[1]CHANG Liang,ZHANG Weitao,GU Tianlong,et al.Review of recommendation systems based on knowledge graph[J].CAAI Transactions on Intelligent Systems,2019,14(2):207-216.[doi:10.11992/tis.201805001]
Copy

Review of recommendation systems based on knowledge graph

References:
[1] XIONG Haitao, LIU Zhengbin. A situation information integrated personalized travel package recommendation approach based on TD-LDA model[C]//2015 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC). Nanjing, China:IEEE, 2015:32-37.
[2] 常亮, 曹玉婷, 孙文平, 等. 旅游推荐系统研究综述[J]. 计算机科学, 2017, 44(10):1-6 CHANG Liang, CAO Yuting, SUN Wenping, et al. Review of tourism recommendation system[J]. Computer science, 2017, 44(10):1-6
[3] 孟祥武, 纪威宇, 张玉杰. 大数据环境下的推荐系统[J]. 北京邮电大学学报, 2015, 38(2):1-15 MENG Xiangwu, JI Weiyu, ZHANG Yujie. A survey of recommendation systems in big data[J]. Journal of Beijing university of posts and telecommunications, 2015, 38(2):1-15
[4] 刘峤, 李杨, 段宏, 等. 知识图谱构建技术综述[J]. 计算机研究与发展, 2016, 53(3):582-600 LIU Yu, LI Yang, DUAN Hong, et al. Knowledge graph construction techniques[J]. Journal of computer research and development, 2016, 53(3):582-600
[5] LUBERG A, TAMMET T, J?RV P. Smart city:A rule-based tourist recommendation system[M]//LAW R, FUCHS M, RICCI F. Information and Communication Technologies in Tourism 2011. Vienna, Austria:Springer, 2011:51-62.
[6] TONG Rong, XUE Lijuan, WANG Haofen, et al. Building and exploring an enterprise knowledge graph for investment analysis[M]//GROTH P, SIMPERL E, GRAY A, et al. The Semantic Web-ISWC 2016. Cham, Germany:Springer International Publishing, 2016:418-436.
[7] 漆桂林, 高桓, 吴天星. 知识图谱研究进展[J]. 情报工程, 2017, 3(1):4-25 QI Guilin, GAO Huan, WU Tianxing. The research advances of knowledge graph[J]. Technology information engineering, 2017, 3(1):4-25
[8] SZEKELY P, KNOBLOCK C A, SLEPICKA J, et al. Building and using a knowledge graph to combat human trafficking[C]//2015 International Semantic Web Conference on. New York, USA:Springer-Verlag, 2015:205-221.
[9] 唐晓波, 魏巍. 基于本体的推荐系统研究综述[J]. 图书馆学研究, 2016(18):7-12, 58 TANG Xiaobo, WEI Wei. A survey of ontology-based recommendation systems[J]. Library science studies, 2016(18):7-12, 58
[10] LI Dongsheng, LV Qin, XIE Xing, et al. Interest-based real-time content recommendation in online social communities[J]. Knowledge-based systems, 2012, 28:1-12.
[11] 印鉴, 王智圣, 李琪, 等. 基于大规模隐式反馈的个性化推荐[J]. 软件学报, 2014, 25(9):1953-1966 YIN Jian, WANG Zhisheng, LI Qi, et al. Personalized recommendation based on large-scale implicit feedback[J]. Journal of software, 2014, 25(9):1953-1966
[12] 王立才, 孟祥武, 张玉洁. 上下文感知推荐系统[J]. 软件学报, 2012, 23(1):1-20 WANG Licai, MENG Xiangwu, ZHANG Yujie. Context-aware recommendation systems[J]. Journal of software, 2012, 23(1):1-20
[13] NIARAKI A S, KIM K. Ontology based personalized route planning system using a multi-criteria decision making approach[J]. Expert systems with applications, 2009, 36(2):2250-2259.
[14] DODWAD P R, LOBO L. A context-aware recommender system using ontology based approach for travel applications[J]. International journal of advanced engineering and nano technology, 2014, 1(10):8-12.
[15] KETHAVARAPU U P K, SARASWATHI S. Concept based dynamic ontology creation for job recommendation system[J]. Procedia computer science, 2016, 85:915-921.
