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 "combining aspects of genetic algorithms with weighted recommender hybridization"):
  Abstract: Recommender systems are established means to inspire users to watch interesting movies, discover baby names, or read books. The recommendation quality further improves by combining the results of multiple recommendation algorithms using hybridization methods. In this paper, we focus on the task of combining unscored recommendations into a single ensemble. Our proposed method is inspired by genetic algorithms. It repeatedly selects items from the recommendations to create a population of items that will be used for the final ensemble. We compare our method with a weighted voting method and test the performance of both in a movie- and name-recommendation scenario. We were able to outperform the weighted method on both datasets by 20.3 % and 31.1 % and decreased the overall execution time by up to 19.9 %. Our results do not only propose a new kind of hybridization method, but introduce the field of recommender hybridization to further work with genetic algorithms.

Includes members:
  Member "collaborative filtering ensemble for personalized name recommendation":
    also connected through other hyperedges:
      (none)
  Member "recommending given names":
    also connected through other hyperedges:
      (none)
  Member "content based book recommending using learning for text categorization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "citation recommendation approaches and datasets")

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.IR(Information Retrieval)