human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "combination of multiple bipartite ranking for web content quality evaluation"
  Abstract: AbstractWeb content quality estimation is crucial to various web content process-ing applications. Our previous work applied Bagging + C4.5 to achive thebest results on the ECML/PKDD Discovery Challenge 2010, which is thecomibination of many point-wise rankinig models. In this paper, we combinemultiple pair-wise bipartite ranking learner to solve the multi-partite rankingproblems for the web quality estimation. In encoding stage, we present theternary encoding and the binary coding extending each rank value to L − 1(L is the number of the diﬀerent ranking value). For the decoding, we discussthe combination of multiple ranking results from multiple bipartite rankingmodels with the predeﬁned weighting and the adaptive weighting. The ex-periments on ECML/PKDD 2010 Discovery Challenge datasets show that ∗ Corresponding author. Tel: +86-0371-67756527 Emailaddresses: xbjin@nlpr.ia.ac.cn(Xiao-Bo Jin), gengguanggang@cnnic.cn(Guang-Gang Geng), zdxzzit@hotmail.com(Dexian Zhang) PreprintsubmittedtoKnowledge-Based Systems January11,2014

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IR(Information Retrieval)