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 "semi streaming algorithms for annotated graph streams"):
  Abstract: Considerable effort has been devoted to the development of streaming algorithms for analyzing massive graphs. Unfortunately, many results have been negative, establishing that a wide variety of problems require $\Omega(n^2)$ space to solve. One of the few bright spots has been the development of semi-streaming algorithms for a handful of graph problems -- these algorithms use space $O(n\cdot\text{polylog}(n))$. #R##N#In the annotated data streaming model of Chakrabarti et al., a computationally limited client wants to compute some property of a massive input, but lacks the resources to store even a small fraction of the input, and hence cannot perform the desired computation locally. The client therefore accesses a powerful but untrusted service provider, who not only performs the requested computation, but also proves that the answer is correct. #R##N#We put forth the notion of semi-streaming algorithms for annotated graph streams (semi-streaming annotation schemes for short). These are protocols in which both the client's space usage and the length of the proof are $O(n \cdot \text{polylog}(n))$. We give evidence that semi-streaming annotation schemes represent a substantially more robust solution concept than does the standard semi-streaming model. On the positive side, we give semi-streaming annotation schemes for two dynamic graph problems that are intractable in the standard model: (exactly) counting triangles, and (exactly) computing maximum matchings. The former scheme answers a question of Cormode. On the negative side, we identify for the first time two natural graph problems (connectivity and bipartiteness in a certain edge update model) that can be solved in the standard semi-streaming model, but cannot be solved by annotation schemes of "sub-semi-streaming" cost. That is, these problems are just as hard in the annotations model as they are in the standard model.

Includes members:
  Member "an improved interactive streaming algorithm for the distinct elements problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "streaming verification of graph properties")
  Member "annotations for sparse data streams":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on szk and pp")
  Member "arthur merlin streaming complexity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "streaming verification in data analysis")
  Member "time optimal interactive proofs for circuit evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "doubly efficient pseudo deterministic proofs")
  Member "single pass sparsification in the streaming model with edge deletions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "work efficient batch incremental minimum spanning trees with applications to the sliding window model")
  Member "practical verified computation with streaming interactive proofs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "doubly efficient pseudo deterministic proofs")
  Member "verifying computations with streaming interactive proofs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "efficient rational proofs with strong utility gap guarantees")
  Member "invertible bloom lookup tables":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "peeling close to the orientability threshold spatial coupling in hashing based data structures")

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.DS(Data Structures and Algorithms)