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 "geocuts geographic clustering using travel statistics"):
  Abstract: Web-based services often run experiments to improve their products. To carry out an effective experiment and evaluate the results appropriately, there must be a control group and at least one treatment group. Ideally all of these groups are disjoint, so that each user is given a specific treatment. Using geographical locations as units of experimentation is desirable because this does not require tracking individual users or browser cookies. With the popularity of mobile devices, a user may issue queries from multiple geographical locations. Hence, to be used as units of experimentation, geographical partitions should be chosen in a way that reduces transit between regions. #R##N#The strategy of clustering users by region is common in advertising. Designated marketing areas (DMAs) are specifically designed for this purpose. However, DMAs are restricted to the US and their granularity is inflexible (there are around two hundred in total). Moreover, they are built based on population density - one DMA per metropolitan area - rather than mobile movement patterns. #R##N#In this paper, we present GeoCUTS, an algorithm that forms geographical clusters to minimize movement between clusters while preserving rough balance in cluster size. We use a random sample of anonymized mobile user traffic to form a graph representing user movements, then construct a geographically coherent clustering of the graph. We propose a statistical framework to measure the effectiveness of clusterings and perform empirical evaluations showing that the performance of GeoCUTS is comparable to hand-crafted DMAs with respect to both novel and existing metrics. GeoCUTS offers a general and flexible framework for conducting geo-based experiments in any part of the world.

Includes members:
  Member "distributed balanced partitioning via linear embedding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi dimensional balanced graph partitioning via projected gradient descent")
  Member "graph cluster randomization network exposure to multiple universes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "inferring individual level causal models from graph based relational time series")
  Member "finding connected components on map reduce in logarithmic rounds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "equivalence classes and conditional hardness in massively parallel computations")

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.SI(Social and Information Networks)