{"type":"ScholarlyArticle","title":"Augmenting Transfer Learning with Semantic Reasoning","authors":[{"name":"Freddy Lécué","slug":"freddy-lecue","given":"Freddy","family":"Lecue","affiliation":"CortAIx Thales , Montreal , Canada; Inria , Sophia Antipolis , France"},{"name":"Jiaoyan Chen","slug":"jiaoyan-chen","given":"Jiaoyan","family":"Chen","affiliation":"Department of Computer Science , University of Oxford , UK"},{"name":"Jeff Z. Pan","slug":"jeff-z-pan","given":"Jeff Z.","family":"Pan","affiliation":"Department of Computer Science , The University of Aberdeen , UK; Edinburgh Research Centre , Huawei , UK"},{"name":"Huajun Chen","slug":"huajun-chen","given":"Huajun","family":"Chen","affiliation":"College of Computer Science , Zhejiang University , China; ZJU-Alibaba Joint Lab on Knowledge Engine , China"}],"abstract":"Transfer learning aims at building robust prediction models by transferring knowledge gained from one problem to another. In the semantic Web, learning tasks are enhanced with semantic representations. We exploit their semantics to augment transfer learning by dealing with when to transfer with semantic measurements and what to transfer with semantic embeddings. We further present a general framework that integrates the above measurements and embeddings with existing transfer learning algorithms  for higher performance. It has demonstrated to be robust in two real-world applications: bus delay forecasting and air quality forecasting.","doi":"10.24963/ijcai.2019/246","url":"https://ijcai.org/proceedings/2019/246","pdf":"https://ijcai.org/proceedings/2019/0246.pdf","markdown":"https://ijcai.org/proceedings/2019/246.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/246","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Knowledge Representation and Reasoning","track":"Main track","number":246,"pages":{"first":1779,"last":1785},"keywords":["Machine Learning: Knowledge-based Learning","Machine Learning: Transfer, Adaptation, Multi-task Learning","Knowledge Representation and Reasoning: Description Logics and Ontologies"],"videos":[],"references":[{"position":1,"raw":"Intra-Domain] RF TL [Intra-Domain] SGD TL [Intra-Domain] AB Plain [Intra-Domain] AB TL [Inter-Domain] RF TL [Inter-Domain] SGD TL [Inter-Domain] AB Plain [Inter-Domain] AB TL References Baader et al., 2005] Franz Baader, Sebastian Brandt, and Carsten Lutz. Pushing the el envelope. In IJCAI, pages 364-369, 2005.","title":"Intra-Domain] RF TL [Intra-Domain] SGD TL [Intra-Domain] AB Plain [Intra-Domain] AB TL [Inter-Domain] RF TL","authors":"Franz Baader, Sebastian Brandt, Carsten Lutz","year":"2005","venue":"IJCAI","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bechhofer et al., 2004] Sean Bechhofer, Frank Van Harme- len, Jim Hendler, Ian Horrocks, Deborah L McGuinness, Peter F Patel-Schneider, Lynn Andrea Stein, et al. Owl web ontology language reference. W3C recommendation, 10(02), 2004.","title":"Owl web ontology language reference","authors":"Sean Bechhofer, Frank Van Harmelen, Jim Hendler, Ian Horrocks, Deborah L Mcguinness, Peter F Patel-Schneider, Lynn Andrea Stein","year":"2004","venue":"W3C recommendation","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Benavides-Prado et al., 2017] Diana Benavides-Prado, Yun Sing Koh, and Patricia Riddle. AccGenSVM: Selectively transferring from previous hypotheses. In IJCAI, pages 1440-1446, 2017.","title":"AccGenSVM: Selectively transferring from previous hypotheses","authors":"Diana Benavides-Prado, Yun Sing Koh, Patricia Riddle","year":"2017","venue":"IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2017/199"},{"position":4,"raw":"[Bishop, 2006] Christopher M Bishop. Pattern recognition. Machine Learning, 128:1-58, 2006.","title":"Pattern recognition","authors":"M Christopher, Bishop","year":"2006","venue":"Machine Learning","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Chen et al., 2015] Jiaoyan Chen, Huajun Chen, Daning Hu, Jeff Z Pan, and Yalin Zhou. Smog disaster forecasting using social web data and physical sensor data. In 2015 IEEE International Conference on Big Data (Big Data), pages 991-998. IEEE, 2015.","title":"Smog disaster forecasting using social web data and physical sensor data","authors":"Chen","year":"2015","venue":"2015 IEEE International Conference on Big Data (Big Data)","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Chen et al., 2017] Jiaoyan Chen, Freddy Lécué, Jeff Z Pan, and Huajun Chen. Learning from ontology streams with semantic concept