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第2期 常亮，等：知识图谱的推荐系统综述 ·215· 36(2:2250-2259 [26]PEROZZI B,AL-RFOU R,SKIENA S.Deepwalk:On- [14]DODWAD P R.LOBO L.A context-aware recommend- line learning of social representations[C]//ACM, er system using ontology based approach for travel ap- 2014,701-710. plications[J].International journal of advanced engineer- [27]GRAD-GYENGE L.KISS A.FILZMOSER P.Graph ing and nano technology,2014,1(10):8-12. embedding based recommendation techniques on the [15]KETHAVARAPU U P K,SARASWATHI S.Concept knowledge graph[C]//Adjunct Publication of the 25th based dynamic ontology creation for job recommendation Conference on User Modeling,Adaptation and Personal- system[J].Procedia computer science,2016,85:915-921. ization.Bratislava,Slovakia:ACM,2017:354-359. 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Menko Park, USA: AAAI, 2014: 180–186. [33] DESHPANDE O, LAMBA D S, TOURN M, et al. Building, maintaining, and using knowledge bases: A report from the trenches[C]//the 32nd ACM SIGMOD International Conference on Management of Data. New York, USA: ACM, 2013: 1209–1220 [34] ZHANG Daqiang, HSU C H, CHEM Min, et al. Coldstart recommendation using bi-clustering and fusion for large-scale social recommender systems[J]. IEEE transactions on emerging topics in computing, 2014, 2(2): 239–250. [35] HSIEH K L. Employing a recommendation expert system based on mental accounting and artificial neural networks into mining business intelligence for study abroad’s P/S recommendations[J]. Expert systems with applications, 2011, 38(12): 14376–14381. [36] 第 2 期 常亮，等：知识图谱的推荐系统综述 ·215·