期刊文献+

结合IFC标准的建设项目中文文本分类研究 被引量:1

Research of Chinese Construction Project Document Classification Based on IFC Standard
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摘要 为促进项目参与方的合作和交流从而使项目更优质高效的完成,研究了结合IFC标准进行建设项目文档分类的方法。在对建设项目管理的特点进行深入分析的基础上,文章提出了将项目生命期中产生的大量的半结构化或非结构化的中文文本按照国际通用的IFC标准进行分类的方法,从而改进了文本的管理与利用效果。通过空间向量模型来表示中文文本,并采用夹角余弦的方法与国际通用的IFC标准中的实体进行相似度计算,最终实现中文文本的标准化分类,并通过案例分析验证了该方法的可行性。最后对本文提出的算法进行了评价,并提出了下一步的研究方向。 In order to improve the usage of the construction documents, facilitate the communication and cooperation among the participants to enhance project management, this paper presents a method of classifying the semi-structured and unstructured Chinese documents, which are produced during the project lifecycle, combined with the commonly used IFC standard based on the analysis of the characteristics of construction project management. This paper conducts a similarity computing between the entities of IFC standard and the Chinese documents by means of Space Vector Model and Cosine similarity algorithm in order to realize the standardized classification of the Chinese documents. Case study proves the effectiveness of the proposed method.
出处 《价值工程》 2014年第27期9-11,共3页 Value Engineering
基金 国家自然科学基金(51178084)
关键词 中文文本 IFC标准化分类 信息管理 Chinese document IFC standardized classification information management
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参考文献6

  • 1National Building Information Modeling Standard (NBIMS) [EB/OL].(August 27,2010)http://www.wbdg.org/pdfs/.
  • 2Carlos H. Caldas, S., Lucio Soibelman, Jiawei Han. Automated Classi cation of Construction Project Documents [J]. JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2002, 16 (4):234-243.
  • 3Mohammed A1 Qady, Amr Kandil. Automatic Classification of Project Documents Based on Text Content [J]. Journal of Computing in Civil Engineering, doi:10.1061/(ASCE)CP.1943- 5487.0000338.
  • 4ICTCLAS官方网站[EB/OL].Ouly,2012)http://ictclas.org/.
  • 5张健.BIM环境下基于建设领域本体的语义检索研究[D].辽宁省大连市:大连理工大学,2013.
  • 6马智亮,娄酷.IFC标;隹在我国建筑工程成本预算中应用的基本问题探讨[C].工程三维模型与虚拟现实表现--第二届工程建设计算机应用创新论坛论文集,2009:25-34.

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  • 1Kiritchenko S,X.Zhu and S.M.Mohammad,Sentiment Analysis of Short Informal Text[J].Journal of Artificial Intelligence Research,2014.50:723-762.
  • 2Deng Z.,K.Luo,H.Yu.A study of supervised term weighting scheme for sentiment analysis[J].Expert Systems With Applications,2014,41(7):3506-3513.
  • 3Bravo-Marquez,F.,M.Mendoza,B.Poblete.Meta-level sentiment models for big social data analysis[J].Knowledge-based Systems.2014.69(SI):86-99.
  • 4Ou G.,et al.,CLUSM:An Unsupervised Model for Microblog Sentiment Analysis Incorporating Link Information.2014:481-494.
  • 5Hassan A.,et al.,A Random Walk-Based Model for Identifying Semantic Orientation[J].Computational Linguistics.2014.40(3):539-562.
  • 6Kim K.,J.Lee.Sentiment visualization and classification via semi-supervised nonlinear dimensionality reduction[J].Pattern Recognition.2014.47(2):758-768.
  • 7冯时,付永陈,阳锋,王大玲,张一飞.基于依存句法的博文情感倾向分析研究[J].计算机研究与发展,2012,49(11):2395-2406. 被引量:34

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