机器学习在外文电子资源评价中的应用

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The Application of Machine Learning in the Evaluation of Foreign Electronic Resources

Abstract Establishing ascientificand efficient method for evaluating electronic resources isa crucial task in the development of university library resourcesand theenhancement of service quality.This paper focuses on foreign electronicresourcesandestablishestwodistincttypesofevaluation indexsystems：onefor foreign journal ful-text databases，the other for foreign abstract databases.Using machine learning models，the study builds feature engineering forthe indicator data，performs normalization，dimensionalityreduction，and featureselection，followed bymodel construction，training，andthetuningandevaluationof different models.TheKNNalgorithm isultimatelyidentifiedas theoptimalmodel，which isthenusedforobjectiveevaluationofforeignelectronicresources.Theresults indicatethat machine learning models，compared with traditional evaluation methods，provide more accurate and eficient predictions， guiding electronic resource optimization inamore objective manner，thereby enabling libraries to make data-driven decisions.

Key Words machine learning; university libraries; electronic resources; evaluation indicators

1引言

电子资源是高校图书馆文献资源建设不可或缺的组成部分，其中外文电子资源对于提升高校教学和科研的国际化水平具有重要意义。（剩余8075字）