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: "almost cover free codes and designs"
  Abstract: An $s$-subset of codewords of a binary code $X$ is said to be an {\em $(s,\ell)$-bad} in $X$ if the code $X$ contains a subset of other $\ell$ codewords such that the conjunction of the $\ell$ codewords is covered by the disjunctive sum of the $s$ codewords. Otherwise, the $s$-subset of codewords of $X$ is said to be an {\em $(s,\ell)$-good} in~$X$.mA binary code $X$ is said to be a cover-free $(s,\ell)$-code if the code $X$ does not contain $(s,\ell)$-bad subsets. In this paper, we introduce a natural {\em probabilistic} generalization of cover-free $(s,\ell)$-codes, namely: a binary code is said to be an almost cover-free $(s,\ell)$-code if {\em almost all} $s$-subsets of its codewords are $(s,\ell)$-good. We discuss the concept of almost cover-free $(s,\ell)$-codes arising in combinatorial group testing problems connected with the nonadaptive search of defective supersets (complexes). We develop a random coding method based on the ensemble of binary constant weight codes to obtain lower bounds on the capacity of such codes.

Connected through hyperedge HE-1 (induced by source paper "group testing schemes from codes and designs"):
  with members:
    - "nonadaptive group testing with random set of defectives"
    - "nonadaptive group testing with random set of defectives via constant weight codes"
    - "bounds on the rate of disjunctive codes"
    - "semiquantitative group testing"
    - "on almost disjunct matrices for group testing"

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.IT(Information Theory)