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: "towards a unifying view of qos enhanced web service description and discovery approaches"
  Abstract: The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why a lot of the research efforts point to discover semantic means for describing web services taking into account not only functional characteristics of services, but also the quality of service (QoS) properties such as availability, reliability, response time, trust, etc. This motivated us to research current approaches presenting complete solutions for QoS enabled web service description, publication and discovery. In this paper we present comparative analysis of these approaches according to their common principals. Based on such analysis we extract the essential aspects from them and propose a pattern for the development of QoS-aware service-oriented architectures. The number of web services increased vastly in the last years. Various providers offer web services with the same functionality, so for web service consumers it is getting more complicated to select the web service, which best fits their requirements. That is why many research efforts point to discovering semantic approaches for describing web services including both functional and non-functional properties. This will give consumers the opportunity to find web services according to their QoS requirements such as availability, reliability, response time, trust, etc. Most of the current solutions are based on Web Service Definition Language (WSDL) and Universal Description and Discovery Interface (UDDI) registry. WSDL documents provide functional description of web services without semantic specifications concerning QoS. UDDI registry provides catalog-based searching without control over the quality of registered services. UDDI APIs allow publishing and discovering data for a particular service, but do not provide an opportunity for a quality-based retrieval. The problem becomes more complicated when the discovery process returns several web services with the same functionality. Such mentioned disadvantages motivated us to research principal current approaches for QoS-aware web service description and discovery in order to find better solutions giving more accurate and productive service retrieval. These approaches have common principals that can be summarized as follows:

Connected through hyperedge HE-1 (induced by source paper "web services discovery and recommendation based on information extraction and symbolic reputation"):
  with members:
    - "the google similarity distance"

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.SE(Software Engineering)