11. ICDM 2011: Vancouver, BC, Canada

Regular Papers

• Rezwan Ahmed, George Karypis:
  Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks. 1-10
  
• Pranay Anchuri, Mohammed J. Zaki, Omer Barkol, Ruth Bergman, Yifat Felder, Shahar Golan, Arik Sityon:
  Infrastructure Pattern Discovery in Configuration Management Databases via Large Sparse Graph Mining. 11-20
  
• Shin Ando, Einoshin Suzuki:
  Role-Behavior Analysis from Trajectory Data by Cross-Domain Learning. 21-30
  
• Hasna Barkia, Haytham Elghazel, Alex Aussem:
  Semi-supervised Feature Importance Evaluation with Ensemble Learning. 31-40
  
• Justin D. Basilico, M. Arthur Munson, Tamara G. Kolda, Kevin R. Dixon, W. Philip Kegelmeyer:
  COMET: A Recipe for Learning and Using Large Ensembles on Massive Data. 41-50
  
• Francesco Bonchi, Aristides Gionis, Antti Ukkonen:
  Overlapping Correlation Clustering. 51-60
  
• Mohammad Taha Bahadori, Yan Liu, Dan Zhang:
  Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning. 61-70
  
• Siddhartha Bhattacharyya:
  Confidence in Predictions from Random Tree Ensembles. 71-80
  
• Petko Bogdanov, Misael Mongiovì, Ambuj K. Singh:
  Mining Heavy Subgraphs in Time-Evolving Networks. 81-90
  
• Xiao Cai, Feiping Nie, Heng Huang, Chris H. Q. Ding:
  Multi-Class L2, 1-Norm Support Vector Machine. 91-100
  
• Nan Cao, David Gotz, Jimeng Sun, Yu-Ru Lin, Huamin Qu:
  SolarMap: Multifaceted Visual Analytics for Topic Exploration. 101-110
  
• Mostafa Haghir Chehreghani:
  Efficiently Mining Unordered Trees. 111-120
  
• Yi-Cheng Chen, Wen-Chih Peng, Suh-Yin Lee:
  CEMiner - An Efficient Algorithm for Mining Closed Patterns from Time Interval-Based Data. 121-130
  
• Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain:
  LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. 131-140
  
• Avinava Dubey, Indrajit Bhattacharya, Mrinal Kanti Das, Tanveer A. Faruquie, Chiranjib Bhattacharyya:
  Learning Dirichlet Processes from Partially Observed Groups. 141-150
  
• Wouter Duivesteijn, Arno J. Knobbe:
  Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery. 151-160
  
• Ahmed K. Farahat, Ali Ghodsi, Mohamed S. Kamel:
  An Efficient Greedy Method for Unsupervised Feature Selection. 161-170
  
• Hongliang Fei, Jun Huan:
  Structured Feature Selection and Task Relationship Inference for Multi-task Learning. 171-180
  
• Yong Ge, Hui Xiong, Chuanren Liu, Zhi-Hua Zhou:
  A Taxi Driving Fraud Detection System. 181-190
  
• Marjan Ghazvininejad, Mostafa Mahdieh, Hamid R. Rabiee, Parisa Khanipour Roshan, Mohammad Hossein Rohban:
  Isograph: Neighbourhood Graph Construction Based on Geodesic Distance for Semi-supervised Learning. 191-200
  
• Christos Giatsidis, Dimitrios M. Thilikos, Michalis Vazirgiannis:
  D-cores: Measuring Collaboration of Directed Graphs Based on Degeneracy. 201-210
  
• Amit Goyal, Wei Lu, Laks V. S. Lakshmanan:
  SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model. 211-220
  
• Siyu Gu, Jun Yan, Lei Ji, Shuicheng Yan, Junshi Huang, Ning Liu, Ying Chen, Zheng Chen:
  Cross Domain Random Walk for Query Intent Pattern Mining from Search Engine Log. 221-230
  
• Stephan Günnemann, Emmanuel Müller, Sebastian Raubach, Thomas Seidl:
  Flexible Fault Tolerant Subspace Clustering for Data with Missing Values. 231-240
  
