human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "polisis automated analysis and presentation of privacy policies using deep learning"):
  Abstract: Privacy policies are the primary channel through which companies inform users about their data collection and sharing practices. In their current form, policies remain long and difficult to comprehend, thus merely serving the goal of legally protecting the companies. Short notices based on information extracted from privacy policies have been shown to be useful and more usable, but face a significant scalability hurdle, given the number of policies and their evolution over time. Companies, users, researchers, and regulators still lack usable and scalable tools to cope with the breadth and depth of privacy policies. To address these hurdles, we propose Polisis, an automated framework for privacy Policies analysis. It enables scalable, dynamic, and multi-dimensional queries on privacy policies. At the core of Polisis is a privacy-centric language model, built with 130K privacy policies, and a novel hierarchy of neural network classifiers that caters to the high-level aspects and the fine-grained details of privacy practices. We demonstrate Polisis's modularity and utility with two robust applications that support structured and free-form querying. The structured querying application is the automated assignment of privacy icons from the privacy policies. With Polisis, we can achieve an accuracy of 88.4% on this task, when evaluated against earlier annotations by a group of three legal experts. The second application is PriBot, the first free-form Question Answering about Privacy policies. We show that PriBot can produce a correct answer among its top-3 results for 82% of the test questions.

Includes members:
  Member "modeling language vagueness in privacy policies using deep neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "automatic detection of vague words and sentences in privacy policies")
  Member "enriching word vectors with subword information":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "applying deep learning to answer selection a study and an open task":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "hybrid tiled convolutional neural networks for text sentiment classification")
  Member "visual instance retrieval with deep convolutional networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deeply activated salient region for instance search")

Question: Please tell me which class the source paper 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.CL(Computation and Language)