[16] MORENO A, VALLS A, ISERN D, et al. SigTur/E-destination:Ontology-based personalized recommendation of tourism and leisure activities[J]. Engineering applications of artificial intelligence, 2013, 26(1):633-651.
[17] PASSANT A. dbrec-music recommendations using DBpedia[M]//PATEL-SCHNEIDER P F, PAN Yue, HITZLER P, et al. The Semantic Web-ISWC 2010. Berlin Heidelberg, Germany:Springer, 2010:209-224.
[18] DI NOIA T, MIRIZZI R, OSTUNI V C, et al. Linked open data to support content-based recommender systems[C]//Proceedings of the 8th International Conference on Semantic Systems. Graz, Austria:ACM, 2012:1-8.
[19] DI NOIA T, CANTADOR I, OSTUNI V C. Linked open data-enabled recommender systems:ESWC 2014 challenge on book recommendation[M]//PRESUTTI V, STANKOVIC M, CAMBRIA E, et al. Semantic Web Evaluation Challenge. Cham, Germany:Springer International Publishing, 2014:129-143.
[20] LU Chun, LAUBLET P, STANKOVIC M. Travel attractions recommendation with knowledge graphs[C]//European Knowledge Acquisition Workshop. Bologna, Italy:Springer, 2016.
[21] ORAMAS S, OSTUNI V C, DI NOIA T, et al. Sound and music recommendation with knowledge graphs[J]. ACM transactions on intelligent systems & technology, 2017, 8(2):21.
[22] HEITMANN B, HAYES C. Using linked data to build open, collaborative recommender systems[C]//Linked Data Meets Artificial Intelligence. Stanford, California, USA:AAAI, 2010.
[23] OSTUNI V C, DI NOIA T, DI SCIASCIO E, et al. Top-N recommendations from implicit feedback leveraging linked open data[C]//Proceedings of the 7th ACM Conference on Recommender Systems. Hong Kong, China:ACM, 2013:85-92.
[24] RISTOSKI P, MENCIA E L, PAULHEIM H. A hybrid multi-strategy recommender system using linked open data[C]//Semantic Web Evaluation Challenge. Cham, Germany:Springer, 2014, 475:150-156.
[25] TING K M, WITTEN I H. Issues in stacked generalization[J]. Artificial intelligence research, 1999,10(1).
[26] PEROZZI B, AL-RFOU R, SKIENA S. Deepwalk:Online learning of social representations[C]//ACM, 2014,701-710.
[27] GRAD-GYENGE L, KISS A, FILZMOSER P. Graph embedding based recommendation techniques on the knowledge graph[C]//Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization. Bratislava, Slovakia:ACM, 2017:354-359.
[28] WANG Meng, LIU Mengyue, LIU Jun, et al. Safe medicine recommendation via medical knowledge graph embedding[EB/OL]. arXiv:1710.05980, 2017.
[29] PALUMBO E, RIZZO G, TRONCY R. entity2rec:Learning user-item relatedness from knowledge graphs for top-N item recommendation[C]//Eleventh ACM Conference on Recommender Systems. Como, Italy:ACM, 2017:32-36.
[30] GRAD-GYENGE L, FILZMOSER P. Recommendation Techniques on a Knowledge Graph for Email Remarketing[C]//eKNOW 2016 The Eighth International Conference on Information, Process, and Knowledge Management. Venice, Italy:IARIA, 2016.
[31] LIU Xiaohua, ZHANG Shaodian, WEI Furu, et al. Recognizing named entities in tweets[C]//49th Annual Meeting of the Association for Computational Linguistics; Human Language Technologies. Stroudsburg, PA, USA:ACL, 2011:359-367.
[32] FELLBAUM C. WordNet[M]//The Encyclopedia of Applied Linguistics. Blackwell:Blackwell Publishing Ltd, 2012:231-243.
