human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "web graph compression with fast access"):
  Abstract: In recent years studying the content of the World Wide Web became a very important yet rather difficult task. There is a need for a compression technique that would allow a web graph representation to be put into the memory while maintaining random access time competitive to the time needed to access uncompressed web graph on a hard drive. #R##N#There are already available techniques that accomplish this task, but there is still room for improvements and this thesis attempts to prove it. It includes a comparison of two methods contained in state of art of this field (BV and k2partitioned) to two already implemented algorithms (rewritten, however, in C++ programming language to maximize speed and resource management efficiency), which are LM and 2D, and introduces the new variant of the latter one, called 2D stripes. #R##N#This thesis serves as well as a proof of concept. The final considerations show positive and negative aspects of all presented methods, expose the feasibility of the new variant as well as indicate future direction for development.

Includes members:
  Member "layered label propagation a multiresolution coordinate free ordering for compressing social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "2ps high quality edge partitioning with two phase streaming")
  Member "tight and simple web graph compression":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "survey and taxonomy of lossless graph compression and space efficient graph representations")

Question: Please tell me which class the source paper 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.DS(Data Structures and Algorithms)