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: "random surfers on a web encyclopedia"
  Abstract: The random surfer model is a frequently used model for simulating user navigation behavior on the Web. Various algorithms, such as PageRank, are based on the assumption that the model represents a good approximation of users browsing a website. However, the way users browse the Web has been drastically altered over the last decade due to the rise of search engines. Hence, new adaptations for the established random surfer model might be required, which better capture and simulate this change in navigation behavior. In this article we compare the classical uniform random surfer to empirical navigation and page access data in a Web Encyclopedia. Our high level contributions are (i) a comparison of stationary distributions of different types of the random surfer to quantify the similarities and differences between those models as well as (ii) new insights into the impact of search engines on traditional user navigation. Our results suggest that the behavior of the random surfer is almost similar to those of users---as long as users do not use search engines. We also find that classical website navigation structures, such as navigation hierarchies or breadcrumbs, only exercise limited influence on user navigation anymore. Rather, a new kind of navigational tools (e.g., recommendation systems) might be needed to better reflect the changes in browsing behavior of existing users.

Connected through hyperedge HE-1 (induced by source paper "hoprank how semantic structure influences teleportation in pagerank a case study on bioportal"):
  with members:
    - "how users explore ontologies on the web a study of ncbo s bioportal usage logs"
    - "detecting memory and structure in human navigation patterns using markov chain models of varying order"

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.SI(Social and Information Networks)