• T. Ryan Hoens, Nitesh V. Chawla, Robi Polikar:
  Heuristic Updatable Weighted Random Subspaces for Non-stationary Environments. 241-250
  
• Timothy M. Hospedales, Shaogang Gong, Tao Xiang:
  Learning Tags from Unsegmented Videos of Multiple Human Actions. 251-259
  
• Po Hu, Minlie Huang, Peng Xu, Weichang Li, Adam K. Usadi, Xiaoyan Zhu:
  Generating Breakpoint-based Timeline Overview for News Topic Retrospection. 260-269
  
• Hao Huang, Shinjae Yoo, Hong Qin, Dantong Yu:
  A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping. 270-279
  
• Xin Jin, W. Scott Spangler, Ying Chen, Keke Cai, Rui Ma, Li Zhang, Xian Wu, Jiawei Han:
  Patent Maintenance Recommendation with Patent Information Network Model. 280-289
  
• Ye Jin, Sriram Lakshminarasimhan, Neil Shah, Zhenhuan Gong, C. S. Chang, Jackie Chen, Stéphane Ethier, Hemanth Kolla, Seung-Hoe Ku, Scott Klasky, Robert Latham, Robert B. Ross, Karen Schuchardt, Nagiza F. Samatova:
  S-preconditioner for Multi-fold Data Reduction with Guaranteed User-Controlled Accuracy. 290-299
  
• U. Kang, Christos Faloutsos:
  Beyond 'Caveman Communities': Hubs and Spokes for Graph Compression and Mining. 300-309
  
• Anitha Kannan, Partha Pratim Talukdar, Nikhil Rasiwasia, Qifa Ke:
  Improving Product Classification Using Images. 310-319
  
• Tushar Khot, Sriraam Natarajan, Kristian Kersting, Jude W. Shavlik:
  Learning Markov Logic Networks via Functional Gradient Boosting. 320-329
  
• Hyungsul Kim, Sungjin Im, Tarek F. Abdelzaher, Jiawei Han, David Sheridan, Shobha Vasudevan:
  Signature Pattern Covering via Local Greedy Algorithm and Pattern Shrink. 330-339
  
• Younghoon Kim, Kyuseok Shim:
  TWITOBI: A Recommendation System for Twitter Using Probabilistic Modeling. 340-349
  
• Kleanthis-Nikolaos Kontonasios, Jilles Vreeken, Tijl De Bie:
  Maximum Entropy Modelling for Assessing Results on Real-Valued Data. 350-359
  
• Florian Lemmerich, Frank Puppe:
  Local Models for Expectation-Driven Subgroup Discovery. 360-369
  
• Bing Li, Weihua Xiong, Weiming Hu:
  Context-Aware Multi-instance Learning Based on Hierarchical Sparse Representation. 370-377
  
• Cindy Xide Lin, Qiaozhu Mei, Jiawei Han, Yunliang Jiang, Marina Danilevsky:
  The Joint Inference of Topic Diffusion and Evolution in Social Communities. 378-387
  
• Dong Liu, Shuicheng Yan, Yadong Mu, Xian-Sheng Hua, Shih-Fu Chang, Hong-Jiang Zhang:
  Towards Optimal Discriminating Order for Multiclass Classification. 388-397
  
• Haishan Liu, Paea LePendu, Ruoming Jin, Dejing Dou:
  A Hypergraph-based Method for Discovering Semantically Associated Itemsets. 398-406
  
• Qi Liu, Yong Ge, Zhongmou Li, Enhong Chen, Hui Xiong:
  Personalized Travel Package Recommendation. 407-416
  
• Yang Liu, Fei Wu, Yin Zhang, Jian Shao, Yueting Zhuang:
  Tag Clustering and Refinement on Semantic Unity Graph. 417-426
  
• Cheng Long, Raymond Chi-Wing Wong:
  Minimizing Seed Set for Viral Marketing. 427-436
  
• Nigel Medforth, Ke Wang:
  Privacy Risk in Graph Stream Publishing for Social Network Data. 437-446
  
