INTERNET RESOURCES: East Asian studies: Sites to help meet the growing demand for information

Chang, C. L.; Chao, Sheau-yueh J.; Chiang, Belinda

doi:10.5860/crln.59.7.514

Cited by 3 publications

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“…The people can easily interact with the news updates and gain knowledge about the world at any time. The frequent users and researchers need to get a useful source of information without visiting several links and websites [11]. The usage of information resources is different in different countries and differ geographically [12].…”

Section: Introductionmentioning

confidence: 99%

Feature Discrimination of News Based on Canopy and KMGC-Search Clustering

et al. 2022

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The internet provides a very vast amount of sources of news and the user has to search for desirable news by spending a lot of time because the user always prefers their related interest, desirable and informative news. The clustering of the news article having a great impact on the preferences of the user. The unsupervised learning techniques such that K-means Clustering and Spectral Clustering are proposed to categorize the news articles by extracting discriminant features that help the user to search and get informative news without wasting time. The BBC news articles dataset is used to perform experiments that consist of 2225 news articles. The TF-IDF feature extraction technique is used with Kmeans clustering and Spectral clustering to get the most similar clusters to categorize the news articles in respective domains. Those domains are sports, tech, entertainment, politics, and business. The clustering algorithms are evaluated using adjusted rand index, V-measure, homogeneity score, completeness score, and Fowlkes mallows score. The experimental results illustrated that K-means clustering performs better than spectral clustering using the TF-IDF feature extraction approach. But to improve the results the canopy centroid selection is used with the grid search optimization technique to optimize the results of the Kmeans and named its as a K-Means using Grid Search based on Canopy (KMGC-Search). The experimental results shows the proposed approach can be used as a viable method for the categorization of news articles.

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Section: Introductionmentioning

confidence: 99%

Feature Discrimination of News Based on Canopy and KMGC-Search Clustering

et al. 2022

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Chinese art libraries: developments and trends Part I

Irvine

2000

Art Libraries Journal

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Chinese art libraries reflect many of the changes which have occurred in the art and culture of this society over the past 100 years. While a visiting scholar at Nanjing Arts Institute, the author had the opportunity to interview librarians working in major art libraries in Beijing, Hangzhou, Nanjing, Shanghai and Shenyang. This first part of her report gives general background, describes the library collections in the institutions visited, and addresses questions of funding and staff. As the electronic era shrinks the world of art librarianship, and as we seek greater cooperation and expanded networking opportunities, knowledge about Chinese art libraries will provide the foundation for future partnerships and resource sharing.

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Internet resources on China and Chinese studies

Zhang

1999

Asian Libraries

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The Internet is full of resources on China and Chinese studies. However, many new users are often overwhelmed by the vast amount of information on the Web. This paper is to offer a starting point for inexperienced users interested in finding information over the Internet on Chinese culture, art, language, literature, history, philosophy and current affairs, etc. It focuses on the World Wide Web resources only, and choices of entry are selective rather than exhaustive.

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INTERNET RESOURCES: East Asian studies: Sites to help meet the growing demand for information

Cited by 3 publications

References 0 publications

Feature Discrimination of News Based on Canopy and KMGC-Search Clustering

Feature Discrimination of News Based on Canopy and KMGC-Search Clustering

Chinese art libraries: developments and trends Part I

Internet resources on China and Chinese studies

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