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: "slope one predictors for online rating based collaborative filtering"
  Abstract: Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which precompute the average difference between the ratings of one item and another for users who rated both. Slope one algorithms are easy to implement, efficient to query, reasonably accurate, and they support both online queries and dynamic updates, which makes them good candidates for real-world systems. The basic slope one scheme is suggested as a new reference scheme for collaborative filtering. By factoring in items that a user liked separately from items that a user disliked, we achieve results competitive with slower memory-based schemes over the standard benchmark EachMovie and Movielens data sets while better fulfilling the desiderata of CF applications.

Connected through hyperedge HE-1 (induced by source paper "an ontology based recommender system with an application to the star trek television franchise"):
  with members:
    - "the literary theme ontology for media annotation and information retrieval"
    - "hybrid recommender systems a systematic literature review"
    - "semantic similarity in a taxonomy an information based measure and its application to problems of ambiguity in natural language"

Connected through hyperedge HE-2 (induced by source paper "preference modeling by exploiting latent components of ratings"):
  with members:
    - "uncovering the information core in recommender systems"
    - "from amateurs to connoisseurs modeling the evolution of user expertise through online reviews"
    - "empirical analysis of predictive algorithms for collaborative filtering"
    - "learning attitudes and attributes from multi aspect reviews"

Connected through hyperedge HE-3 (induced by source paper "proofpeer collaborative theorem proving"):
  with members:
    - "capturing hiproofs in hol light"
    - "recycling proof patterns in coq case studies"
    - "isabelle jedit a prover ide within the pide framework"
    - "a web interface for matita"
    - "learning assisted automated reasoning with flyspeck"
    - "large formal wikis issues and solutions"
    - "coase s penguin or linux and the nature of the firm"

Connected through hyperedge HE-4 (induced by source paper "a comparative study of collaborative filtering algorithms"):
  with members:
    - "empirical analysis of predictive algorithms for collaborative filtering"
    - "collaborative filtering by personality diagnosis a hybrid memory and model based approach"
    - "estimating probabilities in recommendation systems"
    - "feature weighted linear stacking"

Connected through hyperedge HE-5 (induced by source paper "recommender systems by means of information retrieval"):
  with members:
    - "empirical analysis of predictive algorithms for collaborative filtering"

Connected through hyperedge HE-6 (induced by source paper "random graphs for performance evaluation of recommender systems"):
  with members:
    - "random graph generator for bipartite networks modeling"

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.DB(Databases)