• Pauli Miettinen:
  Boolean Tensor Factorizations. 447-456
  
• Emilie Morvant, Amaury Habrard, Stéphane Ayache:
  Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. 457-466
  
• Masud Moshtaghi, Christopher Leckie, Shanika Karunasekera, James C. Bezdek, Sutharshan Rajasegarar, Marimuthu Palaniswami:
  Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks. 467-476
  
• Quang Nguyen, Hamed Valizadegan, Milos Hauskrecht:
  Learning Classification with Auxiliary Probabilistic Information. 477-486
  
• Tam T. Nguyen, Kuiyu Chang, Siu Cheung Hui:
  Word Cloud Model for Text Categorization. 487-496
  
• Xia Ning, George Karypis:
  SLIM: Sparse Linear Methods for Top-N Recommender Systems. 497-506
  
• Jinoh Oh, Sun Park, Hwanjo Yu, Min Song, Seung-Taek Park:
  Novel Recommendation Based on Personal Popularity Tendency. 507-516
  
• Charles Parker:
  An Analysis of Performance Measures for Binary Classifiers. 517-526
  
• Duc-Son Pham, Budhaditya Saha, Dinh Q. Phung, Svetha Venkatesh:
  Detection of Cross-Channel Anomalies from Multiple Data Channels. 527-536
  
• B. Aditya Prakash, Deepayan Chakrabarti, Michalis Faloutsos, Nicholas Valler, Christos Faloutsos:
  Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks. 537-546
  
• Thanawin Rakthanmanon, Eamonn J. Keogh, Stefano Lonardi, Scott Evans:
  Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data. 547-556
  
• Thanawin Rakthanmanon, Qiang Zhu, Eamonn J. Keogh:
  Mining Historical Documents for Near-Duplicate Figures. 557-566
  
• Teemu Roos, Yuan Zou:
  Analysis of Textual Variation by Latent Tree Structures. 567-576
  
• Chun-Wei Seah, Ivor Wai-Hung Tsang, Yew-Soon Ong:
  Healing Sample Selection Bias by Source Classifier Selection. 577-586
  
• C. Seshadhri, Ali Pinar, Tamara G. Kolda:
  An In-depth Study of Stochastic Kronecker Graphs. 587-596
  
• Fanhua Shang, Yuanyuan Liu, Fei Wang:
  Learning Spectral Embedding for Semi-supervised Clustering. 597-606
  
• Junming Shao, Claudia Plant, Qinli Yang, Christian Böhm:
  Detection of Arbitrarily Oriented Synchronized Clusters in High-Dimensional Data. 607-616
  
• Kan Shao, Yandong Liu, Daniel B. Neill:
  A Generalized Fast Subset Sums Framework for Bayesian Event Detection. 617-625
  
• Chao Shen, Tao Li:
  Learning to Rank for Query-Focused Multi-document Summarization. 626-634
  
• Victor S. Sheng:
  Simple Multiple Noisy Label Utilization Strategies. 635-644
  
• Kilho Shin:
  Partitionable Kernels for Mapping Kernels. 645-654
  
• Arnaud Soulet, Chedy Raïssi, Marc Plantevit, Bruno Crémilleux:
  Mining Dominant Patterns in the Sky. 655-664
  
• Michel Speiser, Gianluca Antonini, Abderrahim Labbi:
  Ranking Web-Based Partial Orders by Significance Using a Markov Reference Model. 665-674
  
• Eirini Spyropoulou, Tijl De Bie:
  Interesting Multi-relational Patterns. 675-684
  
• Luite Stegeman, Ad Feelders:
  On Generating All Optimal Monotone Classifications. 685-694
  
• Souhaib Ben Taieb, Gianluca Bontempi:
  Recursive Multi-step Time Series Forecasting by Perturbing Data. 695-704
  
• Nikolaj Tatti, Fabian Moerchen:
  Finding Robust Itemsets under Subsampling. 705-714
  
• Kai Ming Ting, Takashi Washio, Jonathan R. Wells, Fei Tony Liu:
  Density Estimation Based on Mass. 715-724
  
