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 "how users explore ontologies on the web a study of ncbo s bioportal usage logs"):
  Abstract: Ontologies in the biomedical domain are numerous, highly specialized and very expensive to develop. Thus, a crucial prerequisite for ontology adoption and reuse is effective support for exploring and finding existing ontologies. Towards that goal, the National Center for Biomedical Ontology (NCBO) has developed BioPortal---an online repository designed to support users in exploring and finding more than 500 existing biomedical ontologies. In 2016, BioPortal represents one of the largest portals for exploration of semantic biomedical vocabularies and terminologies, which is used by many researchers and practitioners. While usage of this portal is high, we know very little about how exactly users search and explore ontologies and what kind of usage patterns or user groups exist in the first place. Deeper insights into user behavior on such portals can provide valuable information to devise strategies for a better support of users in exploring and finding existing ontologies, and thereby enable better ontology reuse. To that end, we study and group users according to their browsing behavior on BioPortal using data mining techniques. Additionally, we use the obtained groups to characterize and compare exploration strategies across ontologies. In particular, we were able to identify seven distinct browsing-behavior types, which all make use of different functionality provided by BioPortal. For example, Search Explorers make extensive use of the search functionality while Ontology Tree Explorers mainly rely on the class hierarchy to explore ontologies. Further, we show that specific characteristics of ontologies influence the way users explore and interact with the website. Our results may guide the development of more user-oriented systems for ontology exploration on the Web.

Includes members:
  Member "discovering and characterizing mobility patterns in urban spaces a study of manhattan taxi data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "personalized visited poi assignment to individual raw gps trajectories")
  Member "how to apply markov chains for modeling sequential edit patterns in collaborative ontology engineering projects":
    also connected through other hyperedges:
      (none)
  Member "discovering beaten paths in collaborative ontology engineering projects using markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "how to apply markov chains for modeling sequential edit patterns in collaborative ontology engineering projects")
  Member "hyptrails a bayesian approach for comparing hypotheses about human trails on the web":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "detecting path anomalies in time series data on networks")
  Member "enabling semantic analysis of user browsing patterns in the web of data":
    also connected through other hyperedges:
      (none)
  Member "user modeling combining access logs page content and semantics":
    also connected through other hyperedges:
      (none)
  Member "evaluating variable length markov chain models for analysis of user web navigation sessions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "retrospective higher order markov processes for user trails")

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.SI(Social and Information Networks)