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 "spaces trees and colors the algorithmic landscape of document retrieval on sequences"):
  Abstract: Document retrieval is one of the best established information retrieval activities since the sixties, pervading all search engines. Its aim is to obtain, from a collection of text documents, those most relevant to a pattern query. Current technology is mostly oriented to "natural language" text collections, where inverted indices are the preferred solution. As successful as this paradigm has been, it fails to properly handle some East Asian languages and other scenarios where the "natural language" assumptions do not hold. In this survey we cover the recent research in extending the document retrieval techniques to a broader class of sequence collections, which has applications bioinformatics, data and Web mining, chemoinformatics, software engineering, multimedia information retrieval, and many others. We focus on the algorithmic aspects of the techniques, uncovering a rich world of relations between document retrieval challenges and fundamental problems on trees, strings, range queries, discrete geometry, and others.

Includes members:
  Member "orthogonal range searching for text indexing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "time space trade offs for lempel ziv compressed indexing")
  Member "optimal top k document retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic data structures for document collections and graphs")
  Member "on optimal top k string retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "orthogonal range searching for text indexing")
  Member "faster compact top k document retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "document retrieval on repetitive string collections")
  Member "new lower and upper bounds for representing sequences":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "run compressed rank select for large alphabets")
  Member "towards an optimal space and query time index for top k document retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal top k document retrieval")
  Member "space efficient data analysis queries on grids":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "document listing on repetitive collections with guaranteed performance")
  Member "new algorithms on wavelet trees and applications to information retrieval":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "edge minimization in de bruijn graphs")

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.IR(Information Retrieval)