A K-means-based clustering analysis method for biomedical patents

A technology of k-means clustering and cluster analysis, applied in the field of cluster analysis of biomedical patents, can solve problems such as low efficiency, small data samples, and insufficient depth

Inactive Publication Date: 2019-03-08
KUNMING UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Traditional patent data mining has problems such as low efficiency, single dimension, small data sample, and insufficient depth, so it cannot meet the current demand for patent data mining

Method used

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  • A K-means-based clustering analysis method for biomedical patents
  • A K-means-based clustering analysis method for biomedical patents
  • A K-means-based clustering analysis method for biomedical patents

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] Example 1: Analysis of the annual development status of biomedical patent data in Yunnan Province

[0051] Patent preprocessing: The data preprocessing results of the annual development of patents in the biomedical industry in Yunnan Province from 1998 to 2017 are shown in the following table:

[0052]

[0053] Perform K-means cluster analysis, the results are shown in the following table:

[0054]

[0055]

[0056]Result analysis: the cluster with a value of 1 belongs to the first category, including the five years from 1998 to 2002. In the past 5 years, the field of biomedicine has also shown an initial trend in patent applications. Although the number of patent applications has increased at a rate of nearly 1.7 times per year in the past 5 years, the base is relatively low and not representative, but patent awareness has been eliminated by a small number of people. people understand and know. The cluster with a value of 2 is the second category, including ...

Embodiment 2

[0057] Example 2: Cluster analysis of IPC classification numbers of biomedical patent data in Yunnan Province

[0058] Data preprocessing: Through patent data preprocessing, the status information of the IPC classification number of biopharmaceuticals in Yunnan Province is made into a table

[0059]

[0060] Perform K-means cluster analysis, the results are shown in the following table:

[0061]

[0062] Result analysis: Class 1 IPC classification number is A61, in the "International Patent Classification", A61 represents medicine or veterinary medicine, hygiene. The number of patent applications with the IPC classification number A61 is as high as 7,075, and the number of patent authorizations is as high as 5,397, which shows that the technical field of A61 occupies an important position in the biomedical industry of Yunnan Province. Medicine or veterinary medicine and hygiene represent a large scope in the field of biomedicine, so biomedical companies and scientific r...

Embodiment 3

[0063] Example 3: Cluster Analysis of Biomedical Patent Data Applicants in Yunnan Province

[0064] Through patent data preprocessing, the status information of high-yield applicants of biomedical patent data in Yunnan Province was made into a table

[0065]

[0066] Perform K-means cluster analysis, the results are shown in the following table:

[0067]

[0068]

[0069] Result analysis: Kunming University of Science and Technology and Kunming Institute of Botany, Chinese Academy of Sciences are in the first category, and both applicants are scientific research institutions. It is not difficult to see from Table 3 that the two scientific research institutions are significantly ahead of other applicants in the number of patent applications and patent grants. Its patent growth rate and patent effectiveness rate also tend to be relatively high. The four scientific research institutions, Yunnan University, Kunming Institute of Zoology, Chinese Academy of Sciences, Yunn...

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Abstract

The invention relates to a K-means-based clustering analysis method for biomedical patents, which belongs to the field of information retrieval technology. At present, with the development of technology, the number of patents has increased dramatically. Patent information, as the most effective carrier of technical intelligence, hides a lot of technical information. Traditional patent data mininghas some problems, such as low efficiency, single dimension, small data sample and insufficient depth, which can not meet the needs of patent data mining nowadays. 4 important evaluation indexes of patent application quantity, patent grant quantity, patent growth rate and patent efficiency in patent analysis are simultaneously selected as clustering variables for clustering analysis. This method can deeply mine the association between the data, better classify the patent data, and make the clustering results more integrated to make up for the shortcomings of the traditional patent data analysis.

Description

technical field [0001] The invention relates to a biomedical patent cluster analysis method based on K-means, belonging to the technical field of information retrieval. Background technique [0002] Before the extension of data mining technology to patent literature mining, patent information, as the most effective carrier of technical intelligence, hides a large amount of technical information. Traditional patent data mining has problems such as low efficiency, single dimension, small data sample, and insufficient depth, so it cannot meet the current demand for patent data mining. The present invention proposes a biomedical patent cluster analysis method based on hierarchical clustering, which simultaneously selects four important evaluation indicators of patent application volume, patent authorization volume, patent growth rate, and patent effectiveness rate as clustering variables for cluster analysis. This method can deeply mine the relationship between data, better cl...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/35G06K9/62
CPCG06F18/23213
Inventor 姜迪叶波马军
Owner KUNMING UNIV OF SCI & TECH
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