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一种新的基于社会化标签的网页排名算法 被引量：2

A new algorithm based on social annotations for page ranking
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摘要 针对目前web2.0下网页无法进行有效排序这一问题,对社会化标签网下新的数据源"标签"的时间因素加以分析和利用,提出一种新的社会化标签的网页排名算法TagRank.该算法通过对网页上用户的标注行为进行挖掘,计算标签的"热度",从而更客观地反映标签的真实质量,以此提高网页排名的准确性.实验证明该算法是切实有效的. Due to the problem that webpages on web2.0 can＇t be ranked effectively at present, the authors analyse and utilize the time factor of the new data source ＂tag＂ and propose a new algorithm named TagRank based on social annotations for page ranking. This algorithm digs the annotation behavior of the web users, calculates the ＂heat＂ of the tags, consequently, it can response the true quality of tags more externally and improve the veracity of page ranking. The experiment shows that the algorithm works effectively.
作者 张晖 沈洁 陈琛 朱燕 孙荣霜 何堃
机构地区 扬州大学信息工程学院
出处 《扬州大学学报（自然科学版）》 CAS CSCD 2008年第3期49-52,共4页 Journal of Yangzhou University：Natural Science Edition
基金 江苏省自然科学基金资助项目(BK2005046)
关键词 社会化标签 书签 TagRank 排名 social annotations bookmark TagRank ranking
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献9

  • 1CIMIANO P, HANDSCHUH S, STAAB S. Towards the self-annotating web [C/OL]// Proc of the 13th Int World Wide Web Conference (WWW 200t). New York: [s.n.], 2001 [2008-03-13]. http://www.aifb. unikarlsruhe. de/WBS/pci/www04. pdf.
  • 2BYDE A, WAN H, CAYZER S. Personalized tag recommendations via social network and content-based similarity metrics [C/OL]//Proc of the lntl Conference on Conference on Weblogs and Social Media. Denver: [s.n.], 2006 [2008-03-13]. http ://www. iewsm. org/papers/4-Byde-Wan-Cayzer. pdf.
  • 3DUBINCO M, KUMAR R, MAGNANI J, et al. Visualizing tags over time [C/OL]// Proc of WWW 2006. Edinburgh: [s. n.], 2006 [2008-03-13].http://www2006.org/programme/files/pdf/25. pdf.
  • 4PAGE L, BRIN S, MOTWANI R, et al. The pagerank citation ranking: bringing order to the web [R/OL]. Palo alto, CA: Stanford Univercity Database Group, 1998 [2008-03-13]. http://infolab. stanford.edu/-backrub/pageranksub.ps.
  • 5BHARAT K, HENZINGER M. Improved algorithms for topic distillation in a hyperlinked environment [C/ OL]// Proceedings of the 21st Annual International ACM SIGIR 1998. Melbourne: ACM, 1998 [2008-03-13]. http ://gatekeeper. dec. com/pub/DEC/SRC/publications/monika/sigir98.pdf.
  • 6HEYMANN P, GARCIA-MOLINA H. Collaborative creation of communal hierarchical taxonomies in social tagging system [R/OL]. Stanford: Computer Science Department, Stanford University, April 2006 [2008-03- 13]. http ://dbpubs. stanford.edu : 8090/pub/2006-10.
  • 7GOLDER S A, HUBERMAN B A. The structure of collaborative tagging systems [J]. J Inf Sci, 2006, 32(2): 198-208.
  • 8KAMVAR S, HAVELIWALA T, COBNA G. Adaptive methods for the computation of pagerank [C/OL]// Proc of International Conference on the Numerical Solution of Markov Chains. Stanford: [s. n.], 2003[2008-03- 13]. http://nlp.stanford, edu/pubs/adaptive.ps.
  • 9DUBINKO M, CARO G D. New ideas in optimization, chapter the ant colony optimization meta-heuristic [M]. New York: McGraw-Hill, 1999: 11-32.

同被引文献20

  • 1Cattuto C, Loreto V, Pietronero L. Semiotic dynamics and collaborative tagging[J]. Proceedings of the Nation- al Academy of Sciences United States of America, 2007, 104(5) : 1461 - 1464.
  • 2Lawrence K F, Schraefel M C. Freedom and restraits: Tags, vocabularies and ontologies[C]. 2nd IEEE Inter- national Conference on ICTTS, Damasms, Syrid, Apr 24-28,2006.
  • 3Heymann P, Garcia-Molina H. Collaborative creation of communal hierarchical taxonomies in social tagging sys- tem[J]. InfoLab Technical Report,2006, (10):1-5.
  • 4Carmel D, Roitman H, Yom-Tov E, Social Bookmark weighting for search and recommendation [J ]. The VLDB Journal,2010(19) :761- 775.
  • 5Ahel F, Henze N, Krause D. Optimizing search and ranking in folksonomy systems by exploiting context in- formation[J]. Lecture Notes in Business Information Processing, 2010,(45) : 113-127.
  • 6Niwa S, Doi T, Honiden S. Folksonomy tag organiza- tion method based on the tripartite graph analysis[C]. IJCAI Workshop on Semantic Web for Collaborative Knowledge Acquisition, Hyderabad, India, Jan 6 - 8, 2007.
  • 7Byde A, Wan H, Cayzer S. Personalized tag recommendations via social network and content-based simi- larity metrics[C]. International Conference on Weblogs and Social Media,Boulder,USA Mar 26-28, 2007.
  • 8Yao Junjie, Cui Bin, Huang Yuxin, et al. Bursty event detection from collaborative tags[J]. WorldWide Web, 2012, 15(2): 171-195.
  • 9Luo JunZhou,Dong Fang,Cao .liuxin, et al. A context- aware personalized resource recommendation for perva- sive learning[J]. Cluster Comput, 2010, (13) : 213 - 239.
  • 10张晖.基于社会化标注的搜索引擎优化研究[D]扬州大学,扬州大学2008.

引证文献2

二级引证文献6

扬州大学学报（自然科学版）
2008年 第3期

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