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: "carbon dating the web estimating the age of web resources"
  Abstract: In the course of web research it is often necessary to estimate the creation datetime for web resources (in the general case, this value can only be estimated). While it is feasible to manually establish likely datetime values for small numbers of resources, this becomes infeasible if the collection is large. We present "carbon date", a simple web application that estimates the creation date for a URI by polling a number of sources of evidence and returning a machine-readable structure with their respective values. To establish a likely datetime, we poll bitly for the first time someone shortened the URI, topsy for the first time someone tweeted the URI, a Memento aggregator for the first time it appeared in a public web archive, Google's time of last crawl, and the Last-Modified HTTP response header of the resource itself. We also examine the backlinks of the URI as reported by Google and apply the same techniques for the resources that link to the URI. We evaluated our tool on a gold-standard data set of 1200 URIs in which the creation date was manually verified. We were able to estimate a creation date for 75.90% of the resources, with 32.78% having the correct value. Given the different nature of the URIs, the union of the various methods produces the best results. While the Google last crawl date and topsy account for nearly 66% of the closest answers, eliminating the web archives or Last-Modified from the results produces the largest overall negative impact on the results. The carbon date application is available for download or use via a webAPI.

Connected through hyperedge HE-1 (induced by source paper "using micro collections in social media to generate seeds for web archive collections"):
  with members:
    - "focused crawl of web archives to build event collections"
    - "scraping serps for archival seeds it matters when you start"
    - "extracting event centric document collections from large scale web archives"
    - "analyzing web archives through topic and event focused sub collections"
    - "losing my revolution how many resources shared on social media have been lost"

Connected through hyperedge HE-2 (induced by source paper "focused crawl of web archives to build event collections"):
  with members:
    - "scraping serps for archival seeds it matters when you start"
    - "extracting event centric document collections from large scale web archives"
    - "routing memento requests using binary classifiers"
    - "icrawl improving the freshness of web collections by integrating social web and focused web crawling"
    - "evaluating sliding and sticky target policies by measuring temporal drift in acyclic walks through a web archive"

Connected through hyperedge HE-3 (induced by source paper "who and what links to the internet archive"):
  with members:
    - "access patterns for robots and humans in web archives"
    - "profiling web archive coverage for top level domain and content language"
    - "how much of the web is archived"
    - "analyzing the persistence of referenced web resources with memento"
    - "memento time travel for the web"

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)