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: "nosql database new era of databases for big data analytics classification characteristics and comparison"
  Abstract: Digital world is growing very fast and become more complex in the volume (terabyte to petabyte), variety (structured and un-structured and hybrid), velocity (high speed in growth) in nature. This refers to as ‘Big Data’ that is a global phenomenon. This is typically considered to be a data collection that has grown so large it can’t be effectively managed or exploited using conventional data management tools: e.g., classic relational database management systems (RDBMS) or conventional search engines. To handle this problem, traditional RDBMS are complemented by specifically designed a rich set of alternative DBMS; such as - NoSQL, NewSQL and Search-based systems. This paper motivation is to provide - classification, characteristics and evaluation of NoSQL databases in Big Data Analytics. This report is intended to help users, especially to the organizations to obtain an independent understanding of the strengths and weaknesses of various NoSQL database approaches to supporting applications that process huge volumes of data.

Connected through hyperedge HE-1 (induced by source paper "storage solutions for big data systems a qualitative study and comparison"):
  with members:
    - "a billion updates per second using 30 000 hierarchical in memory d4m databases"
    - "foundationdb record layer a multi tenant structured datastore"
    - "hadoop perfect file a fast access container for small files with direct in disc metadata access"
    - "decentralized search on decentralized web"
    - "effects of storage heterogeneity in distributed cache systems"
    - "database as a service current issues and its future"
    - "chain of trust can trusted hardware help scaling blockchains"
    - "towards scaling blockchain systems via sharding"

Connected through hyperedge HE-2 (induced by source paper "bivariate cluster and suitability analysis of nosql solutions for different application areas"):
  with members:
    - "a billion updates per second using 30 000 hierarchical in memory d4m databases"
    - "foundationdb record layer a multi tenant structured datastore"
    - "effects of storage heterogeneity in distributed cache systems"
    - "database as a service current issues and its future"
    - "polypus a big data self deployable architecture for microblogging text extraction and real time sentiment analysis"
    - "a stitch in time saves nine sparql querying of property graphs using gremlin traversals"
    - "blocktag design and applications of a tagging system for blockchain analysis"
    - "g core a core for future graph query languages"

Connected through hyperedge HE-3 (induced by source paper "a perspective on the challenges and opportunities for privacy aware big transportation data"):
  with members:
    - "a blockchain framework for smart mobility"

Connected through hyperedge HE-4 (induced by source paper "big data model simulation on a graph database for surveillance in wireless multimedia sensor networks"):
  with members:
    - "sensor discovery and configuration framework for the internet of things paradigm"
    - "sensing as a service and big data"
    - "sensing as a service model for smart cities supported by internet of things"

Connected through hyperedge HE-5 (induced by source paper "annotation based automatic action processing"):
  with members:
    - "semantify it a platform for creation publication and distribution of semantic annotations"

Connected through hyperedge HE-6 (induced by source paper "a peta scale data movement and analysis in data warehouse apsdmadw"):
  with members:
    - "interactive analytical processing in big data systems a cross industry study of mapreduce workloads"

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.DB(Databases)