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: "testing reading tactics for automated reading assistance is it useful to apply old knowledge"
  Abstract: Given the growing number of new publications appearing everyday, literature reviews are important for software engineering researches to stay up-to-date with their field. A state-of-the-art text mining method (FASTREAD) supports SE researchers in selecting literature of their interests (this approach uses an active learner to suggest what small number of papers, out of many thousands of candidates, might be worth reading). #R##N#While FASTREAD allows researchers to skim 90% fewer papers in fresh new literature reviews, we find two common scenarios where knowledge from old literature reviews can further enhance new one: i.e. a) researchers updating their old literature reviews; b) researchers initializing new literature reviews on topics similar to those of an old review. This paper tested two novel UPDATE and REUSE extensions to FASTREAD. While UPDATE was proved to be quite straight-forward (just importing data from old review to bootstrap FASTREAD), REUSE was much more complex and required additional architecture. #R##N#Overall, we find that UPDATE, or our augmented REUSE tactic, allows researchers to skim an additional 20% to 50% fewer papers by applying old knowledge in the corresponding scenarios. Hence, we strongly recommend sharing and applying old knowledge for new literature reviews.

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.SE(Software Engineering)