{"type":"ScholarlyArticle","title":"C3MM: Clique-Closure based Hyperlink Prediction","authors":[{"name":"Govind Sharma","slug":"govind-sharma","given":"Govind","family":"Sharma","affiliation":"Indian Institute of Science , Bengaluru , India"},{"name":"Prasanna Patil","slug":"prasanna-patil","given":"Prasanna","family":"Patil","affiliation":"Indian Institute of Science , Bengaluru , India"},{"name":"M. Narasimha Murty","slug":"m-narasimha-murty","given":"M. Narasimha","family":"Murty","affiliation":"Indian Institute of Science , Bengaluru , India"}],"abstract":"Usual networks lossily (if not incorrectly) represent higher-order relations, i.e. those between multiple entities instead of a pair. This calls for complex structures such as hypergraphs to be used instead. Akin to the link prediction problem in graphs, we deal with hyperlink (higher-order link) prediction in hypergraphs. With a handful of solutions in the literature that seem to have merely scratched the surface, we provide improvements for the same. Motivated by observations in recent literature, we first formulate a \"clique-closure\" hypothesis (viz., hyperlinks are more likely to be formed from near-cliques rather than from non-cliques), test it on real hypergraphs, and then exploit it for our very problem. In the process, we generalize hyperlink prediction on two fronts: (1) from small-sized to arbitrary-sized hyperlinks, and (2) from a couple of domains to a handful. We perform experiments (both the hypothesis-test as well as the hyperlink prediction) on multiple real datasets, report results, and provide both quantitative and qualitative arguments favoring better performances w.r.t. the state-of-the-art.","doi":"10.24963/ijcai.2020/465","url":"https://ijcai.org/proceedings/2020/465","pdf":"https://ijcai.org/proceedings/2020/0465.pdf","markdown":"https://ijcai.org/proceedings/2020/465.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/465","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Machine Learning Applications","track":"Main track","number":465,"pages":{"first":3364,"last":3370},"keywords":["Machine Learning Applications: Networks","Data Mining: Mining Graphs, Semi Structured Data, Complex Data","Machine Learning: Structured Prediction"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/25422/file_25422.m3u8","length_sec":260,"provider":"hls"}],"references":[{"position":1,"raw":"[Agarwal et al., 2006] Sameer Agarwal, Kristin Branson, and Serge Belongie. Higher order learning with graphs. In Proceedings of the 23rd International Conference on Ma- chine Learning, ICML '06, pages 17-24, New York, NY, USA, 2006. ACM.","title":"Higher order learning with graphs","authors":"Sameer Agarwal, Kristin Branson, Serge Belongie","year":"2006","venue":"Proceedings of the 23rd International Conference on Machine Learning, ICML '06","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Benson et al., 2018] Austin R Benson, Rediet Abebe, Michael T Schaub, Ali Jadbabaie, and Jon Kleinberg. Sim- plicial closure and higher-order link prediction. arXiv preprint arXiv:1802.06916, 2018.","title":"Simplicial closure and higher-order link prediction","authors":"Rediet Austin R Benson, Abebe, T Michael, Ali Schaub, Jon Jadbabaie, Kleinberg","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Berge, 1984] Claude Berge. Hypergraphs: combinatorics of finite sets, volume 45. Elsevier, 1984.","title":"Hypergraphs: combinatorics of finite sets","authors":"Claude Berge, Berge","year":"1984","venue":null,"doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Garcia Gasulla et al., 2015] Dario Garcia Gasulla, Clau- dio Ulises Cortés García, Eduard Ayguadé Parra, and Jesús José Labarta Mancho. Evaluating link prediction on large graphs. In Artificial Intelligence Research and De- velopment: Proceedings of the 18th International Confer- ence of the Catalan Association for Artificial Intelligence, pages 90-99. IOS Press, 2015.","title":"Evaluating link prediction on large graphs","authors":"Dario Garcia Gasulla, Claudio Ulises, Cortés García, Eduard Ayguadé Parra, Jesús José, Labarta Mancho","year":"2015","venue":"Artificial Intelligence Research and Development: Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Ghahramani and Heller, 2006] Zoubin Ghahramani and Katherine A Heller. Bayesian sets. In Y. Weiss, B. Schölkopf, and J. C. Platt, editors, Advances in Neural Information Processing Systems 18, pages 435-442.","title":"Bayesian sets","authors":"Heller Ghahramani, Zoubin Ghahramani, Katherine A Heller","year":"2006","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Katz, 1953] Leo Katz. A new status index derived from sociometric analysis. Psychometrika, 18(1):39-43, Mar 1953.","title":"A new status index derived from sociometric analysis","authors":"Leo Katz, Katz","year":"1953","venue":"Psychometrika","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Kuang et al., 2012] Da Kuang, Chris Ding, and Haesun Park. Symmetric nonnegative matrix factorization for graph clustering. In Proceedings of the 2012 SIAM in- ternational conference on data mining, pages 106-117.","title":"Symmetric nonnegative matrix factorization for graph clustering","authors":"Da Kuang, Chris Ding, Haesun Park","year":null,"venue":"Proceedings of the 2012 SIAM international conference on data mining","doi":null,"url":null,"internal_url":null},{"position":8,"raw":"[Kunegis et al., 2010] Jérôme Kunegis, Ernesto William De Luca, and Sahin Albayrak. The link prediction problem in bipartite networks. CoRR, abs/1006.5367, 2010.","title":"The link prediction problem in bipartite