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Explainable Interaction-driven User Modeling over Knowledge Graph for Sequential Recommendation

https://doi.org/10.1145/3343031.3350893
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17/17 checkable references clean · checked 2026-07-25

Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.

16 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.

The 17 checked references that resolve
resolves10.1145/3038912.3052569
Neural Collaborative Filtering
resolves10.1145/2959100.2959167
Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations
resolves10.1145/3219819.3219965
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model
resolves10.1145/3209978.3210017
Improving Sequential Recommendation with Knowledge-Enhanced Memory Networks
resolves10.1145/3209219.3209270
Sequence-aware Recommender Systems
resolves10.1145/3109859.3109896
Personalizing Session-based Recommendations with Hierarchical Recurrent Neural Networks
resolves10.1145/1772690.1772773
Factorizing personalized Markov chains for next-basket recommendation
resolves10.1145/2806416.2806528
Semantic Path based Personalized Recommendation on Weighted Heterogeneous Information Networks
resolves10.1145/2481244.2481248
Mining heterogeneous information networks
resolves10.1145/3240323.3240361
Recurrent knowledge graph embedding for effective recommendation
resolves10.1145/2911451.2914683
A Dynamic Recurrent Model for Next Basket Recommendation
resolves10.1145/2556195.2556259
Personalized entity recommendation
resolves10.1145/2939672.2939673
Collaborative Knowledge Base Embedding for Recommender Systems
resolves10.1162/dint_a_00008
KB4Rec: A Data Set for Linking Knowledge Bases with Recommender Systems
The 16 references without a DOI — listed, not checked
no DOI — not checkedDzmitry Bahdanau , Kyunghyun Cho , and Yoshua Bengio . 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 ( 2014 ). Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014. Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473 (2014).
no DOI — not checkedAntoine Bordes Nicolas Usunier Alberto Garcia-Duran Jason Weston and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems. 2787--2795. Antoine Bordes Nicolas Usunier Alberto Garcia-Duran Jason Weston and Oksana Yakhnenko. 2013. Translating embeddings for modeling multi-relational data. In Advances in neural information processing systems. 2787--2795.
no DOI — not checkedYixin Cao , Xiang Wang , Xiangnan He , Tat-Seng Chua , et almbox . 2019 . Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences . arXiv preprint arXiv:1902.06236 (2019). Yixin Cao, Xiang Wang, Xiangnan He, Tat-Seng Chua, et almbox. 2019. Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences. arXiv preprint arXiv:1902.06236 (2019).
no DOI — not checkedChen Cheng , Haiqin Yang , Michael R Lyu , and Irwin King . 2013 . Where You Like to Go Next: Successive Point-of-Interest Recommendation .. In IJCAI , Vol. 13. 2605 -- 2611 . Chen Cheng, Haiqin Yang, Michael R Lyu, and Irwin King. 2013. Where You Like to Go Next: Successive Point-of-Interest Recommendation.. In IJCAI , Vol. 13. 2605--2611.
no DOI — not checkedLi Gao , Hong Yang , Jia Wu , Chuan Zhou , Weixue Lu , and Yue Hu. 2018. Recommendation with multi-source heterogeneous information. structure , Vol. 1 , w3 ( 2018 ), w4. Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu, and Yue Hu. 2018. Recommendation with multi-source heterogeneous information. structure , Vol. 1, w3 (2018), w4.
no DOI — not checkedBenjamin Heitmann and Conor Hayes . 2010. Using linked data to build open, collaborative recommender systems . In 2010 AAAI Spring Symposium Series . Benjamin Heitmann and Conor Hayes. 2010. Using linked data to build open, collaborative recommender systems. In 2010 AAAI Spring Symposium Series .
no DOI — not checkedBalázs Hidasi , Alexandros Karatzoglou , Linas Baltrunas , and Domonkos Tikk . 2015. Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939 ( 2015 ). Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk. 2015. Session-based recommendations with recurrent neural networks. arXiv preprint arXiv:1511.06939 (2015).
no DOI — not checkedTomas Mikolov , Edouard Grave , Piotr Bojanowski , Christian Puhrsch , and Armand Joulin . 2018 . Advances in Pre-Training Distributed Word Representations . In Proceedings of the International Conference on Language Resources and Evaluation (LREC 2018) . Tomas Mikolov, Edouard Grave, Piotr Bojanowski, Christian Puhrsch, and Armand Joulin. 2018. Advances in Pre-Training Distributed Word Representations. In Proceedings of the International Conference on Language Resources and Evaluation (LREC 2018) .
no DOI — not checkedSteffen Rendle , Christoph Freudenthaler , Zeno Gantner , and Lars Schmidt-Thieme . 2009 . BPR: Bayesian personalized ranking from implicit feedback . In Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence. AUAI Press, 452--461 . Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the twenty-fifth conference on uncertainty in artificial intelligence. AUAI Press, 452--461.
no DOI — not checkedAshish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez Łukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 6000--6010. Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez Łukasz Kaiser and Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information Processing Systems. 6000--6010.
no DOI — not checkedHongwei Wang , Fuzheng Zhang , Miao Zhao , Wenjie Li , Xing Xie , and Minyi Guo . 2019. Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation. arXiv preprint arXiv:1901.08907 ( 2019 ). Hongwei Wang, Fuzheng Zhang, Miao Zhao, Wenjie Li, Xing Xie, and Minyi Guo. 2019. Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation. arXiv preprint arXiv:1901.08907 (2019).
no DOI — not checkedXiang Wang , Dingxian Wang , Canran Xu , Xiangnan He , Yixin Cao , and Tat-Seng Chua . 2018a. Explainable Reasoning over Knowledge Graphs for Recommendation. arXiv preprint arXiv:1811.04540 ( 2018 ). Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao, and Tat-Seng Chua. 2018a. Explainable Reasoning over Knowledge Graphs for Recommendation. arXiv preprint arXiv:1811.04540 (2018).
no DOI — not checkedSvante Wold , Kim Esbensen , and Paul Geladi . 1987. Principal component analysis. Chemometrics and intelligent laboratory systems , Vol. 2 , 1--3 ( 1987 ), 37--52. Svante Wold, Kim Esbensen, and Paul Geladi. 1987. Principal component analysis. Chemometrics and intelligent laboratory systems , Vol. 2, 1--3 (1987), 37--52.
no DOI — not checkedYongfeng Zhang and Xu Chen . 2018. Explainable recommendation: A survey and new perspectives. arXiv preprint arXiv:1804.11192 ( 2018 ). Yongfeng Zhang and Xu Chen. 2018. Explainable recommendation: A survey and new perspectives. arXiv preprint arXiv:1804.11192 (2018).
no DOI — not checkedYuyu Zhang , Hanjun Dai , Chang Xu , Jun Feng , Taifeng Wang , Jiang Bian , Bin Wang , and Tie-Yan Liu . 2014 . Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks .. In AAAI , Vol. 14. 1369 -- 1375 . Yuyu Zhang, Hanjun Dai, Chang Xu, Jun Feng, Taifeng Wang, Jiang Bian, Bin Wang, and Tie-Yan Liu. 2014. Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks.. In AAAI , Vol. 14. 1369--1375.
no DOI — not checkedChang Zhou , Jinze Bai , Junshuai Song , Xiaofei Liu , Zhengchao Zhao , Xiusi Chen , and Jun Gao . 2018 . Atrank: An attention-based user behavior modeling framework for recommendation . In Thirty-Second AAAI Conference on Artificial Intelligence . Chang Zhou, Jinze Bai, Junshuai Song, Xiaofei Liu, Zhengchao Zhao, Xiusi Chen, and Jun Gao. 2018. Atrank: An attention-based user behavior modeling framework for recommendation. In Thirty-Second AAAI Conference on Artificial Intelligence .
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