http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
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RISS 인기검색어
- 검색키워드
- 저자 : Youlong Luo (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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Entity Relationship Modeling Approach Based on Micro- Blog Tag
Junjiang Li,Chunlin Li,Youlong Luo,Yahui Zhao,Xijun Mao 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.7
Due to the huge information, short length and noise data, the traditional method has poor effect on micro-blog entity relationship modeling. In this paper, a new micro-blog user interests discovering approach based on tag is presented to improve the entity relationship modeling. First the matrix of user tag built by traditional way may generate the problem of sparse matrix in tag recommendation, so we introduce the information of micro-blog and establish the bipartite graph of User-Tag and Tag-Word respectively, then use them to recommend tag to micro-blog users. Meanwhile interactive relationship between users also show their interests, we establish a graph of tag relation by users’ relationship and propose a method called Tag Rank on the basis of this graph to improve the precision of the model. Finally, we combine the two methods to discover user interests. In the experiment, we use several measurement metrics: F-value, precision and the recall rate. It is proven that the new approach in the paper have a perfect performance.
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Mingming Li,Chunlin Li,Chao Wu,Youlong Luo 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.2
Currently, the efficiency of the existing focused crawlers is not high because of their unsatisfactory precision. In this article, we analyze the URL analysis methods of the existing focused crawlers, and propose a URL analysis algorithm based on the semantic content and link clustering in cloud environment. In this algorithm, the download URLs are clustered with the philosophy of clustering on the basis of VSM to improve the precision of the focused crawler according to the correlation between download URLs and new URLs. The algorithm is evaluated on Heritrix3.10 compared with Best First Search algorithm and Shark Search algorithm. The experiment results demonstrate that the algorithm proposed can collect web pages related to the given topic accurately and effectively.Moreover, the algorithm has a good ability of learning which proves the possibility of this algorithm.
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Identifying Opinion Leader in the Internet Forum
Chao Wu,Chunlin Li,Wei Yan,Youlong Luo,Xijun Mao,Shumeng Du,Mingming Li 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.11
Opinion leader is an authority person who has great influence in BBS. Their linguistic behavior has a huge impact on net citizen’s behavior and thought. In this paper, we propose an algorithm called OLRA (Opinion Leader PageRank Algorithm) based on topic-field to identify opinion leaders in the Internet forum. In the algorithm the closeness degree factor and sentiment analyses are taken into consideration. Meanwhile, these two authority values are defined as the weight of links among users. The data is collected from a number of posts on Tianya forum which is a famous forum in China. In the experiment, the algorithm is compared with Interest-based PageRank algorithm, online time Algorithm, and Experience-based Algorithm, the result shows that the OLRA algorithm can identify opinion leaders than others in the Internet forum effectively.
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