• Mikalai Tsytsarau, Francesco Bonchi, Aristides Gionis, Themis Palpanas:
  Diverse Dimension Decomposition of an Itemset Space. 725-734
  
• Michal Valko, Branislav Kveton, Hamed Valizadegan, Gregory F. Cooper, Milos Hauskrecht:
  Conditional Anomaly Detection with Soft Harmonic Functions. 735-743
  
• Celine Vens, Fabrizio Costa:
  Random Forest Based Feature Induction. 744-753
  
• Byron C. Wallace, Kevin Small, Carla E. Brodley, Thomas A. Trikalinos:
  Class Imbalance, Redux. 754-763
  
• Hongxing Wang, Junsong Yuan, Yap-Peng Tan:
  Combining Feature Context and Spatial Context for Image Pattern Discovery. 764-773
  
• Hua Wang, Feiping Nie, Heng Huang, Chris H. Q. Ding:
  Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation. 774-783
  
• Liaoruo Wang, Tiancheng Lou, Jie Tang, John E. Hopcroft:
  Detecting Community Kernels in Large Social Networks. 784-793
  
• Xuezhi Wang, Jie Tang, Hong Cheng, Philip S. Yu:
  ADANA: Active Name Disambiguation. 794-803
  
• Xufei Wang, Jiliang Tang, Huan Liu:
  Document Clustering via Matrix Representation. 804-813
  
• Zhenxing Wang, Laiwan Chan:
  Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series. 814-823
  
• Cheng-Wei Wu, Philippe Fournier-Viger, Philip S. Yu, Vincent S. Tseng:
  Efficient Mining of a Concise and Lossless Representation of High Utility Itemsets. 824-833
  
• Rongjing Xiang, Jennifer Neville:
  Understanding Propagation Error and Its Effect on Collective Classification. 834-843
  
• Liang Xiong, Xi Chen, Jeff G. Schneider:
  Direct Robust Matrix Factorizatoin for Anomaly Detection. 844-853
  
• Tengke Xiong, Shengrui Wang, Qingshan Jiang, Joshua Zhexue Huang:
  A New Markov Model for Clustering Categorical Sequences. 854-863
  
• Xiaoran Xu, Zhi-Hong Deng:
  BibClus: A Clustering Algorithm of Bibliographic Networks by Message Passing on Center Linkage Structure. 864-873
  
• Ye Xu, Wei Ping, Andrew T. Campbell:
  Multi-instance Metric Learning. 874-883
  
• Zhao Xu, Kristian Kersting:
  Multi-task Learning with Task Relations. 884-893
  
• Bin Yang, Issei Sato, Hiroshi Nakagawa:
  Secure Clustering in Private Networks. 894-903
  
• Zhijun Yin, Liangliang Cao, Jiawei Han, Chengxiang Zhai, Thomas S. Huang:
  LPTA: A Probabilistic Model for Latent Periodic Topic Analysis. 904-913
  
• Kui Yu, Xindong Wu, Wei Ding, Hao Wang, Hongliang Yao:
  Causal Associative Classification. 914-923
  
• Chao Yuan:
  Multi-task Learning for Bayesian Matrix Factorization. 924-931
  
• Peng Zhang, Byron J. Gao, Xingquan Zhu, Li Guo:
  Enabling Fast Lazy Learning for Data Streams. 932-941
  
• Xianchao Zhang, Quanzeng You:
  Clusterability Analysis and Incremental Sampling for Nyström Extension Based Spectral Clustering. 942-951
  
• Yan-Ming Zhang, Kaizhu Huang, Cheng-Lin Liu:
  Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut. 952-961
  
• Yuchen Zhao, Xiangnan Kong, Philip S. Yu:
  Positive and Unlabeled Learning for Graph Classification. 962-971
  
• Yuhai Zhao, Guoren Wang, Yuan Li, Zhanghui Wang:
  Finding Novel Diagnostic Gene Patterns Based on Interesting Non-redundant Contrast Sequence Rules. 972-981
  
