending the relevant terms by using Q&A information connected with query that the user wants to retrieve, and then applies them to specific domain field that requires professional and detailed knowledge.

• Journal of Korean Library and Information Science Society
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• v.42 no.1
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• pp.397-415
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• 2011

Google, an internet search service with extensive user base, has provided Book Search service. Google has pursued collaboration with publishers and libraries to obtain content for Book Search service; publisher community for the purpose of sourcing the books with copyrights, and the libraries for the purpose of digitizing their collections and also utilizing already digitized resources. Google Book Search Service has evoked significant controversy because of the potential monopoly problems and its risk, accompanied by Google's huge influence and broad user spectrum. This study, thus, suggests the countermeasures that library community should prepare in order to cope with the Google Book Search.

• Journal of Information Science Theory and Practice
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• v.10 no.1
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• pp.45-58
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• 2022

Community enterprise plays an important role for developing local business. Products from local communities apply local specialties such as high-quality materials and inherited wisdom. This work aims to support merchandises from local community enterprises by bringing out their specialties related to local wisdom and intangible cultural aspects. An ontology is applied to demonstrate the innate information regarding the implicit values of the products and is used as a core for a semantic search system. Details of the products are gathered from their respective community using an interview method and are extracted to align with the developed ontological schema. The semantic search system thus is implemented with a recommendation process for online accessibility for providing the organised information. From evaluation, the developed ontology and its instances are rated highly for their consistency, conciseness, and completeness. In usage, accuracy of the query and recommendation results are evaluated at 97.38% searching accuracy and 85.03% for recommending interesting products.

• Journal of Korean Society of Rural Planning
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• v.20 no.3
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• pp.143-154
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• 2014

For the purpose of drawing a representative type of utilizing idle farmlands, this study collected and analyzed newspaper articles about cases of utilizing idle farmlands in the past decade using Internet search engines. Prior to this, it clarified a concept of idle farmlands to raise accuracy of searching articles, and selected NAVER as a search engine. It set "idle farmland", "abandoned land", and "utilizing" as basic search words in search option, and also set search period from 1st of January in 2004 to 31st of December in 2013. This study primarily searched 1,593 articles, and extracted 165 articles excluding overlapped and unrelated articles. Furthermore, it investigated extracted articles by date, media, headline, content of use, region(province), particular area(city and country), main agent, item and keyword 1, 2, 3 for proper use. This study also examined frequencies by year according to indoor and outdoor environment as well as regional differences through frequencies by regional groups and chronology. Furthermore, it drew a diagram of frequency flow of keyword 2, 3 with each keyword 1 as the central figure in order to draw various types of using idle farmlands. Through the diagrams, this study drew 9 using types such as (1) community service. agriculture type, (2) high income. agriculture type, (3) sightseeing. landscape. agriculture type, (4) livestock. agriculture type, (5) weekend farm type, (6) high income. woodland type, (7) ecology. landscape. woodland type, (8) agricultural work-study type, (9) ecological environment type.

• Journal of the Korean Society for information Management
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• v.23 no.4 s.62
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• pp.179-196
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• 2006

This study proposes an expanded model of personalized search service based on community activities on a Korean Web portal. The model is composed of defining subject categories of users, providing personalized search results, and recommending additional subject categories and queries. Several experiments were performed to verify the feasibility and effectiveness of the proposed model. It was found that users' activities on community services provide valuable data for identifying their Interests, and the personalized search service increases users' satisfaction.

• Asia pacific journal of information systems
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• v.34 no.2
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• pp.635-660
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• 2024

A growing body of research explores how users of online communities navigate through large-scale platforms to find the information they seek. This study builds on the theories of homophily, structural embeddedness, and social exchange to investigate how interest homophily and existing communication structures serve as mechanisms driving information searches and the subsequent formation of communication networks in these communities. Specifically, we analyze comment-on-post tie formation using network data from "Today's House," the largest online user community specializing in interior design in Korea. Employing the LR-QAP method, a permutation-based hypothesis testing algorithm for social network data, our research identifies that network tie formation is driven by both homophilous information searches based on instrumental and hedonic interests, as well as by structurally induced searches such as preferential attachment, reciprocity, and transitivity. In addition, we investigate the contingent effects of communication structure on homophilous tie formation. Our findings suggest that while network-wide structural characteristics enhance homophilous tie formation based on instrumental interests, local network processes leverage homophily based on hedonic interests. We conclude by discussing the theoretical implications of the differential influence of participation motivations on information search patterns and the practical implications for the design of online communities.