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: "multidimensional social network in the social recommender system"
  Abstract: All online sharing systems gather data that reflects users' collective behavior and their shared activities. This data can be used to extract different kinds of relationships which can be grouped into layers and which are basic components of the multidimensional social network (MSN) proposed in the paper. The layers are created on the basis of two types of relations between humans, i.e., direct and object-based ones which, respectively, correspond to either social or semantic links between individuals. For better understanding of the complexity of the social network structure, layers and their profiles were identified and studied on two, spanned in time, snapshots of the `Flickr' population. Additionally, for each layer, a separate strength measure was proposed. The experiments on the `Flickr' photo sharing system revealed that the relationships between users result either from semantic links between objects they operate on or from social connections of these users. Moreover, the density of the social network increases in time. The second part of this paper is devoted to building a social recommender system that supports the creation of new relations between users in a multimedia sharing system. Its main goal is to generate personalized suggestions that are continuously adapted to users' needs depending on the personal weights assigned to each layer in the MSN. The conducted experiments confirmed the usefulness of the proposed model.

Connected through hyperedge HE-1 (induced by source paper "mobile big data analysis with machine learning"):
  with members:
    - "decorrelation of neutral vector variables theory and applications"
    - "distributed optimization using the primal dual method of multipliers"
    - "cross modal subspace learning for fine grained sketch based image retrieval"
    - "adversarial network bottleneck features for noise robust speaker verification"
    - "the role of data analysis in the development of intelligent energy networks"
    - "big data caching for networking moving from cloud to edge"
    - "mobile big data analytics using deep learning and apache spark"
    - "soft defined heterogeneous vehicular network architecture and challenges"

Connected through hyperedge HE-2 (induced by source paper "analysis of a heterogeneous social network of humans and cultural objects"):
  with members:
    - "people are strange when you re a stranger impact and influence of bots on social networks"
    - "the digital evolution of occupy wall street"
    - "the geospatial characteristics of a social movement communication network"
    - "analyzing user behavior across social sharing environments"
    - "is the sample good enough comparing data from twitter s streaming api with twitter s firehose"
    - "a large scale community structure analysis in facebook"
    - "topological features of online social networks"
    - "crawling facebook for social network analysis purposes"

Connected through hyperedge HE-3 (induced by source paper "extraction of multilayered social networks from activity data"):
  with members:
    - "exploiting all phone media a multidimensional network analysis of phone users sociality"
    - "multi layered social networks"
    - "analysis of neighbourhoods in multi layered dynamic social networks"
    - "low distortion inference of latent similarities from a multiplex social network"
    - "a degree centrality in multi layered social network"
    - "a classification for community discovery methods in complex networks"
    - "shortest path discovery in the multi layered social network"
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-4 (induced by source paper "ged the method for group evolution discovery in social networks"):
  with members:
    - "group evolution discovery in social networks"
    - "tracking group evolution in social networks"
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-5 (induced by source paper "group evolution discovery in social networks"):
  with members:
    - "social networks that matter twitter under the microscope"

Connected through hyperedge HE-6 (induced by source paper "analysis of neighbourhoods in multi layered dynamic social networks"):
  with members:
    - "a degree centrality in multi layered social network"
    - "shortest path discovery in the multi layered social network"
    - "exposing multi relational networks to single relational network analysis algorithms"
    - "social networks that matter twitter under the microscope"
    - "a multi relational network to support the scholarly communication process"

Connected through hyperedge HE-7 (induced by source paper "multi stratum networks toward a unified model of on line identities"):
  with members:
    - "one none and one hundred thousand profiles re imagining the pirandellian identity dilemma in the era of online social networks"

Connected through hyperedge HE-8 (induced by source paper "shortest path discovery in the multi layered social network"):
  with members:
    - "social networks that matter twitter under the microscope"

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)