drift. In IJCAI, pages 957-963, 2017.","title":"Learning from ontology streams with semantic concept drift","authors":"Chen","year":"2017","venue":"IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2017/133"},{"position":7,"raw":"[Chen et al., 2018] Jiaoyan Chen, Freddy Lécué, Jeff Z. Pan, Ian Horrocks, and Huajun Chen. Knowledge-based trans- fer learning explanation. In KR, pages 349-358, 2018.","title":"Knowledge-based transfer learning explanation","authors":"Chen","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Choi et al., 2016] Jonghyun Choi, Sung Ju Hwang, Leonid Sigal, and Larry S Davis. Knowledge transfer with inter- active learning of semantic relationships. In AAAI, pages 1505-1511, 2016.","title":"Knowledge transfer with interactive learning of semantic relationships","authors":"Jonghyun Choi, Sung Ju Hwang, Leonid Sigal, Larry S Davis","year":"2016","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Dai et al., 2007] Wenyuan Dai, Qiang Yang, Gui-Rong Xue, and Yong Yu. Boosting for transfer learning. In Pro- ceedings of the 24th international conference on Machine learning, pages 193-200. ACM, 2007.","title":"Boosting for transfer learning","authors":"Wenyuan Dai, Qiang Yang, Gui-Rong Xue, Yong Yu","year":"2007","venue":"Proceedings of the 24th international conference on Machine learning","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Dai et al., 2009] Wenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, and Yong Yu. Translated learning: Transfer learning across different feature spaces. In Ad- vances in neural information processing systems, pages 353-360, 2009.","title":"Translated learning: Transfer learning across different feature spaces","authors":"Wenyuan Dai, Yuqiang Chen, Gui-Rong Xue, Qiang Yang, Yong Yu","year":"2009","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Davis and Domingos, 2009] Jesse Davis and Pedro Domin- gos. Deep transfer via second-order Markov Logic. In ICML, pages 217-224, 2009.","title":"Jesse Davis and Pedro Domingos. Deep transfer via second-order Markov Logic","authors":"Domingos Davis","year":"2009","venue":"ICML","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Du et al., 2019] Jianfeng Du, Jeff Z. Pan, Sylvia Wang, Yuming Shen Kunxun Qi, and Yu Deng. Validation of Growing Knowledge Graphs by Abductive Text Evi- dences. In the Proc. of the 33rd National Conference on Artificial Intelligence (AAAI 2019), 2019.","title":"Validation of Growing Knowledge Graphs by Abductive Text Evidences","authors":"Jianfeng Du, Jeff Z Pan, Sylvia Wang, Yuming Shen Kunxun, Yu Qi, Deng","year":"2019","venue":"the Proc. of the 33rd National Conference on Artificial Intelligence (AAAI 2019)","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Lécué and Pan, 2015] Freddy Lécué and Jeff Z Pan. Con- sistent knowledge discovery from evolving ontologies. In AAAI, pages 189-195, 2015.","title":"Consistent knowledge discovery from evolving ontologies","authors":"Pan Lécué, Freddy Lécué, Jeff Z Pan","year":"2015","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Lécué, 2015] Freddy Lécué. Scalable maintenance of knowledge discovery in an ontology stream. In IJCAI, pages 1457-1463, 2015.","title":"Freddy Lécué. Scalable maintenance of knowledge discovery in an ontology stream","authors":"Lécué","year":"2015","venue":"IJCAI","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Lee et al., 2017] Jaekoo Lee, Hyunjae Kim, Jongsun Lee, and Sungroh Yoon. Transfer learning for deep learning on graph-structured data. In AAAI, pages 2154-2160, 2017.","title":"Transfer learning for deep learning on graph-structured data","authors":"Lee","year":"2017","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Long et al., 2015] Mingsheng Long, Yue Cao, Jianmin Wang, and Michael I. Jordan. Learning transferable fea- tures with deep adaptation networks. In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015, pages 97-105, 2015.","title":"Learning transferable features with deep adaptation networks","authors":"Mingsheng Long, Yue Cao, Jianmin Wang, Michael I Jordan","year":"2015","venue":"Proceedings of the 32nd International Conference on Machine Learning, ICML 2015","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Lv et al., 2012] Wenlong Lv, Weiran Xu, and Jun Guo. Transfer learning in classification based on semantic anal- ysis. In Computer Science and Network Technology (ICC- SNT), 2012 2nd International Conference on, pages 1336- 1339. IEEE, 2012.","title":"Transfer