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线性检索模型中的提问式 被引量:6

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摘要 本文主要讨论自适应性线性检索模型结构中的提问模型。以用户优选的概念作为归纳推理的基础。
出处 《情报学报》 CSSCI 北大核心 1997年第3期174-179,共6页 Journal of the China Society for Scientific and Technical Information
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参考文献2

  • 1董延隂.基础集合论[M]北京师范大学出版社,1988.
  • 2[日]近藤次郎 著,宫荣章等.数学模型[M]机械工业出版社,1985.

同被引文献9

  • 1马巍.自动构造布尔检索提问式算法研究[J].情报学报,1994,13(4):281-288. 被引量:5
  • 2Girogos Akivas, Manolis Wallace, Context - Sensitive Query Expansion Based on Fuzzy Clustering of Index Terms, http: //link. springer. de/link/service/series/0558/tocs. htm.
  • 3Salton, G. and Buckley, C. Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 41, 288-297.
  • 4Giorgos Akivas, Manolis Wallace. Context-Sensitive Query Expansion Based on Fuzzy Clustering of Index Terms[DB/OL], http://link.springer.de/link/service/series/0558/tocs.htm.
  • 5Salton G. Buckley C. Improving retrieval performance by relevance feedback[J]. Journal of the American Society for Information Science, 1998,41,288-297.
  • 6Stefan Klink, Armin Hust Collaborative Learning of Term-Based Concepts for Automatic Query Expansion [EB/OL]. http://link. springer, de/link/service/series/0558/tocs, htm, 2006-03-27.
  • 7Giorgos Akivas, Manolis Wallace, Context- Sensitive Query Expansion Based on Fuzzy Clustering of Index Terms[EB/OL]. http://link, springer, de/link/service/series/0558/tocs, htm, 2006-03-27.
  • 8Salton, G. and Buckley, C.. Improving retrieval performance by relevance feedback[J]. Journal of the American Society for Information Science,2000, (41):288-297.
  • 9李琳.超文本全文检索系统模型分析[J].青岛海洋大学学报(社会科学版),1997(2):91-94. 被引量:1

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