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: "pagerank standing on the shoulders of giants"
  Abstract: PageRank is a Web page ranking technique that has been a fundamental ingredient in the development and success of the Google search engine. The method is still one of the many signals that Google uses to determine which pages are most important. The main idea behind PageRank is to determine the importance of a Web page in terms of the importance assigned to the pages hyperlinking to it. In fact, this thesis is not new, and has been previously successfully exploited in different contexts. We review the PageRank method and link it to some renowned previous techniques that we have found in the fields of Web information retrieval, bibliometrics, sociometry, and econometrics.

Connected through hyperedge HE-1 (induced by source paper "trust evaluation mechanism for user recruitment in mobile crowd sensing in the internet of things"):
  with members:
    - "social network assisted worker recruitment in mobile crowd sensing"
    - "quality of information in mobile crowdsensing survey and research challenges"
    - "when crowdsourcing meets mobile sensing a social network perspective"
    - "mobile crowd sensing and computing when participatory sensing meets participatory social media"
    - "from participatory sensing to mobile crowd sensing"
    - "sensing as a service model for smart cities supported by internet of things"
    - "internet of things iot a vision architectural elements and future directions"
    - "supervised random walks predicting and recommending links in social networks"

Connected through hyperedge HE-2 (induced by source paper "wikilinkgraphs a complete longitudinal and multi language dataset of the wikipedia link networks"):
  with members:
    - "benchmarking distributed stream processing engines"
    - "growing wikipedia across languages via recommendation"
    - "mining missing hyperlinks from human navigation traces a case study of wikipedia"
    - "societal controversies in wikipedia articles"
    - "interactions of cultures and top people of wikipedia from ranking of 24 language editions"
    - "biographical social networks on wikipedia a cross cultural study of links that made history"
    - "ranking of wikipedia articles in search engines revisited fair ranking for reasonable quality"

Connected through hyperedge HE-3 (induced by source paper "early identification of important patents design and validation of citation network metrics"):
  with members:
    - "recognition of emerging technology trends class selective study of citations in the u s patent citation network"
    - "citation algorithms for identifying research milestones driving biomedical innovation"
    - "a review of the literature on citation impact indicators"
    - "pagerank beyond the web"

Connected through hyperedge HE-4 (induced by source paper "two hop walks indicate pagerank order"):
  with members:
    - "black hole metric overcoming the pagerank normalization problem"
    - "spectral properties of the google matrix of the world wide web and other directed networks"
    - "delocalization transition for the google matrix"

Connected through hyperedge HE-5 (induced by source paper "striations in pagerank ordered matrices"):
  with members:
    - "subgraph frequencies mapping the empirical and extremal geography of large graph collections"
    - "defining and evaluating network communities based on ground truth"

Connected through hyperedge HE-6 (induced by source paper "a theory on power in networks"):
  with members:
    - "vulnerability and power on networks"
    - "bargaining dynamics in exchange networks"

Connected through hyperedge HE-7 (induced by source paper "best of both worlds simultaneous evaluation of researchers and their works"):
  with members:
    - "citex a new citation index to measure the relative importance of authors and papers in scientific publications"

Connected through hyperedge HE-8 (induced by source paper "network driven reputation in online scientific communities"):
  with members:
    - "quantifying long term scientific impact"
    - "quantifying the influence of scientists and their publications distinguishing between prestige and popularity"

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.IR(Information Retrieval)