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 "measuring software quality in use state of the art and research challenges"):
  Abstract: Software quality in use comprises quality from the user's perspective. It has gained its importance in e-government applications, mobile-based applications, embedded systems, and even business process development. User's decisions on software acquisitions are often ad hoc or based on preference due to difficulty in quantitatively measuring software quality in use. But, why is quality-in-use measurement difficult? Although there are many software quality models, to the authors' knowledge no works survey the challenges related to software quality-in-use measurement. This article has two main contributions: 1) it identifies and explains major issues and challenges in measuring software quality in use in the context of the ISO SQuaRE series and related software quality models and highlights open research areas; and 2) it sheds light on a research direction that can be used to predict software quality in use. In short, the quality-in-use measurement issues are related to the complexity of the current standard models and the limitations and incompleteness of the customized software quality models. A sentiment analysis of software reviews is proposed to deal with these issues.

Includes members:
  Member "comprehensive landscapes for software related quality models":
    also connected through other hyperedges:
      (none)
  Member "an activity based quality model for maintainability":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "evaluating maintainability prejudices with a large scale study of open source projects")
  Member "thumbs up or thumbs down semantic orientation applied to unsupervised classification of reviews":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "utilizing neural networks and linguistic metadata for early detection of depression indications in text sequences")

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.SE(Software Engineering)