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: "it s all a matter of degree using degree information to optimize multiway joins"
  Abstract: We optimize multiway equijoins on relational tables using degree information. We give a new bound that uses degree information to more tightly bound the maximum output size of a query. On real data, our bound on the number of triangles in a social network can be up to $95$ times tighter than existing worst case bounds. We show that using only a constant amount of degree information, we are able to obtain join algorithms with a running time that has a smaller exponent than existing algorithms--{\em for any database instance}. We also show that this degree information can be obtained in nearly linear time, which yields asymptotically faster algorithms in the serial setting and lower communication algorithms in the MapReduce setting. #R##N#In the serial setting, the data complexity of join processing can be expressed as a function $O(\IN^x + \OUT)$ in terms of input size $\IN$ and output size $\OUT$ in which $x$ depends on the query. An upper bound for $x$ is given by fractional hypertreewidth. We are interested in situations in which we can get algorithms for which $x$ is strictly smaller than the fractional hypertreewidth. We say that a join can be processed in subquadratic time if $x < 2$. Building on the AYZ algorithm for processing cycle joins in quadratic time, for a restricted class of joins which we call $1$-series-parallel graphs, we obtain a complete decision procedure for identifying subquadratic solvability (subject to the $3$-SUM problem requiring quadratic time). Our $3$-SUM based quadratic lower bound is tight, making it the only known tight bound for joins that does not require any assumption about the matrix multiplication exponent $\omega$. We also give a MapReduce algorithm that meets our improved communication bound and handles essentially optimal parallelism.

Connected through hyperedge HE-1 (induced by source paper "instance and output optimal parallel algorithms for acyclic joins"):
  with members:
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "answering conjunctive queries under updates"
    - "worst case optimal algorithms for parallel query processing"
    - "what do shannon type inequalities submodular width and disjunctive datalog have to do with one another"
    - "the input output complexity of triangle enumeration"
    - "skew in parallel query processing"
    - "gym a multiround join algorithm in mapreduce"

Connected through hyperedge HE-2 (induced by source paper "topology dependent bounds for faqs"):
  with members:
    - "query to communication lifting for bpp"
    - "juggling functions inside a database"
    - "worst case optimal algorithms for parallel query processing"
    - "tight network topology dependent bounds on rounds of communication"
    - "the range of topological effects on communication"
    - "faq questions asked frequently"
    - "skew in parallel query processing"
    - "aggregation and ordering in factorised databases"

Connected through hyperedge HE-3 (induced by source paper "box covers and domain orderings for beyond worst case join processing"):
  with members:
    - "worst case optimal join algorithms techniques results and open problems"
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "computing join queries with functional dependencies"
    - "joins via geometric resolutions worst case and beyond"
    - "beyond worst case analysis for joins with minesweeper"
    - "worst case optimal join algorithms"

Connected through hyperedge HE-4 (induced by source paper "computing join queries with functional dependencies"):
  with members:
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "emptyheaded boolean algebra based graph processing"
    - "entropy bounds for conjunctive queries with functional dependencies"
    - "skew strikes back new developments in the theory of join algorithms"
    - "tractable hypergraph properties for constraint satisfaction and conjunctive queries"

Connected through hyperedge HE-5 (induced by source paper "sharesskew an algorithm to handle skew for joins in mapreduce"):
  with members:
    - "worst case optimal algorithms for parallel query processing"
    - "α k minimal sorting and skew join in mpi and mapreduce"
    - "skew in parallel query processing"
    - "gym a multiround join algorithm in mapreduce"
    - "the family of mapreduce and large scale data processing systems"
    - "beyond worst case analysis for joins with minesweeper"
    - "skew strikes back new developments in the theory of join algorithms"
    - "communication steps for parallel query processing"

Connected through hyperedge HE-6 (induced by source paper "aggregations over generalized hypertree decompositions"):
  with members:
    - "size bounds and query plans for relational joins"
    - "constraint solving via fractional edge covers"
    - "emptyheaded a relational engine for graph processing"
    - "gym a multiround join algorithm in mapreduce"
    - "aggregation and ordering in factorised databases"
    - "skew strikes back new developments in the theory of join algorithms"
    - "tractable hypergraph properties for constraint satisfaction and conjunctive queries"
    - "hypertree decompositions and tractable queries"

Connected through hyperedge HE-7 (induced by source paper "gym a multiround join algorithm in mapreduce"):
  with members:
    - "size bounds and query plans for relational joins"
    - "skew in parallel query processing"
    - "skew strikes back new developments in the theory of join algorithms"
    - "communication steps for parallel query processing"
    - "sorting searching and simulation in the mapreduce framework"
    - "the complexity of acyclic conjunctive queries revisited"
    - "hypertree decompositions and tractable queries"

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)