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: "efficient snapshot retrieval over historical graph data"
  Abstract: We address the problem of managing historical data for large evolving information networks like social networks or citation networks, with the goal to enable temporal and evolutionary queries and analysis. We present the design and architecture of a distributed graph database system that stores the entire history of a network and provides support for efficient retrieval of multiple graphs from arbitrary time points in the past, in addition to maintaining the current state for ongoing updates. Our system exposes a general programmatic API to process and analyze the retrieved snapshots. We introduce DeltaGraph, a novel, extensible, highly tunable, and distributed hierarchical index structure that enables compactly recording the historical information, and that supports efficient retrieval of historical graph snapshots for single-site or parallel processing. Along with the original graph data, DeltaGraph can also maintain and index auxiliary information; this functionality can be used to extend the structure to efficiently execute queries like subgraph pattern matching over historical data. We develop analytical models for both the storage space needed and the snapshot retrieval times to aid in choosing the right parameters for a specific scenario. In addition, we present strategies for materializing portions of the historical graph state in memory to further speed up the retrieval process. Secondly, we present an in-memory graph data structure called GraphPool that can maintain hundreds of historical graph instances in main memory in a non-redundant manner. We present a comprehensive experimental evaluation that illustrates the effectiveness of our proposed techniques at managing historical graph information.

Connected through hyperedge HE-1 (induced by source paper "practice of streaming and dynamic graphs concepts models systems and parallelism"):
  with members:
    - "storing and querying large scale spatio temporal graphs with high throughput edge insertions"
    - "parallel batch dynamic graph connectivity"
    - "demystifying graph databases analysis and taxonomy of data organization system designs and graph queries"
    - "graph processing on fpgas taxonomy survey challenges"
    - "slim fly a cost effective low diameter network topology"
    - "red blue pebbling revisited near optimal parallel matrix matrix multiplication"
    - "dynamic algorithms for the massively parallel computation model"
    - "fatpaths routing in supercomputers data centers and clouds with low diameter networks when shortest paths fall short"

Connected through hyperedge HE-2 (induced by source paper "low latency graph streaming using compressed purely functional trees"):
  with members:
    - "multiversion concurrency with bounded delay and precise garbage collection"
    - "theoretically efficient parallel graph algorithms can be fast and scalable"
    - "pam parallel augmented maps"
    - "parallel local graph clustering"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "storing and analyzing historical graph data at scale"
    - "the gap benchmark suite"

Connected through hyperedge HE-3 (induced by source paper "using compressed suffix arrays for a compact representation of temporal graphs"):
  with members:
    - "action2activity recognizing complex activities from sensor data"
    - "compact trip representation over networks"
    - "an introduction to temporal graphs an algorithmic perspective"
    - "exploring the structure and function of temporal networks with dynamic graphlets"
    - "windows into relational events data structures for contiguous subsequences of edges"
    - "succinct indexable dictionaries with applications to encoding k ary trees prefix sums and multisets"

Connected through hyperedge HE-4 (induced by source paper "forkbase an efficient storage engine for blockchain and forkable applications"):
  with members:
    - "blocksci design and applications of a blockchain analysis platform"
    - "ustore a distributed storage with rich semantics"
    - "untangling blockchain a data processing view of blockchain systems"
    - "principles of dataset versioning exploring the recreation storage tradeoff"
    - "datahub collaborative data science dataset version management at scale"

Connected through hyperedge HE-5 (induced by source paper "rstore a distributed multi version document store"):
  with members:
    - "principles of dataset versioning exploring the recreation storage tradeoff"
    - "data placement and replica selection for improving co location in distributed environments"

Connected through hyperedge HE-6 (induced by source paper "portal a query language for evolving graphs"):
  with members:
    - "on graph deltas for historical queries"
    - "shark sql and rich analytics at scale"
    - "nonparametric link prediction in dynamic networks"

Connected through hyperedge HE-7 (induced by source paper "best friends forever bff finding lasting dense subgraphs"):
  with members:
    - "space and time efficient algorithm for maintaining dense subgraphs on one pass dynamic streams"
    - "densest subgraph in streaming and mapreduce"

Connected through hyperedge HE-8 (induced by source paper "storing and analyzing historical graph data at scale"):
  with members:
    - "information contagion an empirical study of the spread of news on digg and twitter social networks"
    - "fast incremental and personalized pagerank"
    - "semantics and complexity of sparql"

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)