Please wait a minute...
New Technology of Library and Information Service  2011, Vol. 27 Issue (9): 66-71    DOI: 10.11925/infotech.1003-3513.2011.09.11
Current Issue | Archive | Adv Search |
Study on Influence of Data Standardization to Evaluation Results in Science and Technology
Yu Liping1, Wu Yishan2
1. School of Business, Ningbo University, Ningbo 315211, China;
2. Institute of Scientific & Technical Information of China, Beijing 100038, China
Download:
Export: BibTeX | EndNote (RIS)      
Abstract  This paper analyzes data standardization of multiple attribute evaluation in science and technology evaluation. The results show the evaluation score of side standardization is smaller than tunable standardization. Tunable standardization may increase evaluation score of lower level journals, linear standardization may affect evaluation score but cant affect evaluation ranking, and negative indicator standardization may change the evaluation ranking. The authors give a new linear negative indicator standardization method, and point out that the negative classical indicator standardization should be abandoned, and the evaluation institute should make known to the public of data standardization method so as to keep evaluation justice.
Key wordsS&      T evaluation      Data standardization      Evaluation result      Effect     
Received: 07 June 2011      Published: 02 December 2011
: 

G312

 

Cite this article:

Yu Liping, Wu Yishan. Study on Influence of Data Standardization to Evaluation Results in Science and Technology. New Technology of Library and Information Service, 2011, 27(9): 66-71.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2011.09.11     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2011/V27/I9/66

[1] Saaty T L. The Analytic Hierarchy Process[M]. New York:McGraw-Hill, 1980.

[2] Shannon C E. A Mathematical Theory of Communication[J]. Bell System Technical Journal, 1948,27:379-429,623-656.

[3] Hwang C L,Yoon K.Multiple Attribute Decision Making:Methods and Applications[M].NY:Springer-Verlag,1981:12-34.

[4] Diakoulaki D,Mavrotas G,Papayannakis L.Determining Objective Weights in Multiple Criteria Problems:The CRlTIC Method[J].Computers and Operations Research,1995,22(7):763-770.

[5] 吴松涛,侯风华,戴锋. 非线性数据标准化处理过程中的线性近似法[J]. 信息工程大学学报,2007,8(2):250-253.

[6] 焦立新. 评价指标标准化处理方法的探讨[J]. 安徽农业技术师范学院学报,1999,13(3):7-10.

[7] 马立平. 统计数据标准化——无量纲化方法[J]. 北京统计,2000(3):34-35.

[8] 刘玉秀,李玉刚. 医院工作质量综合评价指标的非线性标准化[J]. 中国医院统计,1997,4(4):213-215.

[9] 俞立平,潘云涛,武夷山. 学术期刊综合评价数据标准化方法研究[J]. 图书情报工作,2009,53(12):146-149.
[1] Xu Zengxulin, Xie Jing, Yu Qianqian. Designing New Evaluation Model for Talents[J]. 数据分析与知识发现, 2021, 5(8): 122-131.
[2] Dong Mei,Chang Zhijun,Zhang Runjie. A Multiple Pattern Matching Algorithm for Specifications of Incremental Metadata for Sci-Tech Literature[J]. 数据分析与知识发现, 2021, 5(6): 135-144.
[3] Liu Weijiang,Wei Hai,Yun Tianhe. Evaluation Model for Customer Credits Based on Convolutional Neural Network[J]. 数据分析与知识发现, 2020, 4(6): 80-90.
[4] Jiying Hu,Jing Xie,Li Qian,Changlei Fu. Constructing Big Data Platform for Sci-Tech Knowledge Discovery with Knowledge Graph[J]. 数据分析与知识发现, 2019, 3(1): 55-62.
[5] Wang Ling,Dai Qianjin,Wu Xiaojun. The Study on the Temporal and Spatial Distribution of Event Tourism Based on Large-scale Tourism Early Warning Platform[J]. 数据分析与知识发现, 2018, 2(8): 31-40.
[6] Fan Xinyue,Cui Lei. Using Text Mining to Discover Drug Side Effects: Case Study of PubMed[J]. 数据分析与知识发现, 2018, 2(3): 79-86.
[7] Wang Zhongyi,Zhang Heming,Huang Jing,Li Chunya. Studying Knowledge Dissemination of Online Q&A Community with Social Network Analysis[J]. 数据分析与知识发现, 2018, 2(11): 80-94.
[8] Ye Guanghui,Xia Lixin. Review of Expert Retrieval and Expert Ranking Studies[J]. 数据分析与知识发现, 2017, 1(2): 1-10.
[9] Huai Mengjiao,Pan Yuntao,Yuan Junpeng. Evaluating Academic Credits of Scientific Research Project Leaders[J]. 数据分析与知识发现, 2017, 1(11): 94-102.
[10] Yaming Zhang,Na Li,Peiqing Zhao. Study on Credit Evaluation Model of Online Group-buying by Using ACO and Similarity Weight Algorithm[J]. 现代图书情报技术, 2016, 32(1): 40-47.
[11] Zhang Yongyun, Zhang Shengtai. Star Effect and Broker Effect in Social Media Knowledge Collaboration Network: Discovery from Wikipedia Social Media[J]. 现代图书情报技术, 2015, 31(4): 72-78.
[12] He Yue, Song Lingxi, Qi Liyun. Spillover Effect of Internet Word of Mouth in Negative Events——Take the “Deadly Yuantong Express” Event for an Example[J]. 现代图书情报技术, 2015, 31(10): 58-64.
[13] Zhang Zhixiong, Liu Jianhua, Xie Jing, Qian Li, Zhang Min, Yu Gaihong. Design and Implementation of the Service Cloud for Strategic S&T Information Monitoring[J]. 现代图书情报技术, 2014, 30(6): 51-61.
[14] Hao Mei, Wang Daoping. Mining Customer Focus Features from Product Reviews Oriented Supply Chain[J]. 现代图书情报技术, 2014, 30(4): 65-70.
[15] Li Bing, Xu Weijia, Zhang Jingxuan. The Research of Products Evaluation Using Microblogging Data with “Android System” Evaluation as an Example[J]. 现代图书情报技术, 2014, 30(4): 92-98.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn