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: "context spaces as the cornerstone of a near transparent and self reorganizing semantic desktop"
  Abstract: Existing Semantic Desktops are still reproached for being too complicated to use or not scaling well. Besides, a real “killer app” is still missing. In this paper, we present a new prototype inspired by NEPOMUK and its successors having a semantic graph and ontologies as its basis. In addition, we introduce the idea of context spaces that users can directly interact with and work on. To make them available in all applications without further ado, the system is transparently integrated using mostly standard protocols complemented by a sidebar for advanced features. By exploiting collected context information and applying Managed Forgetting features (like hiding, condensation or deletion), the system is able to dynamically reorganize itself, which also includes a kind of tidy-up-itself functionality. We therefore expect it to be more scalable while providing new levels of user support. An early prototype has been implemented and is presented in this demo.

Connected through hyperedge HE-1 (induced by source paper "managed forgetting to support information management and knowledge work"):
  with members:
    - "temporarily unavailable memory inhibition in cognitive and computer science"
    - "advanced memory buoyancy for forgetful information systems"
    - "inflection tolerant ontology based named entity recognition for real time applications"
    - "context aware computing for the internet of things a survey"

Connected through hyperedge HE-2 (induced by source paper "interactive concept mining on personal data bootstrapping semantic services"):
  with members:
    - "deep linking desktop resources"
    - "inflection tolerant ontology based named entity recognition for real time applications"

Connected through hyperedge HE-3 (induced by source paper "inflection tolerant ontology based named entity recognition for real time applications"):
  with members:
    - "speedread a fast named entity recognition pipeline"

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.AI(Artificial Intelligence)