摘要
为提高科技查新的效率,利用信息化技术对查新业务流程进行优化重构,在常规查新系统的基础上构建了一个智能的科技查新系统;系统设计时首先利用网络爬虫技术自动按照科技项目申请书的关键词搜索和下载相关文献资源,然后以自适应分配算法分配查新任务和遴选查新报告审核专家,最后以系统中累计的以往查新报告和文献资料为基础,利用Lucene检索工具对生成的查新报告进行全文检索;一是实现了文献资源检索工作的自动化,保证了检索途径、范围及检索表达式的全面性和准确性,避免了大量的人工检索,提高了文献检索效率;二是实现了任务分配的智能化,均衡分配相关任务,使查新效率最大化;三是实现与既往研究项目进行精确比对,避免了科技项目的重复申报,进一步提高查新质量。
In order to improve the efficiency of sci-tech novelty retrieval,an intelligent sci-tech novelty retrieval system is constructed on the basis of conventional novelty retrieval system by using information technology to optimize and reconstruct the business process of sci-tech novelty retrieval.Firstly,the network crawler technology was used to search and download the relevant literature resources automatically according to the keywords of the application for scientific and technological projects.Secondly,the self-adaptive allocation algorithm was used to assign the task of novelty search and select the experts to audit the novelty search reports.Finally,based on the accumulated previous novelty search reports and literature in the system,the full-text search of the generated novelty search reports was carried out by using Lucene search tool.First,it realizes the automation of literature resources retrieval,guarantees the comprehensiveness and accuracy of retrieval approach,scope and expression,avoids a large number of manual searches and improves the efficiency of literature retrieval.Second,it realizes the intelligence of task allocation,balances the distribution of related tasks,and maximizes the efficiency of novelty retrieval.Third,it realizes accurate comparison with previous research projects,avoids duplicate declaration of scientific and technological projects,and further improves the quality of novelty search.
作者
黄孝伦
王东
谭涛
刘芹
Huang Xiaolun;Wang Dong;Tan Tao;Liu Qin(Chongqing City Sanitation Information Center,Chongqing 401120,China)
出处
《计算机测量与控制》
2020年第2期202-205,共4页
Computer Measurement &Control
基金
重庆市科委决策咨询项目(cstc2016jccx BX0067)
关键词
科技查新
网络爬虫
全文检索
自适应分配模型
Sci-tech novelty search
internet crawler
full-text retrieval
adaptive allocation model
