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 "data requirements for evaluation of personalization of information retrieval a position paper"):
  Abstract: Two key, but usually ignored, issues for the evaluation of methods of personalization for information retrieval are: that such evaluation must be of a search session as a whole; and, that people, during the course of an information search session, engage in a variety of activities, intended to accomplish differ- ent goals or intentions. Taking serious account of these factors has major impli- cations for not only evaluation methods and metrics, but also for the nature of the data that is necessary both for understanding and modeling information search, and for evaluation of personalized support for information retrieval (IR). In this position paper, we: present a model of IR demonstrating why these fac- tors are important; identify some implications of accepting their validity; and, on the basis of a series of studies in interactive IR, identify some types of data concerning searcher and system behavior that we claim are, at least, necessary, if not necessarily sufficient, for meaningful evaluation of personalization of IR.

Includes members:
  Member "a complete year of user retrieval sessions in a social sciences academic search engine":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "analysis of search stratagem utilisation")
  Member "a usefulness based approach for measuring the local and global effect of iir services":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a digital library for research data and related information in the social sciences")

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)