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: "fairness preserving text summarzation"
  Abstract: Given the rapid growth in online information content, text summarization algorithms are progressively used to provide users a succinct idea about the total information content. Historically, summarization algorithms are evaluated only based on how close their outputs are to human-written gold standard summaries. In this work, we propose to evaluate summarization algorithms from an unprecedented viewpoint. Considering that an extractive summarization algorithm selects a subset of the textual units (tweets / sentences) in the input data for inclusion in the summary, we examine the fairness of this selection. Importantly, if the data to be summarized is generated by different socially salient groups, or different political groups, or different news media sources, then we check whether the generated summaries fairly represent these different groups or sources. In real-world datasets we observe that existing summarization algorithms often represent the groups very differently compared to their distributions in the input data. To alleviate such adverse impacts, we propose a novel fair summarization algorithm 'FairSumm' capable of generating high-quality fair summaries.

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)