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: "growing wikipedia across languages via recommendation"
  Abstract: The different Wikipedia language editions vary dramatically in how comprehensive they are. As a result, most language editions contain only a small fraction of the sum of information that exists across all Wikipedias. In this paper, we present an approach to filling gaps in article coverage across different Wikipedia editions. Our main contribution is an end-to-end system for recommending articles for creation that exist in one language but are missing in another. The system involves identifying missing articles, ranking the missing articles according to their importance, and recommending important missing articles to editors based on their interests. We empirically validate our models in a controlled experiment involving 12,000 French Wikipedia editors. We find that personalizing recommendations increases editor engagement by a factor of two. Moreover, recommending articles increases their chance of being created by a factor of 3.2. Finally, articles created as a result of our recommendations are of comparable quality to organically created articles. Overall, our system leads to more engaged editors and faster growth of Wikipedia with no effect on its quality.

Connected through hyperedge HE-1 (induced by source paper "quantifying engagement with citations on wikipedia"):
  with members:
    - "citation needed a taxonomy and algorithmic assessment of wikipedia s verifiability"
    - "mapping the backbone of the humanities through the eyes of wikipedia"
    - "detecting and gauging impact on wikipedia page views"
    - "eliciting new wikipedia users interests via automatically mined questionnaires for a warm welcome not a cold start"
    - "why the world reads wikipedia beyond english speakers"
    - "structuring wikipedia articles with section recommendations"
    - "amplifying the impact of open access wikipedia and the diffusion of science"
    - "why we read wikipedia"

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"
    - "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"
    - "pagerank standing on the shoulders of giants"

Connected through hyperedge HE-3 (induced by source paper "missing movie synergistic completion across multiple isomeric online movie knowledge libraries"):
  with members:
    - "data driven blockbuster planning on online movie knowledge library"
    - "multilinguals and wikipedia editing"
    - "multiple location profiling for users and relationships from social network and content"
    - "almost stable matchings by truncating the gale shapley algorithm"

Connected through hyperedge HE-4 (induced by source paper "eliciting new wikipedia users interests via automatically mined questionnaires for a warm welcome not a cold start"):
  with members:
    - "structuring wikipedia articles with section recommendations"
    - "efficient estimation of word representations in vector space"
    - "content based book recommending using learning for text categorization"

Connected through hyperedge HE-5 (induced by source paper "non parametric class completeness estimators for collaborative knowledge graphs the case of wikidata"):
  with members:
    - "predicting completeness in knowledge bases"

Connected through hyperedge HE-6 (induced by source paper "structuring wikipedia articles with section recommendations"):
  with members:
    - "improving website hyperlink structure using server logs"

Connected through hyperedge HE-7 (induced by source paper "multiwiki interlingual text passage alignment in wikipedia"):
  with members:
    - "analysing temporal evolution of interlingual wikipedia article pairs"
    - "multilingual open relation extraction using cross lingual projection"
    - "multilinguals and wikipedia editing"
    - "the jrc acquis a multilingual aligned parallel corpus with 20 languages"

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.SI(Social and Information Networks)