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: "solving the large scale next release problem with a backbone based multilevel algorithm"
  Abstract: The Next Release Problem (NRP) aims to optimize customer profits and requirements selection for the software releases. The research on the NRP is restricted by the growing scale of requirements. In this paper, we propose a Backbone based Multilevel Algorithm (BMA) to address the large scale NRP. In contrast to direct solving approaches, BMA employs multilevel reductions to downgrade the problem scale and multilevel refinements to construct the final optimal set of customers. In both reductions and refinements, the backbone is built to fix the common part of the optimal customers. Since it is intractable to extract the backbone in practice, the approximate backbone is employed for the instance reduction while the soft backbone is proposed to augment the backbone application. In the experiments, to cope with the lack of open large requirements databases, we propose a method to extract instances from open bug repositories. Experimental results on 15 classic instances and 24 realistic instances demonstrate that BMA can achieve better solutions on the large scale NRP instances than direct solving approaches. Our work provides a reduction approach for solving large scale problems in search based requirements engineering.

Connected through hyperedge HE-1 (induced by source paper "a fuzzy based optimization method for integrating value dependencies into software requirement selection"):
  with members:
    - "dependency aware release planning for software projects using fuzzy graphs and integer programming"
    - "a study on the prevalence of human values in software engineering publications 2015 2018"
    - "modeling and selection of interdependent software requirements using fuzzy graphs"
    - "a hybrid aco algorithm for the next release problem"
    - "dependency aware software release planning through mining user preferences"
    - "graded causation and defaults"

Connected through hyperedge HE-2 (induced by source paper "dependency aware software requirements selection using fuzzy graphs and integer programming"):
  with members:
    - "a study on the prevalence of human values in software engineering publications 2015 2018"
    - "a hybrid aco algorithm for the next release problem"
    - "from observational studies to causal rule mining"
    - "graded causation and defaults"

Connected through hyperedge HE-3 (induced by source paper "modeling and selection of interdependent software requirements using fuzzy graphs"):
  with members:
    - "dependency aware software release planning through mining user preferences"
    - "graded causation and defaults"
    - "the multiobjective multidimensional knapsack problem a survey and a new approach"

Connected through hyperedge HE-4 (induced by source paper "dependency aware software release planning through mining user preferences"):
  with members:
    - "modeling and selection of interdependent software requirements using fuzzy graphs"
    - "a hybrid aco algorithm for the next release problem"
    - "graded causation and defaults"

Connected through hyperedge HE-5 (induced by source paper "debt prone bugs technical debt in software maintenance"):
  with members:
    - "automatic bug triage using semi supervised text classification"
    - "developer prioritization in bug repositories"

Connected through hyperedge HE-6 (induced by source paper "towards effective bug triage with towards effective bug triage with software data reduction techniques"):
  with members:
    - "automatic bug triage using semi supervised text classification"
    - "towards training set reduction for bug triage"

Connected through hyperedge HE-7 (induced by source paper "developer prioritization in bug repositories"):
  with members:
    - "automatic bug triage using semi supervised text classification"
    - "towards training set reduction for bug triage"

Connected through hyperedge HE-8 (induced by source paper "a more accurate model for finding tutorial segments explaining apis"):
  with members:
    - "developer prioritization in bug repositories"
    - "efficient estimation of word representations in vector space"

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.SE(Software Engineering)