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: "does a daily deal promotion signal a distressed business an empirical investigation of small business survival"
  Abstract: In the last four years, daily deals have emerged from nowhere to become a multi-billion dollar industry world-wide. Daily deal sites such as Groupon and Livingsocial off er products and services at deep discounts to consumers via email and social networks. As the industry matures, there are many questions regarding the impact of daily deals on the market-place Important questions in this regard concern the reasons why businesses decide to o er daily deals and their longer-term impact on businesses. In the present paper, we investigate whether the unobserved factors that make marketers run daily deals are correlated with the unobserved factors that influence the business, In particular, we employ the framework of seemingly unrelated regression to model the correlation between the errors in predicting whether a business uses a daily deal and the errors in predicting the business' survival. Our analysis consists of the survival of 985 small businesses that off ered daily deals between January and July 2011 in the city of Chicago. Our results indicate that there is a statistically signifi cant correlation between the unobserved factors that influence the business' decision to o ffer a daily deal and the unobserved factors that impact its survival. Furthermore, our results indicate that the correlation coefficient is signifi cant in certain business categories (e.g. restaurants).

Connected through hyperedge HE-1 (induced by source paper "role discovery in networks"):
  with members:
    - "a boosting approach to learning graph representations"
    - "an information theoretic analysis of hard and soft assignment methods for clustering"
    - "role dynamics fast mining of large dynamic networks"
    - "network sampling from static to streaming graphs"
    - "correlated non parametric latent feature models"
    - "on learning discrete graphical models using greedy methods"
    - "the internet as level topology three data sources and one definitive metric"

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.CE(Computational Engineering, Finance, and Science)