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: "the placement of the head that minimizes online memory a complex systems approach"
  Abstract: It is well known that the length of a syntactic dependency determines its online memory cost. Thus, the problem of the placement of a head and its dependents (complements or modifiers) that minimizes online memory is equivalent to the problem of the minimum linear arrangement of a star tree. However, how that length is translated into cognitive cost is not known. This study shows that the online memory cost is minimized when the head is placed at the center, regardless of the function that transforms length into cost, provided only that this function is strictly monotonically increasing. Online memory defines a quasi-convex adaptive landscape with a single central minimum if the number of elements is odd and two central minima if that number is even. We discuss various aspects of the dynamics of word order of subject (S), verb (V) and object (O) from a complex systems perspective and suggest that word orders tend to evolve by swapping adjacent constituents from an initial or early SOV configuration that is attracted towards a central word order by online memory minimization. We also suggest that the stability of SVO is due to at least two factors, the quasi-convex shape of the adaptive landscape in the online memory dimension and online memory adaptations that avoid regression to SOV. Although OVS is also optimal for placing the verb at the center, its low frequency is explained by its long distance to the seminal SOV in the permutation space.

Connected through hyperedge HE-1 (induced by source paper "optimal coding and the origins of zipfian laws"):
  with members:
    - "anti efficient encoding in emergent communication"
    - "source codes in human communication"
    - "the polysemy of the words that children learn over time"

Connected through hyperedge HE-2 (induced by source paper "towards a theory of word order comment on dependency distance a new perspective on syntactic patterns in natural language by haitao liu et al"):
  with members:
    - "the placement of the head that maximizes predictability an information theoretic approach"
    - "non crossing dependencies least effort not grammar"
    - "kauffman s adjacent possible in word order evolution"
    - "reply to the commentary be careful when assuming the obvious by p alday"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-3 (induced by source paper "the placement of the head that maximizes predictability an information theoretic approach"):
  with members:
    - "the polysemy of the words that children learn over time"
    - "compression and the origins of zipf s law for word frequencies"
    - "kauffman s adjacent possible in word order evolution"
    - "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2016"

Connected through hyperedge HE-4 (induced by source paper "crossings as a side effect of dependency lengths"):
  with members:
    - "can chunking reduce syntactic complexity of natural languages"
    - "transition based dependency parsing with stack long short term memory"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "random crossings in dependency trees"

Connected through hyperedge HE-5 (induced by source paper "non crossing dependencies least effort not grammar"):
  with members:
    - "the risks of mixing dependency lengths from sequences of different length"
    - "hubiness length crossings and their relationships in dependency trees"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-6 (induced by source paper "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2015"):
  with members:
    - "compression and the origins of zipf s law for word frequencies"
    - "crossings as a side effect of dependency lengths"
    - "compression and the origins of zipf s law of abbreviation"
    - "reply to the commentary be careful when assuming the obvious by p alday"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "the optimality of attaching unlinked labels to unlinked meanings"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-7 (induced by source paper "liberating language research from dogmas of the 20th century"):
  with members:
    - "scarcity of crossing dependencies a direct outcome of a specific constraint"
    - "crossings as a side effect of dependency lengths"
    - "dependency length minimization puzzles and promises"
    - "reply to the commentary be careful when assuming the obvious by p alday"

Connected through hyperedge HE-8 (induced by source paper "compression and the origins of zipf s law of abbreviation"):
  with members:
    - "rank diversity of languages generic behavior in computational linguistics"
    - "be careful when assuming the obvious commentary on the placement of the head that minimizes online memory a complex systems approach"
    - "a stronger null hypothesis for crossing dependencies"
    - "the optimality of attaching unlinked labels to unlinked meanings"

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.CL(Computation and Language)