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: "believe it or not adding belief annotations to databases"
  Abstract: We propose a database model that allows users to annotate data with belief statements. Our motivation comes from scientific database applications where a community of users is working together to assemble, revise, and curate a shared data repository. As the community accumulates knowledge and the database content evolves over time, it may contain conflicting information and members can disagree on the information it should store. For example, Alice may believe that a tuple should be in the database, whereas Bob disagrees. He may also insert the reason why he thinks Alice believes the tuple should be in the database, and explain what he thinks the correct tuple should be instead. #R##N#We propose a formal model for Belief Databases that interprets users' annotations as belief statements. These annotations can refer both to the base data and to other annotations. We give a formal semantics based on a fragment of multi-agent epistemic logic and define a query language over belief databases. We then prove a key technical result, stating that every belief database can be encoded as a canonical Kripke structure. We use this structure to describe a relational representation of belief databases, and give an algorithm for translating queries over the belief database into standard relational queries. Finally, we report early experimental results with our prototype implementation on synthetic data.

Connected through hyperedge HE-1 (induced by source paper "scrutinizer a mixed initiative approach to large scale data driven claim verification"):
  with members:
    - "explainable fact checking with probabilistic answer set programming"
    - "claimrank detecting check worthy claims in arabic and english"
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "automated fact checking task formulations methods and future directions"
    - "fact checking in community forums"
    - "discriminative predicate path mining for fact checking in knowledge graphs"
    - "the rise of social bots"
    - "computational fact checking from knowledge networks"

Connected through hyperedge HE-2 (induced by source paper "linearized and single pass belief propagation"):
  with members:
    - "semi supervised learning with heterophily"
    - "linview incremental view maintenance for complex analytical queries"
    - "vog summarizing and understanding large graphs"
    - "deltacon a principled massive graph similarity function"
    - "spectral redemption in clustering sparse networks"
    - "residual belief propagation informed scheduling for asynchronous message passing"
    - "paris probabilistic alignment of relations instances and schema"
    - "data conflict resolution using trust mappings"

Connected through hyperedge HE-3 (induced by source paper "approximate query answering in inconsistent databases"):
  with members:
    - "answer sets for consistent query answering in inconsistent databases"
    - "relational association rules getting warmer"

Connected through hyperedge HE-4 (induced by source paper "data conflict resolution using trust mappings"):
  with members:
    - "the dlv system for knowledge representation and reasoning"

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)