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: "efficient query rewrite for structured web queries"
  Abstract: Web search engines and specialized online verticals are increasingly incorporating results from structured data sources to answer semantically rich user queries. For example, the query \WebQuery{Samsung 50 inch led tv} can be answered using information from a table of television data. However, the users are not domain experts and quite often enter values that do not match precisely the underlying data. Samsung makes 46- or 55- inch led tvs, but not 50-inch ones. So a literal execution of the above mentioned query will return zero results. For optimal user experience, a search engine would prefer to return at least a minimum number of results as close to the original query as possible. Furthermore, due to typical fast retrieval speeds in web-search, a search engine query execution is time-bound. #R##N#In this paper, we address these challenges by proposing algorithms that rewrite the user query in a principled manner, surfacing at least the required number of results while satisfying the low-latency constraint. We formalize these requirements and introduce a general formulation of the problem. We show that under a natural formulation, the problem is NP-Hard to solve optimally, and present approximation algorithms that produce good rewrites. We empirically validate our algorithms on large-scale data obtained from a commercial search engine's shopping vertical.

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.IR(Information Retrieval)