{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T04:11:10Z","timestamp":1751602270535,"version":"3.41.0"},"publisher-location":"New York, New York, USA","reference-count":49,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1145\/3178876.3186064","type":"proceedings-article","created":{"date-parts":[[2018,4,13]],"date-time":"2018-04-13T15:53:48Z","timestamp":1523634828000},"page":"1523-1532","source":"Crossref","is-referenced-by-count":31,"title":["Learning on Partial-Order Hypergraphs"],"prefix":"10.1145","author":[{"given":"Fuli","family":"Feng","sequence":"first","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}]},{"given":"Xiangnan","family":"He","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}]},{"given":"Yiqun","family":"Liu","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, China"}]},{"given":"Liqiang","family":"Nie","sequence":"additional","affiliation":[{"name":"Shandong University, Qingdao, China"}]},{"given":"Tat-Seng","family":"Chua","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}]}],"member":"320","reference":[{"key":"key-10.1145\/3178876.3186064-1","doi-asserted-by":"crossref","unstructured":"Charu C Aggarwal and Chandan K Reddy . 2013. Data clustering: algorithms and applications. CRC press.","DOI":"10.1201\/b15410"},{"key":"key-10.1145\/3178876.3186064-2","unstructured":"Stephen H. Bach, Matthias Broecheler, Bert Huang, and Lise Getoor . 2017. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. Journal of Machine Learning Research (2017)."},{"key":"key-10.1145\/3178876.3186064-3","doi-asserted-by":"crossref","unstructured":"Abdelghani Bellaachia and Mohammed Al-Dhelaan . 2014. Multi-document hyperedge-based ranking for text summarization CIKM. 1919--1922.","DOI":"10.1145\/2661829.2662036"},{"key":"key-10.1145\/3178876.3186064-4","doi-asserted-by":"crossref","unstructured":"Chen Chen, Cewu Lu, Qixing Huang, Qiang Yang, Dimitrios Gunopulos, and Leonidas Guibas . 2016 a. City-Scale Map Creation and Updating Using GPS Collections SIGKDD. 1465--1474.","DOI":"10.1145\/2939672.2939833"},{"key":"key-10.1145\/3178876.3186064-5","doi-asserted-by":"crossref","unstructured":"Jingyuan Chen, Xuemeng Song, Liqiang Nie, Xiang Wang, Hanwang Zhang, and Tat-Seng Chua . 2016 b. Micro tells macro: predicting the popularity of micro-videos via a transductive model MM. 898--907.","DOI":"10.1145\/2964284.2964314"},{"key":"key-10.1145\/3178876.3186064-6","doi-asserted-by":"crossref","unstructured":"Zhiyong Cheng and Jialie Shen . 2016. On effective location-aware music recommendation. Transactions on Information System Vol. 34, 2 (2016), 13.","DOI":"10.1145\/2846092"},{"key":"key-10.1145\/3178876.3186064-7","doi-asserted-by":"crossref","unstructured":"Paolo Cremonesi, Yehuda Koren, and Roberto Turrin . 2010. Performance of Recommender Algorithms on Top-n Recommendation Tasks RecSys. 39--46.","DOI":"10.1145\/1864708.1864721"},{"key":"key-10.1145\/3178876.3186064-8","doi-asserted-by":"crossref","unstructured":"Inderjit S Dhillon, Yuqiang Guan, and Brian Kulis . 2004. Kernel k-means: spectral clustering and normalized cuts SIGKDD. 551--556.","DOI":"10.1145\/1014052.1014118"},{"key":"key-10.1145\/3178876.3186064-9","doi-asserted-by":"crossref","unstructured":"Fuli Feng, Liqiang Nie, Xiang Wang, Richang Hong, and Tat-Seng Chua . 2017 a. Computational social indicators: a case study of chinese university ranking SIGIR. 455--464.","DOI":"10.1145\/3077136.3080773"},{"key":"key-10.1145\/3178876.3186064-10","unstructured":"Xiaodong Feng, Sen Wu, and Wenjun Zhou . 2017 b. Multi-Hypergraph Consistent Sparse Coding. Transactions on Intelligent Systems and Technology, Vol. 8, 6 (2017), 75."