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: "inferring the strength of social ties a community driven approach"
  Abstract: Online social networks are growing and becoming denser. The social connections of a given person may have very high variability: from close friends and relatives to acquaintances to people who hardly know. Inferring the strength of social ties is an important ingredient for modeling the interaction of users in a network and understanding their behavior. Furthermore, the problem has applications in computational social science, viral marketing, and people recommendation. #R##N#In this paper we study the problem of inferring the strength of social ties in a given network. Our work is motivated by a recent approach [27], which leverages the strong triadic closure (STC) principle, a hypothesis rooted in social psychology [13]. To guide our inference process, in addition to the network structure, we also consider as input a collection of tight communities. Those are sets of vertices that we expect to be connected via strong ties. Such communities appear in different situations, e.g., when being part of a community implies a strong connection to one of the existing members. #R##N#We consider two related problem formalizations that reflect the assumptions of our setting: small number of STC violations and strong-tie connectivity in the input communities. We show that both problem formulations are NP-hard. We also show that one problem formulation is hard to approximate, while for the second we develop an algorithm with approximation guarantee. We validate the proposed method on real-world datasets by comparing with baselines that optimize STC violations and community connectivity separately.

Connected through hyperedge HE-1 (induced by source paper "fixed parameter algorithms for maximum profit facility location under matroid constraints"):
  with members:
    - "on the relation of strong triadic closure and cluster deletion"
    - "parameterized aspects of strong subgraph closure"
    - "deterministic truncation of linear matroids"
    - "approximation algorithms for hard capacitated k facility location problems"
    - "parameterized exact and approximation algorithms for maximum k set cover and related satisfiability problems"
    - "improved approximation algorithms for matroid and knapsack median problems and applications"

Connected through hyperedge HE-2 (induced by source paper "on the relation of strong triadic closure and cluster deletion"):
  with members:
    - "fixed parameter algorithms for maximum profit facility location under matroid constraints"
    - "parameterized aspects of strong subgraph closure"
    - "your rugby mates don t need to know your colleagues triadic closure with edge colors"
    - "maximizing the strong triadic closure in split graphs and proper interval graphs"
    - "kernelization lower bounds by cross composition"

Connected through hyperedge HE-3 (induced by source paper "your rugby mates don t need to know your colleagues triadic closure with edge colors"):
  with members:
    - "tight lower bounds for list edge coloring"
    - "on the relation of strong triadic closure and cluster deletion"
    - "parameterized aspects of strong subgraph closure"

Connected through hyperedge HE-4 (induced by source paper "from acquaintance to best friend forever robust and fine grained inference of social tie strengths"):
  with members:
    - "romantic partnerships and the dispersion of social ties a network analysis of relationship status on facebook"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

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.DS(Data Structures and Algorithms)