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: "pyndri a python interface to the indri search engine"
  Abstract: We introduce pyndri, a Python interface to the Indri search engine. Pyndri allows to access Indri indexes from Python at two levels: (1) dictionary and tokenized document collection, (2) evaluating queries on the index. We hope that with the release of pyndri, we will stimulate reproducible, open and fast-paced IR research.

Connected through hyperedge HE-1 (induced by source paper "macaw an extensible conversational information seeking platform"):
  with members:
    - "asking clarifying questions in open domain information seeking conversations"
    - "towards deep conversational recommendations"
    - "coqa a conversational question answering challenge"
    - "joint modeling and optimization of search and recommendation"
    - "conversational recommender system"
    - "quac question answering in context"
    - "reading wikipedia to answer open domain questions"

Connected through hyperedge HE-2 (induced by source paper "neural vector spaces for unsupervised information retrieval"):
  with members:
    - "neural networks for information retrieval"
    - "semantic entity retrieval toolkit"
    - "efficient vector representation for documents through corruption"
    - "reply with proactive recommendation of email attachments"
    - "a deep relevance matching model for ad hoc retrieval"
    - "learning to match using local and distributed representations of text for web search"
    - "noisy activation functions"
    - "siamese cbow optimizing word embeddings for sentence representations"

Connected through hyperedge HE-3 (induced by source paper "ilps at trec 2017 common core track"):
  with members:
    - "neural vector spaces for unsupervised information retrieval"
    - "learning latent vector spaces for product search"

Connected through hyperedge HE-4 (induced by source paper "luandri a clean lua interface to the indri search engine"):
  with members:
    - "a knowledge grounded neural conversation model"
    - "a deep relevance matching model for ad hoc retrieval"
    - "query expansion with locally trained word embeddings"
    - "learning to match using local and distributed representations of text for web search"
    - "text matching as image recognition"
    - "multimodal convolutional neural networks for matching image and sentence"
    - "tensorflow large scale machine learning on heterogeneous distributed systems"
    - "convolutional neural network architectures for matching natural language sentences"

Connected through hyperedge HE-5 (induced by source paper "remedies against the vocabulary gap in information retrieval"):
  with members:
    - "neural vector spaces for unsupervised information retrieval"
    - "semantic entity retrieval toolkit"
    - "reply with proactive recommendation of email attachments"
    - "unsupervised efficient and semantic expertise retrieval"
    - "recurrent memory network for language modeling"
    - "learning latent vector spaces for product search"
    - "adadelta an adaptive learning rate method"
    - "the numpy array a structure for efficient numerical computation"

Connected through hyperedge HE-6 (induced by source paper "semantic entity retrieval toolkit"):
  with members:
    - "unsupervised efficient and semantic expertise retrieval"
    - "learning latent vector spaces for product search"
    - "off the beaten path let s replace term based retrieval with k nn search"

Connected through hyperedge HE-7 (induced by source paper "reply with proactive recommendation of email attachments"):
  with members:
    - "anticipating information needs based on check in activity"
    - "smart reply automated response suggestion for email"
    - "adam a method for stochastic optimization"

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)