networks","authors":"Jérôme Kunegis, Ernesto William De Luca, Sahin Albayrak","year":"2010","venue":null,"doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Liben-Nowell and Kleinberg, 2003] David Liben-Nowell and Jon Kleinberg. The link prediction problem for social networks. In Proceedings of the Twelfth International Conference on Information and Knowledge Management, CIKM '03, pages 556-559, New York, NY, USA, 2003. ACM.","title":"The link prediction problem for social networks","authors":"Liben-Nowell, Kleinberg, David Liben-Nowell, Jon Kleinberg","year":"2003","venue":"Proceedings of the Twelfth International Conference on Information and Knowledge Management, CIKM '03","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Liben-Nowell and Kleinberg, 2007] David Liben-Nowell and Jon Kleinberg. The link-prediction problem for social networks. Journal of the American society for information science and technology, 58(7):1019-1031, 2007.","title":"The link-prediction problem for social networks","authors":"Liben-Nowell, Kleinberg, David Liben-Nowell, Jon Kleinberg","year":"2007","venue":"Journal of the American society for information science and technology","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Lichtenwalter et al., 2010] Ryan N Lichtenwalter, Jake T Lussier, and Nitesh V Chawla. New perspectives and methods in link prediction. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 243-252. ACM, 2010.","title":"New perspectives and methods in link prediction","authors":"Jake T Ryan N Lichtenwalter, Nitesh V Lussier, Chawla","year":"2010","venue":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Lichtnwalter and Chawla, 2012] Ryan Lichtnwalter and Nitesh V Chawla. Link prediction: fair and effective evaluation. In Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012), pages 376-383. IEEE Computer Society, 2012.","title":"Link prediction: fair and effective evaluation","authors":"Ryan Lichtnwalter, V Nitesh, Chawla","year":"2012","venue":"Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Newman, 2001] Mark EJ Newman. Clustering and prefer- ential attachment in growing networks. Physical review E, 64(2):025102, 2001.","title":"Clustering and preferential attachment in growing networks","authors":"Mark Ej Newman","year":"2001","venue":"Physical review E","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Patil et al., 2020] Prasanna Patil, Govind Sharma, and M Narasimha Murty. Negative sampling for hyperlink prediction in networks. In Pacific-Asia Conference on Knowledge Discovery and Data Mining, pages 607-619. Springer, 2020.","title":"Negative sampling for hyperlink prediction in networks","authors":"Prasanna Patil, Govind Sharma, M Narasimha, Murty","year":"2020","venue":"Pacific-Asia Conference on Knowledge Discovery and Data Mining","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Rendle, 2012] Steffen Rendle. Factorization machines with libfm. ACM Trans. Intell. Syst. Technol., 3(3):57:1-57:22, May 2012.","title":"Factorization machines with libfm","authors":"Steffen Rendle","year":"2012","venue":"ACM Trans. Intell. Syst. Technol","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Xu et al., 2013] Ye Xu, Dan Rockmore, and Adam M Kleinbaum. Hyperlink prediction in hypernetworks using latent social features. In International Conference on Dis- covery Science, pages 324-339. Springer, 2013.","title":"Hyperlink prediction in hypernetworks using latent social features","authors":"Xu","year":"2013","venue":"International Conference on Discovery Science","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Yang et al., 2015] Yang Yang, Ryan N Lichtenwalter, and Nitesh V Chawla. Evaluating link prediction meth- ods. Knowledge and Information Systems, 45(3):751-782, 2015.","title":"Evaluating link prediction methods","authors":"Yang Yang, Ryan N Lichtenwalter, Nitesh V Chawla","year":"2015","venue":"Knowledge and Information Systems","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Yu et al., 2014] Philip S. Yu, Bing Liu, and Ouri Wolfson. Link prediction across heterogeneous social networks: A survey. 2014.","title":"Link prediction across heterogeneous social networks: A survey","authors":"Philip S Yu, Bing Liu, Ouri Wolfson","year":"2014","venue":null,"doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Zhang et al., 2016] Muhan Zhang, Zhicheng Cui, Tolutola Oyetunde, Yinjie Tang, and Yixin Chen. Recovering metabolic networks using a novel hyperlink prediction method. arXiv preprint arXiv:1610.06941, 2016.","title":"Recovering metabolic networks using a novel hyperlink prediction method","authors":"Zhang","year":"2016","venue":null,"doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Zhang et al., 2018] Muhan Zhang, Zhicheng Cui, Shali Jiang, and Yixin Chen. Beyond link prediction: Predicting hyperlinks in adjacency space. AAAI, 2018.","title":"Beyond link prediction: Predicting hyperlinks in adjacency space","authors":"Zhang","year":"2018","venue":null,"doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Zhou et al., 2006] Dengyong Zhou, Jiayuan Huang, and Bernhard Schölkopf. Learning with hypergraphs: Cluster- ing, classification, and embedding. In Proceedings of the 19th International Conference on Neural Information Pro- cessing Systems, NIPS'06, pages 1601-1608, Cambridge, MA, USA, 2006. MIT Press.","title":"Learning with hypergraphs: Clustering, classification, and embedding","authors":"Zhou","year":"2006","venue":"Proceedings of the 19th International Conference on Neural Information Processing Systems, NIPS'06","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}