},{"key":"key-10.1145\/3178876.3186064-11","doi-asserted-by":"crossref","unstructured":"David F Gleich and Michael W Mahoney . 2015. Using local spectral methods to robustify graph-based learning algorithms SIGKDD. 359--368.","DOI":"10.1145\/2783258.2783376"},{"key":"key-10.1145\/3178876.3186064-12","unstructured":"Ian Goodfellow, Yoshua Bengio, and Aaron Courville . 2016. Deep learning. MIT press."},{"key":"key-10.1145\/3178876.3186064-13","doi-asserted-by":"crossref","unstructured":"Richard HR Hahnloser, Rahul Sarpeshkar, Misha A Mahowald, Rodney J Douglas, and H Sebastian Seung . 2000. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit. Nature, Vol. 405, 6789 (2000), 947.","DOI":"10.1038\/35016072"},{"key":"key-10.1145\/3178876.3186064-14","doi-asserted-by":"crossref","unstructured":"Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun . 2016. Deep residual learning for image recognition. In CVPR. 770--778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"key-10.1145\/3178876.3186064-15","doi-asserted-by":"crossref","unstructured":"Xiangnan He and Tat-Seng Chua . 2017. Neural Factorization Machines for Sparse Predictive Analytics SIGIR. 355--364.","DOI":"10.1145\/3077136.3080777"},{"key":"key-10.1145\/3178876.3186064-16","doi-asserted-by":"crossref","unstructured":"Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, and Kazunari Sugiyama . 2014. Predicting the Popularity of Web 2.0 Items Based on User Comments SIGIR. 233--242.","DOI":"10.1145\/2600428.2609558"},{"key":"key-10.1145\/3178876.3186064-17","doi-asserted-by":"crossref","unstructured":"Xiangnan He, Ming Gao, Min-Yen Kan, and Dingxian Wang . 2017. Birank: Towards ranking on bipartite graphs. Transactions on Knowledge and Data Engineering, Vol. 29, 1 (2017), 57--71.","DOI":"10.1109\/TKDE.2016.2611584"},{"key":"key-10.1145\/3178876.3186064-18","doi-asserted-by":"crossref","unstructured":"Manel Hmimida and Rushed Kanawati . 2016. A Graph-Coarsening Approach for Tag Recommendation WWW. 43--44.","DOI":"10.1145\/2872518.2889415"},{"key":"key-10.1145\/3178876.3186064-19","doi-asserted-by":"crossref","unstructured":"Sheng Huang, Mohamed Elhoseiny, Ahmed Elgammal, and Dan Yang . 2015. Learning hypergraph-regularized attribute predictors CVPR. 409--417.","DOI":"10.1109\/CVPR.2015.7298638"},{"key":"key-10.1145\/3178876.3186064-20","doi-asserted-by":"crossref","unstructured":"Jyun-Yu Jiang, Pu-Jen Cheng, and Wei Wang . 2017. Open Source Repository Recommendation in Social Coding SIGIR. 1173--1176.","DOI":"10.1145\/3077136.3080753"},{"key":"key-10.1145\/3178876.3186064-21","unstructured":"Thomas N Kipf and Max Welling . 2017. Semi-supervised classification with graph convolutional networks. ICLR (2017)."},{"key":"key-10.1145\/3178876.3186064-22","doi-asserted-by":"crossref","unstructured":"Lei Li and Tao Li . 2013. News recommendation via hypergraph learning: encapsulation of user behavior and news content WSDM. 305--314.","DOI":"10.1145\/2433396.2433436"},{"key":"key-10.1145\/3178876.3186064-23","doi-asserted-by":"crossref","unstructured":"David C Liu, Stephanie Rogers, Raymond Shiau, Dmitry Kislyuk, Kevin C Ma, Zhigang Zhong, Jenny Liu, and Yushi Jing . 2017 a. Related pins at pinterest: The evolution of a real-world recommender system WWW. 583--592.","DOI":"10.1145\/3041021.3054202"},{"key":"key-10.1145\/3178876.3186064-24","doi-asserted-by":"crossref","unstructured":"Qingshan Liu, Yubao Sun, Cantian Wang, Tongliang Liu, and Dacheng Tao . 2017 b. Elastic net hypergraph learning for image clustering and semi-supervised classification. Transactions on Image Processing Vol. 26, 1 (2017), 452--463.","DOI":"10.1109\/TIP.2016.2621671"},{"key":"key-10.1145\/3178876.3186064-25","doi-asserted-by":"crossref","unstructured":"Tie-Yan Liu . 