human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "memory based shallow parsing"):
  Abstract: We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of the memory-based learner. Our approach is evaluated on standard data sets and the results are compared with that of other systems. This reveals that our approach works well for base phrase identification while its application towards recognizing embedded structures leaves some room for improvement.

Includes members:
  Member "what is the minimal set of fragments that achieves maximal parse accuracy":
    also connected through other hyperedges:
      (none)
  Member "introduction to the conll 2000 shared task chunking":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "linguistic knowledge and transferability of contextual representations")
  Member "applying system combination to base noun phrase identification":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning computational grammars")
  Member "noun phrase recognition by system combination":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multidimensional transformation based learning")
  Member "parsing with the shortest derivation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bootstrapping structure into language alignment based learning")
  Member "more accurate tests for the statistical significance of result differences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "two level transformer and auxiliary coherence modeling for improved text segmentation")
  Member "a learning approach to shallow parsing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multidimensional transformation based learning")
  Member "representing text chunks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an efficient architecture for predicting the case of characters using sequence models")

Question: Please tell me which class the source paper 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)