Fang S(方曙)

Gao LD(高利丹)

Hu ZY(胡正银)

Pang HS(庞弘燊)

Tang C(唐川)

Xiao GH(肖国华)

Zhang DS(张邓锁)

Zhang X(张娴)

National Science Library,Chinese Academy of Sciences

An Empirical Test of the Evaluation Model on Core Patent Documents Xian Zhang1, Shu Fang2, Guohua Xiao3, Lidan Gao4, Chuan Tang5,  Dengsuo Zhang6, Zhengyin Hu7 and Hongshen Pang8 1 zhangx@clas.ac.cn, 2fangsh@clas.ac.cn, 3xiaogh@clas.ac.cn, 4gld@clas.ac.cn, 5tangc@clas.ac.cn,  6zhangds@clas.ac.cn, 7huzy@clas.ac.cn, 8winsunpang@126.com Chengdu Library of the Chinese Academy of Sciences, Chengdu 610041 (China) Introduction The patent document becomes an important information source for technology assessment and forecasting. In our previous study, combining AHP and Delphi Questionnaires as the primary approach, with a group decision-making model basing on the Maximum Likelihood and Unbiased Estimation theory, we constructed an evaluation model for identifying core patent documents of a certain technology field in patent information analysis (Zhang, 2009a). This paper is a subsequent practical application of above evaluation model developed in our first-stage study. An empirical test is carried out. The evaluation model is applied to calculate the value score of patent documents in a certain field. Those patent documents that have the highest scores are selected as the core ones in their field. By peer review, these documents are recognized as the core patents. Empirical test results turn out that this model works well. This paper reports the results of the empirical test on this issue. The focus is to look at the empirical process. Methodology Indicator system optimization The further clarifying of relevant indicators in our previous evaluating system is the starting point for our empirical issues. Reviewing the system, we optimize 3 indicators which did not reflect practice, to further optimize the evaluation performance. The 3 indicators are Technology Dependence (TD), Science Linkage (SL) and Standardization Index (STI). After these adjustments, the evaluation hierarchical structure with weights is further optimized to practical empirical. Valuing rules of each indicator The valuing rules of each base-level indicator of the evaluation system are determined. That is how to assign to each indicator. Multiple data sources are employed in our empirical test for the availability of indicator measurements, including: Derwent Innovation Index (DII), Aureka and Journal Citation Reports® (JCR) from Thomson Reuters; Patent Full-Text and Image Database (PatFT), Patent Application Full-Text and Image Database (AppFT), Patent Application Information Retrieval (PAIR) system and Patent Assignment Database (Assignments on the Web) from USPTO; Industrial Property Digital Library (IPDL) from Japanese patent office. Normalizing and dimensionless To eliminate computational problems caused by differing measurement units, it is essential to normalize attribute ratings in empirical application. Normalization aims at obtaining comparable scales, which allow inter-attribute as well as intra-attribute comparisons. Consequently, normalized ratings have dimensionless units (Yoon, 2005). Firstly, we classify the attributes of the system into two groups, and then for each group, present normalization techniques. (1) Benefit attributes: Offer increasing monotonic utility. That is, the greater the attribute value the more its preference; (2) Cost attributes: Offer decreasing monotonic utility. That is, the greater the attribute value the less its preference.  The principle of our normalization is to transform the attributes so that all the attribute values mapped into the range [0, 1]. Here Linear Normalization method is adopted as following:  For the jth attribute pj, its value xij∈[vj, Vj], where vj is the minimum value of pj while Vj is the maximum value of pj.  For benefit attributes, the normalized value of xij is given as jjjijij vVvxr   ),,2,1;,,2,1( njmi        (1) While for cost attributes, the normalized value of xij is given as jjijjij vVxVr   ),,2,1;,,2,1( njmi          (2) It is clear that10  ijr , and the attribute is more favorable as rij approaches 1.  Empirical test Implementation procedure The empirical test is implemented by the following steps:  (1) Finding effective patent document samples;  (2) Raw indicator value acquisitions;  (3) Normalizing and dimensionless;  (4) Evaluation model applied to valuate patent documents, and identifying the core patent documents wherein;  (5) Investigate the empirical test results by peer review of the technical experts in the given tech field.  