2011. Learning to rank for information retrieval. Springer Science &#38; Business Media.","DOI":"10.1007\/978-3-642-14267-3"},{"key":"key-10.1145\/3178876.3186064-26","doi-asserted-by":"crossref","unstructured":"Tao Mei, Yong Rui, Shipeng Li, and Qi Tian . 2014. Multimedia search reranking: A literature survey. Comput. Surveys Vol. 46, 3 (2014), 38.","DOI":"10.1145\/2536798"},{"key":"key-10.1145\/3178876.3186064-27","doi-asserted-by":"crossref","unstructured":"Michael Mitzenmacher, Jakub Pachocki, Richard Peng, Charalampos Tsourakakis, and Shen Chen Xu . 2015. Scalable large near-clique detection in large-scale networks via sampling SIGKDD. 815--824.","DOI":"10.1145\/2783258.2783385"},{"key":"key-10.1145\/3178876.3186064-28","unstructured":"RB Nelsen . 2001. Kendall tau metric. Encyclopaedia of Mathematics Vol. 3 (2001), 226--227."},{"key":"key-10.1145\/3178876.3186064-29","doi-asserted-by":"crossref","unstructured":"Liqiang Nie, Meng Wang, Zheng-Jun Zha, and Tat-Seng Chua . 2012 a. Oracle in image search: a content-based approach to performance prediction. Transactions on Information System Vol. 30, 2 (2012), 13.","DOI":"10.1145\/2180868.2180875"},{"key":"key-10.1145\/3178876.3186064-30","doi-asserted-by":"crossref","unstructured":"Liqiang Nie, Shuicheng Yan, Meng Wang, Richang Hong, and Tat-Seng Chua . 2012 b. Harvesting visual concepts for image search with complex queries MM. 59--68.","DOI":"10.1145\/2393347.2393363"},{"key":"key-10.1145\/3178876.3186064-31","doi-asserted-by":"crossref","unstructured":"Adi Omari, David Carmel, Oleg Rokhlenko, and Idan Szpektor . 2016. Novelty Based Ranking of Human Answers for Community Questions SIGIR. 215--224.","DOI":"10.1145\/2911451.2911506"},{"key":"key-10.1145\/3178876.3186064-32","doi-asserted-by":"crossref","unstructured":"Xiang Ren, Ahmed El-Kishky, Chi Wang, Fangbo Tao, Clare R. Voss, and Jiawei Han . 2015. ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering SIGKDD. 995--1004.","DOI":"10.1145\/2783258.2783362"},{"key":"key-10.1145\/3178876.3186064-33","doi-asserted-by":"crossref","unstructured":"Marian-Andrei Rizoiu, Lexing Xie, Scott Sanner, Manuel Cebrian, Honglin Yu, and Pascal Van Hentenryck . 2017. Expecting to Be HIP: Hawkes Intensity Processes for Social Media Popularity WWW. 735--744.","DOI":"10.1145\/3038912.3052650"},{"key":"key-10.1145\/3178876.3186064-34","doi-asserted-by":"crossref","unstructured":"Charles Spearman . 1987. The proof and measurement of association between two things. The American journal of psychology Vol. 100 (1987), 441--471.","DOI":"10.2307\/1422689"},{"key":"key-10.1145\/3178876.3186064-35","doi-asserted-by":"crossref","unstructured":"Kenneth Tran, Saghar Hosseini, Lin Xiao, Thomas Finley, and Mikhail Bilenko . 2015. Scaling up stochastic dual coordinate ascent. In SIGKDD. 1185--1194.","DOI":"10.1145\/2783258.2783412"},{"key":"key-10.1145\/3178876.3186064-36","doi-asserted-by":"crossref","unstructured":"Charalampos E Tsourakakis, Jakub Pachocki, and Michael Mitzenmacher . 2017. Scalable motif-aware graph clustering. In WWW. 1451--1460.","DOI":"10.1145\/3038912.3052653"},{"key":"key-10.1145\/3178876.3186064-37","doi-asserted-by":"crossref","unstructured":"Meng Wang, Weijie Fu, Shijie Hao, Dacheng Tao, and Xindong Wu . 2016 a. Scalable semi-supervised learning by efficient anchor graph regularization. Transactions on Knowledge and Data Engineering, Vol. 28, 7 (2016), 1864--1877.","DOI":"10.1109\/TKDE.2016.2535367"},{"key":"key-10.1145\/3178876.3186064-38","unstructured":"Meng Wang, Xueliang Liu, and Xindong Wu . 