learning in classification based on semantic analysis","authors":"Wenlong Lv, Weiran Xu, Jun Guo","year":"2012","venue":"Computer Science and Network Technology (ICC-SNT), 2012 2nd International Conference on","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Mihalkova and Mooney, 2009] L. Mihalkova and R. J. Mooney. Transfer learning from minimal target data by mapping across relational domains, 2009.","title":"Transfer learning from minimal target data by mapping across relational domains","authors":"L Mihalkova, R J Mooney","year":"2009","venue":null,"doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Mihalkova et al., 2007] Lilyana Mihalkova, Tuyen Huynh, and Raymond J. Mooney. Mapping and revising Markov Logic Networks for transfer learning. In AAAI, pages 608- 614, 2007.","title":"Mapping and revising Markov Logic Networks for transfer learning","authors":"Lilyana Mihalkova, Tuyen Huynh, Raymond J Mooney","year":"2007","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Nickel et al., 2016] Maximilian Nickel, Kevin Murphy, Volker Tresp, and Evgeniy Gabrilovich. A review of re- lational machine learning for knowledge graphs. Proceed- ings of the IEEE, 104(1):11-33, 2016.","title":"A review of relational machine learning for knowledge graphs","authors":"Maximilian Nickel, Kevin Murphy, Evgeniy Volker Tresp, Gabrilovich","year":"2016","venue":"Proceedings of the IEEE","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Pan and Thomas, 2007] Jeff Z. Pan and Edward Thomas. Approximating OWL-DL Ontologies. In the Proc. of the 22nd National Conference on Artificial Intelligence (AAAI-07), pages 1434-1439, 2007.","title":"Approximating OWL-DL Ontologies","authors":"Jeff Z Pan, Edward Thomas","year":"2007","venue":"the Proc. of the 22nd National Conference on Artificial Intelligence (AAAI-07)","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Pan and Yang, 2010] Sinno Jialin Pan and Qiang Yang. A survey on transfer learning. IEEE Transactions on knowl- edge and data engineering, 22(10):1345-1359, 2010.","title":"A survey on transfer learning","authors":"Jialin Sinno, Qiang Pan, Yang","year":"2010","venue":"IEEE Transactions on knowledge and data engineering","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Pan et al., 2011] Sinno Jialin Pan, Ivor W Tsang, James T Kwok, and Qiang Yang. Domain adaptation via transfer component analysis. IEEE Transactions on Neural Net- works, 22(2):199-210, 2011.","title":"Domain adaptation via transfer component analysis","authors":"Ivor W Sinno Jialin Pan, James T Tsang, Qiang Kwok, Yang","year":"2011","venue":"IEEE Transactions on Neural Networks","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Pan et al., 2016] Jeff Z. Pan, Yuan Ren, and Yuting Zhao. Tractable approximate deduction for OWL. Arteficial In- telligence, pages 95-155, 2016.","title":"Tractable approximate deduction for OWL","authors":"Jeff Z Pan, Yuting Yuan Ren, Zhao","year":"2016","venue":"Arteficial Intelligence","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Tan et al., 2017] Ben Tan, Yu Zhang, Sinno Jialin Pan, and Qiang Yang. Distant domain transfer learning. In AAAI, pages 2604-2610, 2017.","title":"Distant domain transfer learning","authors":"Ben Tan, Yu Zhang, Sinno Jialin Pan, Qiang Yang","year":"2017","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Van Haaren et al., 2015] Jan Van Haaren, Andrey Kolobov, and Jesse Davis. TODTLER: Two-order-deep transfer learning. In AAAI, pages 3007-3015, 2015.","title":"TODTLER: Two-order-deep transfer learning","authors":"Van Haaren","year":"2015","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Vicient et al., 2013] Carlos Vicient, David Sánchez, and Antonio Moreno. An automatic approach for ontology- based feature extraction from heterogeneous textual re- sources. Engineering Applications of Artificial Intelli- gence, 26(3):1092-1106, 2013.","title":"An automatic approach for ontologybased feature extraction from heterogeneous textual resources","authors":"Carlos Vicient, David Sánchez, Antonio Moreno","year":"2013","venue":"Engineering Applications of Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Weiss et al., 2016] Karl Weiss, Taghi M Khoshgoftaar, and DingDing Wang. A survey of transfer learning. Journal of Big Data, 3(1):9, 2016.","title":"A survey of transfer learning","authors":"Karl Weiss, Taghi M Khoshgoftaar, Dingding Wang","year":"2016","venue":"Journal of Big Data","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}