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: "an analytical study of large sparql query logs"
  Abstract: With the adoption of RDF as the data model for Linked Data and the Semantic Web, query specification from end- users has become more and more common in SPARQL end- points. In this paper, we conduct an in-depth analytical study of the queries formulated by end-users and harvested from large and up-to-date query logs from a wide variety of RDF data sources. As opposed to previous studies, ours is the first assessment on a voluminous query corpus, span- ning over several years and covering many representative SPARQL endpoints. Apart from the syntactical structure of the queries, that exhibits already interesting results on this generalized corpus, we drill deeper in the structural char- acteristics related to the graph- and hypergraph represen- tation of queries. We outline the most common shapes of queries when visually displayed as pseudographs, and char- acterize their (hyper-)tree width. Moreover, we analyze the evolution of queries over time, by introducing the novel con- cept of a streak, i.e., a sequence of queries that appear as subsequent modifications of a seed query. Our study offers several fresh insights on the already rich query features of real SPARQL queries formulated by real users, and brings us to draw a number of conclusions and pinpoint future di- rections for SPARQL query evaluation, query optimization, tuning, and benchmarking.

Connected through hyperedge HE-1 (induced by source paper "knowledge graphs"):
  with members:
    - "modl a modular ontology design library"
    - "drum end to end differentiable rule mining on knowledge graphs"
    - "hypernetwork knowledge graph embeddings"
    - "ceres distantly supervised relation extraction from the semi structured web"
    - "a tutorial on modular ontology modeling with ontology design patterns the cooking recipes ontology"
    - "building an ecosystem for the tyrolean tourism knowledge graph"
    - "eventkg a multilingual event centric temporal knowledge graph"
    - "how powerful are graph neural networks"

Connected through hyperedge HE-2 (induced by source paper "complexity analysis of general and fractional hypertree decompositions"):
  with members:
    - "hyperbench a benchmark and tool for hypergraphs and empirical findings"
    - "tree projections and constraint optimization problems fixed parameter tractability and parallel algorithms"
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "old techniques for new join algorithms a case study in rdf processing"
    - "general and fractional hypertree decompositions hard and easy cases"
    - "myhill nerode methods for hypergraphs"
    - "faq questions asked frequently"

Connected through hyperedge HE-3 (induced by source paper "structural indexing for conjunctive path queries"):
  with members:
    - "the ubiquity of large graphs and surprising challenges of graph processing extended survey"
    - "survey and taxonomy of lossless graph compression and space efficient graph representations"
    - "gmark schema driven generation of graphs and queries"
    - "g core a core for future graph query languages"
    - "foundations of modern query languages for graph databases"
    - "taming subgraph isomorphism for rdf query processing"
    - "similarity and bisimilarity notions appropriate for characterizing indistinguishability in fragments of the calculus of relations"
    - "relative expressive power of navigational querying on graphs"

Connected through hyperedge HE-4 (induced by source paper "containment of simple regular path queries"):
  with members:
    - "on the complexity of xpath containment in the presence of disjunction dtds and variables"

Connected through hyperedge HE-5 (induced by source paper "a comparative survey of recent natural language interfaces for databases"):
  with members:
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "amuse multilingual semantic parsing for question answering over linked data"
    - "knowledge rich natural language queries over structured biological databases"
    - "learning a neural semantic parser from user feedback"
    - "kbqa learning question answering over qa corpora and knowledge bases"
    - "language to logical form with neural attention"
    - "effective approaches to attention based neural machine translation"
    - "sequence to sequence learning with neural networks"

Connected through hyperedge HE-6 (induced by source paper "semantic guided and response times bounded top k similarity search over knowledge graphs"):
  with members:
    - "accelerating partial evaluation in distributed sparql query evaluation"
    - "keyword search on rdf graphs a query graph assembly approach"
    - "kbqa learning question answering over qa corpora and knowledge bases"
    - "processing sparql queries over distributed rdf graphs"
    - "connecting language and knowledge bases with embedding models for relation extraction"
    - "querying knowledge graphs by example entity tuples"
    - "optimal aggregation algorithms for middleware"

Connected through hyperedge HE-7 (induced by source paper "conjunctive regular path queries with string variables"):
  with members:
    - "boundedness of conjunctive regular path queries"
    - "a trichotomy for regular trail queries"
    - "split correctness in information extraction"
    - "deterministic regular expressions with back references"
    - "joining extractions of regular expressions"
    - "foundations of modern query languages for graph databases"

Connected through hyperedge HE-8 (induced by source paper "a trichotomy for regular trail queries"):
  with members:
    - "g core a core for future graph query languages"

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)