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: "explaining scenarios for information personalization"
  Abstract: Personalization customizes information access. The PIPE (‘Personalization is Partial Evaluation’) modeling methodology represents interaction with an information space as a program. The program is then specialized to a user’s known interests or information seeking activity by the technique of partial evaluation. In this paper, we elaborate PIPE by considering requirements analysis in the personalization lifecycle. We investigate the use of scenarios as a means of identifying and analyzing personalization requirements. As our first result, we show how designing a PIPE representation can be cast as a search within a space of PIPE models, organized along a partial order. This allows us to view the design of a personalization system, itself, as specialized interpretation of an information space. We then exploit the underlying equivalence of explanation-based generalization (EBG) and partial evaluation to realize high-level goals and needs identified in scenarios; in particular, we specialize (personalize) an information space based on the explanation of a user scenario in that information space, just as EBG specializes a theory based on the explanation of an example in that theory. In this approach, personalization becomes the transformation of information spaces to support the explanation of usage scenarios. An example application is described. Word counts: Abstract (183 words), Main Text (10200), Bibliography (1092), Appendix (2375).

Connected through hyperedge HE-1 (induced by source paper "the traits of the personable"):
  with members:
    - "a personalized system for conversational recommendations"
    - "staging transformations for multimodal web interaction management"
    - "mixed initiative interaction mixed computation"
    - "the partial evaluation approach to information personalization"

Connected through hyperedge HE-2 (induced by source paper "the partial evaluation approach to information personalization"):
  with members:
    - "semantic similarity in a taxonomy an information based measure and its application to problems of ambiguity in natural language"

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.HC(Human-Computer Interaction)