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 "temporally evolving community detection and prediction in content centric networks"):
  Abstract: In this work, we consider the problem of combining link, content and temporal analysis for community detection and prediction in evolving networks. Such temporal and content-rich networks occur in many real-life settings, such as bibliographic networks and question answering forums. Most of the work in the literature (that uses both content and structure) deals with static snapshots of networks, and they do not reflect the dynamic changes occurring over multiple snapshots. Incorporating dynamic changes in the communities into the analysis can also provide useful insights about the changes in the network such as the migration of authors across communities. In this work, we propose Chimera, a shared factorization model that can simultaneously account for graph links, content, and temporal analysis. This approach works by extracting the latent semantic structure of the network in multidimensional form, but in a way that takes into account the temporal continuity of these embeddings. Such an approach simplifies temporal analysis of the underlying network by using the embedding as a surrogate. A consequence of this simplification is that it is also possible to use this temporal sequence of embeddings to predict future communities. We present experimental results illustrating the effectiveness of the approach.

Includes members:
  Member "predicting community evolution in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "community discovery in dynamic networks a survey")
  Member "predicting small group accretion in social networks a topology based incremental approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "temporally evolving community detection and prediction in content centric networks")
  Member "detecting overlapping temporal community structure in time evolving networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "temporally evolving community detection and prediction in content centric networks")
  Member "different approaches to community evolution prediction in blogosphere":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a comparative study of different approaches for tracking communities in evolving social networks")
  Member "sequential detection of temporal communities by estrangement confinement":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "community discovery in dynamic networks a survey")
  Member "efficient community detection in large networks using content and links":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "social science guided feature engineering a novel approach to signed link analysis")

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.LG(Machine Learning)