human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fast join project query evaluation using matrix multiplication"):
  Abstract: In the last few years, much effort has been devoted to developing join algorithms in order to achieve worst-case optimality for join queries over relational databases. Towards this end, the database community has had considerable success in developing succinct algorithms that achieve worst-case optimal runtime for full join queries, i.e the join is over all variables present in the input database. However, not much is known about join evaluation with {\em projections} beyond some simple techniques of pushing down the projection operator in the query execution plan. Such queries have a large number of applications in entity matching, graph analytics and searching over compressed graphs. In this paper, we study how a class of join queries with projections can be evaluated faster using worst-case optimal algorithms together with matrix multiplication. Crucially, our algorithms are parameterized by the output size of the final result, allowing for choice of the best execution strategy. We implement our algorithms as a subroutine and compare the performance with state-of-the-art techniques to show they can be improved upon by as much as 50x. More importantly, our experiments indicate that matrix multiplication is a useful operation that can help speed up join processing owing to highly optimized open source libraries that are also highly parallelizable.

Includes members:
  Member "memory efficient group by aggregates over multi way joins":
    also connected through other hyperedges:
      (none)
  Member "trade offs in static and dynamic evaluation of hierarchical queries":
    also connected through other hyperedges:
      (none)
  Member "size bounds and query plans for relational joins":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "complexity analysis of general and fractional hypertree decompositions")
  Member "extracting and analyzing hidden graphs from relational databases":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "kaskade graph views for efficient graph analytics")
  Member "compressed representations of conjunctive query results":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "constant delay enumeration with fpt preprocessing for conjunctive queries of bounded submodular width")
  Member "improved rectangular matrix multiplication using powers of the coppersmith winograd tensor":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "set containment join revisited":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gb kmv an augmented kmv sketch for approximate containment similarity search")
  Member "data structure lower bounds for document indexing problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the hardness of set disjointness and set intersection with bounded universe")

Question: Please tell me which class the source paper 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)