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 "semi structured data extraction and modelling the wia project"):
  Abstract: Over the last decades, the amount of data of all kinds available electronically has increased dramatically. Data are accessible through a range of interfaces including Web browsers, database query languages, application-specific interfaces, built on top of a number of different data exchange formats. All these data span from un-structured to highly structured data. Very often, some of them have structure even if the structure is implicit, and not as rigid or regular as that found in standard database systems. Spreadsheet documents are prototypical in this respect. Spreadsheets are the lightweight technology able to supply companies with easy to build business management and business intelligence applications, and business people largely adopt spreadsheets as smart vehicles for data files generation and sharing. Actually, the more spreadsheets grow in complexity (e.g., their use in product development plans and quoting), the more their arrangement, maintenance, and analysis appear as a knowledge-driven activity. The algorithmic approach to the problem of automatic data structure extraction from spreadsheet documents (i.e., grid-structured and free topological-related data) emerges from the WIA project: Worksheets Intelligent Analyser. The WIA-algorithm shows how to provide a description of spreadsheet contents in terms of higher level of abstractions or conceptualisations. In particular, the WIA-algorithm target is about the extraction of i) the calculus work-flow implemented in the spreadsheets formulas and ii) the logical role played by the data which take part into the calculus. The aim of the resulting conceptualisations is to provide spreadsheets with abstract representations useful for further model refinements and optimizations through evolutionary algorithms computations.

Includes members:
  Member "automated spreadsheet development":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spreadsheets the good the bad and the downright ugly")
  Member "a toolkit for scalable spreadsheet visualization":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "excelsior bringing the benefits of modularisation to excel")
  Member "reducing overconfidence in spreadsheet development":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the reification of an incorrect and inappropriate spreadsheet model")
  Member "interpretation as a factor in understanding flawed spreadsheets":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the interpretation of spreadsheets within their environment")
  Member "spreadsheet engineering a research framework":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bientropy trientropy and primality")

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.SE(Software Engineering)