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: "engineering crowdsourced stream processing systems"
  Abstract: A crowdsourced stream processing system (CSP) is a system that incorporates crowdsourced tasks in the processing of a data stream. This can be seen as enabling crowdsourcing work to be applied on a sample of large-scale data at high speed, or equivalently, enabling stream processing to employ human intelligence. It also leads to a substantial expansion of the capabilities of data processing systems. Engineering a CSP system requires the combination of human and machine computation elements. From a general systems theory perspective, this means taking into account inherited as well as emerging properties from both these elements. In this paper, we position CSP systems within a broader taxonomy, outline a series of design principles and evaluation metrics, present an extensible framework for their design, and describe several design patterns. We showcase the capabilities of CSP systems by performing a case study that applies our proposed framework to the design and analysis of a real system (AIDR) that classifies social media messages during time-critical crisis events. Results show that compared to a pure stream processing system, AIDR can achieve a higher data classification accuracy, while compared to a pure crowdsourcing solution, the system makes better use of human workers by requiring much less manual work effort.

Connected through hyperedge HE-1 (induced by source paper "modeling human annotation errors to design bias aware systems for social stream processing"):
  with members:
    - "quantifying the impact of cognitive biases in question answering systems"
    - "crisismmd multimodal twitter datasets from natural disasters"
    - "ranking of social media alerts with workload bounds in emergency operation centers"

Connected through hyperedge HE-2 (induced by source paper "it s about time online macrotask sequencing in expert crowdsourcing"):
  with members:
    - "online assignment of heterogeneous tasks in crowdsourcing markets"
    - "mechanism design for time critical and cost critical task execution via crowdsourcing"
    - "analytic methods for optimizing realtime crowdsourcing"
    - "the labor economics of paid crowdsourcing"

Connected through hyperedge HE-3 (induced by source paper "cross language domain adaptation for classifying crisis related short messages"):
  with members:
    - "processing social media messages in mass emergency a survey"
    - "domain adaptation for statistical classifiers"

Connected through hyperedge HE-4 (induced by source paper "processing social media messages in mass emergency a survey"):
  with members:
    - "where in the world are you geolocation and language identification in twitter"
    - "understanding types of users on twitter"
    - "beating the news with embers forecasting civil unrest using open source indicators"
    - "tweetcred real time credibility assessment of content on twitter"
    - "event evolution tracking from streaming social posts"

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)