[33] WANG Zhigang, LI Juanzi, LI Shuanjie, et al. Cross-lingual knowledge validation based taxonomy derivation from heterogeneous online wikis[C]//28th Conference on Artificial Intelligence. Menko Park, USA:AAAI, 2014:180-186.
[34] 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
[35] ZHANG Daqiang, HSU C H, CHEM Min, et al. Cold-start 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.
[36] 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.
[37] 薛福亮, 马莉. 利用动态产品分类树改进的关联规则推荐方法[J]. 计算机工程与应用, 2016, 52(4):135-141 XUE Fuliang, MA Li. Improved association rule recommendation method based on dynamic product taxonomy[J]. Computer engineering and applications, 2016, 52(4):135-141
[38] LU E H C, FANG S H, TSENG V S. Integrating tourist packages and tourist attractions for personalized trip planning based on travel constraints[J]. GeoInformatica, 2016, 20(4):741-763.
[39] LI Ting, LIU Anfeng, HUANG Changqin. A similarity scenario-based recommendation model with small disturbances for unknown items in social networks[J]. IEEE Access, 2017, 4:9251-9272.
[40] GRüN C, NEIDHARDT J, WERTHNER H. Ontology-based matchmaking to provide personalized recommendations for tourists[M]//SCHEGG R, STANGL B. Information and Communication Technologies in Tourism 2017. Cham:Springer International Publishing, 2017.
[41] 朱郁筱, 吕琳媛. 推荐系统评价指标综述[J]. 电子科技大学学报, 2012, 41(2):163-175 ZHU Yuxi, Lü Linyuan. Evaluation metrics for recommender systems[J]. Journal of university of electronic science and technology, 2012, 41(2):163-175
[42] VARGAS S, CASTELLS P. Rank and relevance in novelty and diversity metrics for recommender systems[C]//5th ACM Conference on Recommender Systems. Chicago, USA:ACM, 2011:109-116.
[43] CATHERINE R, COHEN W. Personalized recommendations using knowledge graphs:A probabilistic logic programming approach[C]//10th ACM Conference on Recommender Systems. Boston, USA:ACM, 2016:325-332.
[44] LI Haoyang, WU Yuanxu, XIA Wei. Review on state-of-the-art technologies and algorithms on recommendation system[C]//2016 International Conference on Mechatronics Engineering and Information Technology. 2016.
[45] MAYER-SCHNBERGER V, CUKIER K. Big data:A revolution that will transform how we live, work, and think[M]. Eamon Dolan/Houghton Mifflin Harcourt, 2014.
[46] KETHAVARAPU U P K, SARASWATHI S. Concept based dynamic ontology creation for job recommendation system[J]. Procedia computer science, 2016, 85:915-921.
[47] OSTUNI V C, DI NOIA T, MIRIZZI R, et al. A linked data recommender system using a neighborhood-based graph kernel[M]//International Conference on Electronic Commerce and Web Technologies. Cham:Springer International Publishing, 2014:89-100.
[48] FENG Xiaodong, SHARMA A, SRIVASTAVA J, et al. Social network regularized sparse linear model for Top-N, recommendation[J]. Engineering applications of artificial intelligence, 2016, 51:5-15.
[49] LIU Juntao, WU Caihua. Deep learning based recommendation:a survey[M]//International Conference on Information Science and Applications 2017. Singapore:Springer, 2017.
[50] WANG Quan, MAO Zhendong, WANG Bin, et al. Knowledge graph embedding:A survey of approaches and applications[J]. IEEE transactions on knowledge and data engineering, 2017, 29(12):2724-2743.
Similar References:

Memo

-

Last Update: 2019-04-25

Copyright © CAAI Transactions on Intelligent Systems