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: "hetesim a general framework for relevance measure in heterogeneous networks"
  Abstract: Similarity search is an important function in many applications, which usually focuses on measuring the similarity between objects with the same type. However, in many scenarios, we need to measure the relatedness between objects with different types. With the surge of study on heterogeneous networks, the relevance measure on objects with different types becomes increasingly important. In this paper, we study the relevance search problem in heterogeneous networks, where the task is to measure the relatedness of heterogeneous objects (including objects with the same type or different types). A novel measure HeteSim is proposed, which has the following attributes: (1) a uniform measure: it can measure the relatedness of objects with the same or different types in a uniform framework; (2) a path-constrained measure: the relatedness of object pairs are defined based on the search path that connect two objects through following a sequence of node types; (3) a semi-metric measure: HeteSim has some good properties (e.g., self-maximum and symmetric), that are crucial to many data mining tasks. Moreover, we analyze the computation characteristics of HeteSim and propose the corresponding quick computation strategies. Empirical studies show that HeteSim can effectively and efficiently evaluate the relatedness of heterogeneous objects.

Connected through hyperedge HE-1 (induced by source paper "deep collaborative filtering with multi aspect information in heterogeneous networks"):
  with members:
    - "prsim sublinear time simrank computation on large power law graphs"
    - "deep learning based recommender system a survey and new perspectives"
    - "outer product based neural collaborative filtering"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "neural brane neural bayesian personalized ranking for attributed network embedding"
    - "neural factorization machines for sparse predictive analytics"
    - "attention is all you need"
    - "neural collaborative filtering"

Connected through hyperedge HE-2 (induced by source paper "hetespaceywalk a heterogeneous spacey random walk for heterogeneous information network embedding"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "metagraph2vec complex semantic path augmented heterogeneous network embedding"
    - "easing embedding learning by comprehensive transcription of heterogeneous information networks"
    - "carl content aware representation learning for heterogeneous networks"
    - "joint embedding of meta path and meta graph for heterogeneous information networks"
    - "the spacey random walk a stochastic process for higher order data"
    - "heterogeneous information network embedding for recommendation"
    - "a comprehensive survey of graph embedding problems techniques and applications"

Connected through hyperedge HE-3 (induced by source paper "relation structure aware heterogeneous information network embedding"):
  with members:
    - "struc2vec learning node representations from structural identity"
    - "a survey on network embedding"
    - "heterogeneous information network embedding for recommendation"
    - "a comprehensive survey of graph embedding problems techniques and applications"
    - "bl mne emerging heterogeneous social network embedding through broad learning with aligned autoencoder"
    - "meta path guided embedding for similarity search in large scale heterogeneous information networks"
    - "node2vec scalable feature learning for networks"
    - "a survey of heterogeneous information network analysis"

Connected through hyperedge HE-4 (induced by source paper "content based news recommendation via shortest entity distance over knowledge graphs"):
  with members:
    - "neural networks models for entity discovery and linking"
    - "an empirical evaluation of doc2vec with practical insights into document embedding generation"
    - "distributed representations of sentences and documents"
    - "personalized news recommendation with context trees"

Connected through hyperedge HE-5 (induced by source paper "link weights recovery in heterogeneous information networks"):
  with members:
    - "recurrent meta structure for robust similarity measure in heterogeneous information networks"
    - "stream graphs and link streams for the modeling of interactions over time"
    - "a survey of heterogeneous information network analysis"

Connected through hyperedge HE-6 (induced by source paper "learning with heterogeneous side information fusion for recommender systems"):
  with members:
    - "taking human out of learning applications a survey on automated machine learning"
    - "heteromed heterogeneous information network for medical diagnosis"
    - "collaborative filtering with social local models"
    - "heterogeneous information network embedding for recommendation"
    - "wide deep learning for recommender systems"
    - "ups and downs modeling the visual evolution of fashion trends with one class collaborative filtering"
    - "fast low rank matrix learning with nonconvex regularization"
    - "a survey of heterogeneous information network analysis"

Connected through hyperedge HE-7 (induced by source paper "collective classification of spam campaigners on twitter a hierarchical meta path based approach"):
  with members:
    - "poised spotting twitter spam off the beaten paths"
    - "dial one for scam a large scale analysis of technical support scams"
    - "botornot a system to evaluate social bots"
    - "detecting smart spammers on social network a topic model approach"
    - "the rise of social bots"
    - "towards detecting compromised accounts on social networks"
    - "detecting criminal organizations in mobile phone networks"
    - "meta path based collective classification in heterogeneous information networks"

Connected through hyperedge HE-8 (induced by source paper "a semantic rich similarity measure in heterogeneous information networks"):
  with members:
    - "forward backward similarity search in knowledge networks"
    - "a survey of heterogeneous information network analysis"
    - "relation strength aware clustering of heterogeneous information networks with incomplete attributes"

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)