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 h imath l e x system for semantic information extraction"
  Abstract: The explosive growth and popularity of the Web has resulted in a huge amount of digital information sources on the Internet. Unfortunately, such sources only manage data, rather than the knowledge they carry. Recognizing, extracting, and structuring relevant information according to their semantics is a crucial task. Several approaches in the field of Information Extraction (IE) have been proposed to support the translation of semi-structured/unstructured documents into structured data or knowledge. Most of them have a high precision but, since they are mainly syntactic, they often have a low recall, are dependent on the document format, and ignore the semantics of information they extract. In this paper, we describe a new approach for semantic information extraction that could represent the basis for automatically extracting highly structured data from unstructured web sources without any undesirable trade-off between precision and recall. In short, the approach (i) is ontology driven, (ii) is based on a unified representation of documents, (iii) integrates existing IE techniques, (iv) implements semantic regular expressions, (v) has been implemented through Answer Set Programming, (vi) is employed in real-world applications, and (vii) is having a positive feedback from business customers.

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.AI(Artificial Intelligence)