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: "a historical perspective on developing foundations iinfo tm information systems iconsult tm and ientertain tm apps using idescribers tm information integration for iorgs tm information systems"
  Abstract: Technology now at hand can integrate all kinds of digital information for individuals, groups, and organizations so their information usefully links together. iInfo(TM) information integration works by making connections including examples like the following: #R##N#- A statistical connection between "being in a traffic jam" and "driving in downtown Trenton between 5PM and 6PM on a weekday." #R##N#- A terminological connection between "MSR" and "Microsoft Research." #R##N#- A causal connection between "joining a group" and "being a member of the group." #R##N#- A syntactic connection between "a pin dropped" and "a dropped pin." #R##N#- A biological connection between "a dolphin" and "a mammal". #R##N#- A demographic connection between "undocumented residents of California" and "7% of the population of California." #R##N#- A geographical connection between "Leeds" and "England." #R##N#- A temporal connection between "turning on a computer" and "joining an on-line discussion." #R##N#By making these connections, iInfo offers tremendous value for individuals, families, groups, and organizations in making more effective use of information technology. #R##N#In practice, integrated information is invariably pervasively inconsistent. Therefore iInfo must be able to make connections even in the face of inconsistency. The business of iInfo is not to make difficult decisions like deciding the ultimate truth or probability of propositions. Instead it provides means for processing information and carefully recording its provenance including arguments (including arguments about arguments) for and against propositions that is used by iConsult(TM) and iEntertain(TM) apps in iOrgs(TM) Information Systems. #R##N#A historical perspective on the above questions is highly pertinent to the current quest to develop foundations for privacy-friendly client-cloud computing.

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.DC(Distributed, Parallel, and Cluster Computing)