本文選題：數(shù)字資源聚合 + 語義相似度　； 參考：《情報學(xué)報》2017年05期

【摘要】：隨著國內(nèi)外數(shù)字資源聚合以及服務(wù)推薦研究的不斷深入,聚合及服務(wù)推薦方法的改進(jìn)和融合也成為學(xué)術(shù)研究熱點。本文綜合運用聚類分析、語義相似度計算、協(xié)同過濾推薦算法等方法,提出了基于領(lǐng)域本體的數(shù)字文獻(xiàn)資源聚合及服務(wù)推薦的方法和途徑,并以知網(wǎng)文獻(xiàn)資源為例,對本文提出的方法流程進(jìn)行分析研究。結(jié)果表明,該方法能夠?qū)?shù)字文獻(xiàn)資源有效聚合,并挖掘用戶需求信息,根據(jù)用戶偏好對其進(jìn)行推薦。本文不僅為資源聚合與服務(wù)推薦的深入研究搭建了一個新的框架,同時也為資源聚合以服務(wù)推薦理論拓展性研究提供了一個新的思路。通過本體、數(shù)據(jù)挖掘以及服務(wù)推薦等方法,對數(shù)字圖書館文獻(xiàn)資源聚合以及服務(wù)推薦進(jìn)行研究,從而為優(yōu)化其資源再組織結(jié)構(gòu)和提升知識服務(wù)能力提供有價值的參考與指導(dǎo)。
[Abstract]:With the development of digital resource aggregation and service recommendation research at home and abroad, the improvement and integration of aggregation and service recommendation methods has become a hot topic of academic research. Based on cluster analysis, semantic similarity calculation, collaborative filtering and recommendation algorithm, this paper puts forward the methods and approaches of domain ontology based digital literature resource aggregation and service recommendation. The flow of the method proposed in this paper is analyzed and studied. The results show that this method can effectively aggregate the digital document resources and mine the information of users' needs and recommend them according to their preferences. This paper not only provides a new framework for the research of resource aggregation and service recommendation, but also provides a new idea for the research of resource aggregation based on the theory of service recommendation. Through the methods of ontology, data mining and service recommendation, this paper studies the document resource aggregation and service recommendation of digital library, which provides valuable reference and guidance for optimizing the resource reorganizing structure and enhancing the knowledge service ability.
【作者單位】： 吉林大學(xué)管理學(xué)院;
【基金】：國家自然科學(xué)基金，

本文編號：1985677