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 "topological properties of web services similarity networks"):
  Abstract: The number of publicly available Web services (WS) is continuously growing. To perform efficient WS discovery, it is desirable to organize the WS space. Works in this direction propose to group WS according to certain shared properties. Such groups commonly called communities are based either on similarity or on interaction between WS. In this paper we focus on the former, and propose a new network-based approach to extract communities from a WS collection. This process is three-stepped: first we define several similarity functions able to compare WS operations, second we use them to build so-called similarity networks, and third we identify communities under the form of specific structures in these networks. We apply our method on a collection of real-world WS and comment the resulting communities. Finally, we additionally provide an analysis and an interpretation of our similarity networks with a complex networks perspective.

Includes members:
  Member "web services dependency networks analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analyzing web services networks a ws next application")
  Member "benefits of semantics on web service composition from a complex network perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing web services networks a ws next application")

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.IR(Information Retrieval)