基于支持向量机的社科查新工作指标体系评价  

Evaluation of the Working Index System of Social Science's Novelty Search Based on Support Vector Machine

作　　者：张群[1] 朱治军[1] 

机构地区：[1]江南大学图书档案馆,江苏无锡214122

出　　处：《情报科学》2014年第7期66-69,77,共5页Information Science

基　　金：教育部人文社会科学研究青年基金项目(10YJC870047);江苏省教育厅高校哲学社会科学指导项目(2011SJD870002)

摘　　要：设计了一套由唯一性、新颖性、规范性、社会性等4个一级指标构成的社科查新工作指标体系。并在此基础上提出了基于支持向量机的社科查新工作指标体系评价模型。仿真结果表明,基于支持向量机的社科查新工作指标体系评价模型准确率较高。从而为查新工作提供了新的评价方法,有广泛的应用前景。This paper designed a set of working index system of social science＇ s novelty search, which includes four first-class indexes as uniqueness, novelty, standardization and sociality. Then based on support vector machine, a social science＇ s novelty search working index system evaluation model was proposed. Simulation results showed that the support vector machine can get the high evaluation accuracy. It provides a new evaluation method for the novelty search work and has a broad application prospect.

关 键 词：支持向量机 社科查新 工作指标 

分 类 号：G250.2[文化科学—图书馆学]