• Li Zheng, Tao Li:
  Semi-supervised Hierarchical Clustering. 982-991
  
• Indre Zliobaite, Faisal Kamiran, Toon Calders:
  Handling Conditional Discrimination. 992-1001
  

Short Papers

• Charu C. Aggarwal, Yao Li, Philip S. Yu:
  On the Hardness of Graph Anonymization. 1002-1007
  
• Hong Cao, Xiaoli Li, Yew-Kwong Woon, See-Kiong Ng:
  SPO: Structure Preserving Oversampling for Imbalanced Time Series Classification. 1008-1013
  
• Miguel Á. Carreira-Perpiñán, Zhengdong Lu:
  Manifold Learning and Missing Data Recovery through Unsupervised Regression. 1014-1019
  
• Danqi Chen, Weizhu Chen, Qiang Yang:
  Characterizing Inverse Time Dependency in Multi-class Learning. 1020-1025
  
• Pan Du, Jiafeng Guo, Xueqi Cheng:
  Supervised Lazy Random Walk for Topic-Focused Multi-document Summarization. 1026-1031
  
• Wentao Fan, Nizar Bouguila, Djemel Ziou:
  Unsupervised Anomaly Intrusion Detection via Localized Bayesian Feature Selection. 1032-1037
  
• Qiong Fang, Jianlin Feng, Wilfred Ng:
  Identifying Differentially Expressed Genes via Weighted Rank Aggregation. 1038-1043
  
• Chuancong Gao, Jianyong Wang, Qingyan Yang:
  Efficient Mining of Closed Sequential Patterns on Stream Sliding Window. 1044-1049
  
• Jing Gao, Wei Fan, Deepak S. Turaga, Srinivasan Parthasarathy, Jiawei Han:
  A Spectral Framework for Detecting Inconsistency across Multi-source Object Relationships. 1050-1055
  
• Zekai Gao, Yangqiu Song, Shixia Liu, Haixun Wang, Hao Wei, Yang Chen, Weiwei Cui:
  Tracking and Connecting Topics via Incremental Hierarchical Dirichlet Processes. 1056-1061
  
• Wei Guan, Arkadas Ozakin, Alexander G. Gray, Jose Borreguero, Shashi Bhushan Pandit, Anna Jagielska, Liliana Wroblewska, Jeffrey Skolnick:
  Learning Protein Folding Energy Functions. 1062-1067
  
• Dan He, Xingquan Zhu, D. Stott Parker:
  How Does Research Evolve? Pattern Mining for Research Meme Cycles. 1068-1073
  
• Jianjun He, Hong Gu, Shaorui Jiang:
  Twin Gaussian Processes for Binary Classification. 1074-1079
  
• Mohammed Hindawi, Kais Allab, Khalid Benabdeslem:
  Constraint Selection-Based Semi-supervised Feature Selection. 1080-1085
  
• Bing Hu, Thanawin Rakthanmanon, Yuan Hao, Scott Evans, Stefano Lonardi, Eamonn J. Keogh:
  Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL. 1086-1091
  
• Zhen Hu, Raj Bhatnagar:
  Discovery of Versatile Temporal Subspace Patterns in 3-D Datasets. 1092-1097
  
• Jens Humrich, Thomas Gärtner, Gemma C. Garriga:
  A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix. 1098-1103
  
• Yexi Jiang, Chang-Shing Perng, Tao Li, Rong N. Chang:
  ASAP: A Self-Adaptive Prediction System for Instant Cloud Resource Demand Provisioning. 1104-1109
  
• Prateek Jindal, Dan Roth:
  Learning from Negative Examples in Set-Expansion. 1110-1115
  
• Edward Casey Kenley, Young-Rae Cho:
  Entropy-Based Graph Clustering: Application to Biological and Social Networks. 1116-1121
  
• Saehoon Kim, Seungjin Choi:
  Semi-supervised Discriminant Hashing. 1122-1127
  
• Petr Krajca, Jan Outrata, Vilém Vychodil:
  Using Frequent Closed Itemsets for Data Dimensionality Reduction. 1128-1133
  
