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 "finding astronomical communities through co readership analysis"):
  Abstract: Whenever a large group of people are engaged in an activity, communities will form. The nature of these communities depends on the relationship considered. In the group of people who regularly use scholarly literature, a relationship like “person i and person j have cited the same paper” might reveal communities of people working in a particular field. On this poster, we will investigate the relationship “person i and person j have read the same paper”. Using the data logs of the NASA/Smithsonian Astrophysics Data System (ADS), we first determine the population that will participate by requiring that a user queries the ADS at a certain rate. Next, we apply the relationship to this population. The result of this will be an abstract “relationship space”, which we will describe in terms of various “representations”. Examples of such “representations” are the projection of co-read vectors onto Principal Components and the spectral density of the co-read network. We will show that the co-read relationship results in structure, we will describe this structure and we will provide a first attempt in the classification of this structure in terms of astronomical communities. The ADS is funded by NASA Grant NNG06GG68G.

Includes members:
  Member "effect of e printing on citation rates in astronomy and physics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "core elements in the process of citing publications conceptual overview of the literature")
  Member "the bibliometric properties of article readership information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "readership data and research impact")

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.DL(Digital Libraries)