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 "caching policy optimization for d2d communications by learning user preference"):
  Abstract: Cache-enabled device-to-device (D2D) communications can boost network throughput. By pre-downloading contents to local caches of users, the content requested by a user can be transmitted via D2D links by other users in proximity. Prior works optimize the caching policy at users with the knowledge of content popularity, defined as the probability distribution of request for every file in a library from by all users. However, content popularity can not reflect the interest of each individual user and thus popularity-based caching policy may not fully capture the performance gain introduced by caching. In this paper, we optimize caching policy for cache-enabled D2D by learning user preference, defined as the conditional probability distribution of a user's request for a file given that the user sends a request. We first formulate an optimization problem with given user preference to maximize the offloading probability, which is proved as NP-hard, and then provide a greedy algorithm to find the solution. In order to predict the preference of each individual user, we model the user request behavior by probabilistic latent semantic analysis (pLSA), and then apply expectation maximization (EM) algorithm to estimate the model parameters. Simulation results show that the user preference can be learnt quickly. Compared to the popularity-based caching policy, the offloading gain achieved by the proposed policy can be remarkably improved even with predicted user preference.

Includes members:
  Member "caching at the wireless edge design aspects challenges and future directions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "enhancing physical layer security of random caching in large scale multi antenna heterogeneous wireless networks")
  Member "wireless device to device caching networks basic principles and system performance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")
  Member "energy saving pushing based on personal interest and context information":
    also connected through other hyperedges:
      (none)
  Member "placing dynamic content in caches with small population":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online convex optimization for caching networks")
  Member "a provably efficient online collaborative caching algorithm for multicell coordinated systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a rolling horizon dynamic programming approach for collaborative caching")
  Member "optimal geographic caching in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "online convex optimization for caching networks")
  Member "cooperative local caching and file sharing under heterogeneous file preferences":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "coded caching clusters with device to device communications")
  Member "learning based optimization of cache content in a small cell base station":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal scheduling of content caching subject to deadline")

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.IT(Information Theory)