2015. Visual Classification by $ell _1$ -Hypergraph Modeling. TKDE, Vol. 27, 9 (2015), 2564--2574."},{"key":"key-10.1145\/3178876.3186064-39","doi-asserted-by":"crossref","unstructured":"Xiang Wang, Xiangnan He, Liqiang Nie, and Tat-Seng Chua . 2017. Item silk road: Recommending items from information domains to social users SIGIR. 185--194.","DOI":"10.1145\/3077136.3080771"},{"key":"key-10.1145\/3178876.3186064-40","doi-asserted-by":"crossref","unstructured":"Xiaoqian Wang, Feiping Nie, and Heng Huang . 2016 b. Structured Doubly Stochastic Matrix for Graph Based Clustering: Structured Doubly Stochastic Matrix SIGKDD. 1245--1254.","DOI":"10.1145\/2939672.2939805"},{"key":"key-10.1145\/3178876.3186064-41","unstructured":"Cort J Willmott and Kenji Matsuura . 2005. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate research, Vol. 30, 1 (2005), 79--82."},{"key":"key-10.1145\/3178876.3186064-42","doi-asserted-by":"crossref","unstructured":"Yuichi Yoshida . 2014. Almost linear-time algorithms for adaptive betweenness centrality using hypergraph sketches. In SIGKDD. 1416--1425.","DOI":"10.1145\/2623330.2623626"},{"key":"key-10.1145\/3178876.3186064-43","doi-asserted-by":"crossref","unstructured":"Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, SVN Vishwanathan, and Inderjit S Dhillon . 2015. A scalable asynchronous distributed algorithm for topic modeling WWW. 1340--1350.","DOI":"10.1145\/2736277.2741682"},{"key":"key-10.1145\/3178876.3186064-44","unstructured":"Rose Yu, Huida Qiu, Zhen Wen, ChingYung Lin, and Yan Liu . 2016. A survey on social media anomaly detection. SIGKDD, Vol. 18, 1 (2016), 1--14."},{"key":"key-10.1145\/3178876.3186064-45","doi-asserted-by":"crossref","unstructured":"Dongxiang Zhang, Long Guo, Xiangnan He, Jie Shao, Sai Wu, and Heng Tao Shen . 2018. A Graph-Theoretic Fusion Framework for Unsupervised Entity Resolution ICDE.","DOI":"10.1109\/ICDE.2018.00070"},{"key":"key-10.1145\/3178876.3186064-46","doi-asserted-by":"crossref","unstructured":"Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan, and Tat-Seng Chua . 2016. Discrete collaborative filtering. In SIGIR. 325--334.","DOI":"10.1145\/2911451.2911502"},{"key":"key-10.1145\/3178876.3186064-47","unstructured":"Denny Zhou, Olivier Bousquet, Thomas N Lal, Jason Weston, and Bernhard Sch&#246;lkopf . 2004 a. Learning with local and global consistency. In NIPS. 321--328."},{"key":"key-10.1145\/3178876.3186064-48","unstructured":"Denny Zhou, Jiayuan Huang, and Bernhard Sch&#246;lkopf . 2007. Learning with hypergraphs: Clustering, classification, and embedding NIPS. 1601--1608."},{"key":"key-10.1145\/3178876.3186064-49","unstructured":"Denny Zhou, Jason Weston, Arthur Gretton, Olivier Bousquet, and Bernhard Sch&#246;lkopf . 2004 b. Ranking on data manifolds. In NIPS. 169--176."}],"event":{"number":"2018","sponsor":["SIGWEB, ACM Special Interest Group on Hypertext, Hypermedia, and Web","IW3C2, International World Wide Web Conference Committee"],"acronym":"WWW '18","name":"the 2018 World Wide Web Conference","start":{"date-parts":[[2018,4,23]]},"location":"Lyon, France","end":{"date-parts":[[2018,4,27]]}},"container-title":["Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3178876.3186064","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=3186064&ftid=1957401&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T17:27:37Z","timestamp":1751563657000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=3178876.3186064"}},"subtitle":[],"proceedings-subject":"World Wide Web","short-title":[],"issued":{"date-parts":[[2018]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1145\/3178876.3186064","relation":{},"subject":[],"published":{"date-parts":[[2018]]}}}