• Taeho Kwon, Zhendong Su:
  Modeling High-Level Behavior Patterns for Precise Similarity Analysis of Software. 1134-1139
  
• Lazhar Labiod, Mohamed Nadif:
  Co-clustering for Binary and Categorical Data with Maximum Modularity. 1140-1145
  
• Chang-Hwan Lee, Fernando Gutierrez, Dejing Dou:
  Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure. 1146-1151
  
• Rong-Hua Li, Jeffrey Xu Yu:
  Scalable Diversified Ranking on Large Graphs. 1152-1157
  
• Bing Li, Weihua Xiong, Weiming Hu:
  Web Horror Image Recognition Based on Context-Aware Multi-instance Learning. 1158-1163
  
• Xiaoxu Li, Junyu Zeng, Xiaojie Wang, Yixin Zhong:
  Mixture of Softmax sLDA. 1164-1169
  
• Qi Mao, Ivor Wai-Hung Tsang:
  Optimizing Performance Measures for Feature Selection. 1170-1175
  
• Mohammad M. Masud, Tahseen Al-Khateeb, Latifur Khan, Charu C. Aggarwal, Jing Gao, Jiawei Han, Bhavani M. Thuraisingham:
  Detecting Recurring and Novel Classes in Concept-Drifting Data Streams. 1176-1181
  
• Xiang Niu, Lusong Li, Xiaobing Xiong, Daniel S. Tkach, He Li, Ke Xu:
  Performances and Characteristics of DIGRank, Ranking in the Incomplete Networks. 1182-1187
  
• Satoshi Oyama, Kohei Hayashi, Hisashi Kashima:
  Cross-Temporal Link Prediction. 1188-1193
  
• Huan-Kai Peng, Pang Wu, Jiang Zhu, Joy Ying Zhang:
  Helix: Unsupervised Grammar Induction for Structured Activity Recognition. 1194-1199
  
• Ning Ruan, Ruoming Jin, Yan Huang:
  Distance Preserving Graph Simplification. 1200-1205
  
• Jana Schmidt, Elisabeth Maria Brändle, Stefan Kramer:
  Clustering with Attribute-Level Constraints. 1206-1211
  
• Mahito Sugiyama, Akihiro Yamamoto:
  A Fast and Flexible Clustering Algorithm Using Binary Discretization. 1212-1217
  
• Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda, Ping Li:
  A New Multi-task Learning Method for Personalized Activity Recognition. 1218-1223
  
• Chih-Hua Tai, Peng-Jui Tseng, Philip S. Yu, Ming-Syan Chen:
  Identities Anonymization in Dynamic Social Networks. 1224-1229
  
• Toshimitsu Takahashi, Ryota Tomioka, Kenji Yamanishi:
  Discovering Emerging Topics in Social Streams via Link Anomaly Detection. 1230-1235
  
• Chayant Tantipathananandh, Tanya Y. Berger-Wolf:
  Finding Communities in Dynamic Social Networks. 1236-1241
  
• Guan Wang, Sihong Xie, Bing Liu, Philip S. Yu:
  Review Graph Based Online Store Review Spammer Detection. 1242-1247
  
• Jiabing Wang, Pei Zhang, Guihua Wen, Jia Wei:
  Classifying Categorical Data by Rule-Based Neighbors. 1248-1253
  
• Miao Zhang, Chris H. Q. Ding, Zhifang Liao:
  Tensor Fold-in Algorithms for Social Tagging Prediction. 1254-1259
  
• Gangqiang Zhao, Junsong Yuan:
  Discovering Thematic Patterns in Videos via Cohesive Sub-graph Mining. 1260-1265
  
• Guoqiang Zhong, Kaizhu Huang, Cheng-Lin Liu:
  Low Rank Metric Learning with Manifold Regularization. 1266-1271
  
• Lei Zhu, Qinbao Song:
  A Study of Laplacian Spectra of Graph for Subgraph Queries. 1272-1277
  
• Yan Zhu, Liping Jing, Jian Yu:
  Text Clustering via Constrained Nonnegative Matrix Factorization. 1278-1283
  

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