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: "web services dependency networks analysis"
  Abstract: Along with a continuously growing number of publicly available Web services (WS), we are witnessing a rapid development in semantic-related web technologies, which lead to the apparition of semantically described WS. In this work, we perform a comparative analysis of the syntactic and semantic approaches used to describe WS, from a complex network perspective. First, we extract syntactic and semantic WS dependency networks from a collection of publicly available WS descriptions. Then, we take advantage of tools from the complex network field to analyze them and determine their topological properties. We show WS dependency networks exhibit some of the typical characteristics observed in real-world networks, such as small world and scale free properties, as well as community structure. By comparing syntactic and semantic networks through their topological properties, we show the introduction of semantics in WS description allows modeling more accurately the dependencies between parameters, which in turn could lead to improved composition mining methods.

Connected through hyperedge HE-1 (induced by source paper "analyzing web services networks a ws next application"):
  with members:
    - "topological properties of web services similarity networks"
    - "mataws a multimodal approach for automatic ws semantic annotation"
    - "on flexible web services composition networks"
    - "benefits of semantics on web service composition from a complex network perspective"

Connected through hyperedge HE-2 (induced by source paper "on topological structure of web services networks for composition"):
  with members:
    - "community structure in interaction web service networks"
    - "qualitative comparison of community detection algorithms"
    - "benefits of semantics on web service composition from a complex network perspective"

Connected through hyperedge HE-3 (induced by source paper "a comparative study of web services composition networks"):
  with members:
    - "on flexible web services composition networks"
    - "benefits of semantics on web service composition from a complex network perspective"

Connected through hyperedge HE-4 (induced by source paper "topological properties of web services similarity networks"):
  with members:
    - "benefits of semantics on web service composition from a complex network perspective"

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.IR(Information Retrieval)