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: "on the spatiotemporal burstiness of terms"
  Abstract: Thousands of documents are made available to the users via the web on a daily basis. One of the most extensively studied problems in the context of such document streams is burst identification. Given a term t, a burst is generally exhibited when an unusually high frequency is observed for t. While spatial and temporal burstiness have been studied individually in the past, our work is the first to simultaneously track and measure spatiotemporal term burstiness. In addition, we use the mined burstiness information toward an efficient document-search engine: given a user's query of terms, our engine returns a ranked list of documents discussing influential events with a strong spatiotemporal impact. We demonstrate the efficiency of our methods with an extensive experimental evaluation on real and synthetic datasets.

Connected through hyperedge HE-1 (induced by source paper "importance of small probability events in big data information measures applications and challenges"):
  with members:
    - "local deep feature alignment for unsupervised dimension reduction"
    - "matching users preference under target revenue constraints in data recommendation systems"
    - "differential message importance measure a new approach to the required sampling number in big data structure characterization"
    - "decorrelation of neutral vector variables theory and applications"
    - "group cooperation with optimal resource allocation in wireless powered communication networks"
    - "amplifying inter message distance on information divergence measures in big data"
    - "focusing on a probability element parameter selection of message importance measure in big data"
    - "linear complexity exponentially consistent tests for universal outlying sequence detection"

Connected through hyperedge HE-2 (induced by source paper "spatio temporal data mining a survey of problems and methods"):
  with members:
    - "classification of passes in football matches using spatiotemporal data"
    - "theory guided data science a new paradigm for scientific discovery from data"
    - "latent space model for road networks to predict time varying traffic"
    - "structural rnn deep learning on spatio temporal graphs"
    - "empirical comparison of algorithms for network community detection"
    - "discovery of convoys in trajectory databases"

Connected through hyperedge HE-3 (induced by source paper "surge continuous detection of bursty regions over a stream of spatial objects"):
  with members:
    - "a scalable algorithm for maximizing range sum in spatial databases"

Connected through hyperedge HE-4 (induced by source paper "multiscale event detection in social media"):
  with members:
    - "a tutorial on spectral clustering"

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.DB(Databases)