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: "diploid alignment is np hard"
  Abstract: Human genomes consist of pairs of homologous chromosomes, one of which is inherited from the mother and the other from the father. Species, such as human, with pairs of homologous chromosomes are called \textit{diploid}. Sequence analysis literature is, however, almost solely built under the model of a single \emph{haplotype sequence} representing a species. This fundamental choice is apparently due to the huge conceptual simplification of carrying out analyses over sequences rather than over pairs of related sequences. In this paper, we show that not only raising the abstraction level creates conceptual difficulties, but also the computational complexity will change for a natural non-trivial extension of optimal alignment to diploids. As of independent interest, our approach can also be seen as an extension of sequence alignment to labelled directed acyclic graphs (labeled DAGs). Namely, we show that a \emph{covering alignment} of two labeled DAGs is NP-hard. A covering alignment is to find two paths $P_1(A)$ and $P_2(A)$ in DAG $A$ and two paths $P_1(B)$ and $P_2(B)$ in DAG $B$ that cover the nodes of the graphs and maximize sum of the global alignment scores: $S(\ell(P_1(A)), \ell(P_1(B))) + S(\ell(P_2(A)), \ell(P_2(B)))$, where $\ell(P)$ is the concatenation of labels on the path $P$. Pair-wise alignment of haplotype sequences forming a diploid chromosome can be converted to a two-path coverable labelled DAG, and then the covering alignment models the similarity of two diploids over arbitrary recombination.

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.CC(Computational Complexity)