[目的/意義]為準確發現高校讀者個性化閱讀需求并預測其發展趨勢,實現圖書館智能服務的個性化定制與推送。[方法/過程]分析高校讀者小數據應用于圖書館個性化智能服務的可行性,圖書館通過高校讀者小數據采集、預處理、個性化閱讀需求發現與預測利用決策推薦機制為高校讀者推送個性化智能服務。[結果/結論]結果表明,高校讀者小數據能夠準確體現其個性化閱讀及知識需求,為圖書館個性化智能服務決策制定和模式構建提供支撐作用。大數據環境下,該研究能提供一定的理論指導和實踐價值。

[Purpose/significance] This paper aims to identify personalized reading needs of university readers,predict its development trend,and realize personalized push services. [Method/process] By analyzing the feasibility of the small data of university readers applying to library personalized intelligent services,libraries push personalized intelligent services combining with small data acquisition,preprocessing,detection and prediction of personalized reading needs with decision recommendation mechanism. [Result/conclusion] Results show that the small data of university readers can accurately reflect their personalized reading and knowledge needs,and provide support for making the decision and constructing the model about personalized intelligent service by library. Under the big data environment,this research can provide some theoretical guidance and practical value.