Data samples selection The samples are patent documents from the field of high temperature superconductive (HTS) cables. We first spent considerable time on the search strategies. After careful examination and repeated experimental searches, the search algorithm is constructed. Besides, country (regional) distributions analysis shows the top 2 country players in this field are Japan and US, whose patent applications account for 72% of the total (Zhang, 2009b). Therefore the data sampling focuses on these JP and US patent documents on HTS cables, including wire (belt) material thereof.  Outcomes and findings According to the calculation results, the core patent documents in the HTS cable field are identified. To examine the accuracy of the results, we conduct peer reviews. The technical experts being familiar with the HTS cable field are invited and grouped into 2 expert panels. Panel A consists of experts from the Institute of Electrical Engineering of Chinese Academy of Sciences. Their research group have conducted HTS R&D in China for nearly 10 years, and successfully commercialized the first set of cables into the power grid operation. Panel B consists of experts from the University of Electronic Science and Technology of China. The PI of this group once was the researcher of Superconductor application projects of Australian Research Council.  Based on the subjective votes, the 2 panels judged these selected patents. According to Panel A’s judgement, these selected patents revealed the key issues in the preparation of HTS wires, in particular the most advanced second-generation HTS wire technology. And some of them were particularly critical, which were filed by SuperPower, AMSC and Sumitomo, the current global leading players in HTS wire productions, and almost involved the core technologies within this field.  The Panel B agreed with these selected core patent documents. In their view, the top dozen were particularly critical (Table 1). A scorecard was shown by them to better illustrate their comments. By the experts, these selected patents were the core patent in their field. In addition, the 2 panels gave their comments which suggested there are broad prospects for their commercializing and promotion.  Table 1   Scorecard about the selected core patent documents（100-point scale） Ranks Pat. Num. Empirical test score by the model 1 US 6884527 B2 0.51744 2 US 6716795 B2 0.46851 3 US 6466805 B2 0.46250 4 US 6610632 B2 0.42452 5 US 6195870 B1 0.41581 6 US 6420318 B1 0.38342 7 US 5846910 0.38186 8 US 5827798 0.35523 9 US 6745059 B2 0.34930 10 US 6849580 B2 0.33787 11 US 6906008 B2 0.33562 12 US 5874384 A1 0.32831 13 US 7569521 B2 0.31167 Conclusions and future work In this study, basing on the evaluation model proposed in our previous study, we succeed in conducting an empirical test to apply this model to value the core patent documents in a particular field. The empirical result supports the validity of the model, and also successfully demonstrates the operability of the evaluation approach.  However, further efforts should be taken to advance this study. Firstly, this empirical test is based on a small sample of a particular field. It is necessary to have more tests in more other technical fields for further verifying. Secondly, our model aims to facilitate practitioners in patent information analysis especially the patent literature workers. As patent evaluation in practical is a very complex work requiring in-depth knowledge of markets, competitors and technology, it implies that there may be an integrated evaluator synthesizing several models, in which our evaluation model acts as one literature model. We believe that this integrated evaluator would play a greater role. Acknowledgments We are very grateful to the technical experts for providing us with technical information. Also we deeply appreciate the financial supports to this research from the West Light Foundation and the Knowledge Innovation Program of the Chinese Academy of Sciences. References Yoon, K. P. & Hwang, C. L. (2005). Multiple Attribute Decision Making: An Introduction. London: Sage. Zhang, X., Fang S., Tang C., et al. (2009a). Study on indicator system for core patent documents evaluation. In B. Larsen & J. Leta (Ed.), Proceedings of ISSI 2009 Volume 1: (154-164). Rio de Janeiro. ISSI.  Zhang, X., Gao, L. D., Fang, S., et al. (2009b). Patent analysis on high-temperature superconductive cable. Intellectual Property Research Report (pp. 171-232). 

An Empirical Test of the Evaluation Model on Core Patent Documents

An Empirical Test of the Evaluation Model on Core Patent Documents

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National Science Library,Chinese Academy of Sciences