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 "i humo an interactive human and machine cooperation framework for entity resolution with quality guarantees"):
  Abstract: Even though many approaches have been proposed for entity resolution (ER), it remains very challenging to find one with quality guarantees. To this end, we propose an interactive HUman and Machine cOoperation framework for ER, denoted by i-HUMO. Similar to the existing HUMO framework, i-HUMO enforces both precision and recall levels by dividing an ER workload between the human and the machine. It essentially makes the machine label easy instances while assigning more challenging instances to the human. However, i-HUMO is a major improvement over HUMO in that it is interactive: its process of human workload selection is optimized based on real-time risk analysis on human-labeled results as well as pre-specified machine metrics. In this paper, we first introduce the i-HUMO framework and then present the risk analysis technique to prioritize the instances for manual labeling. Finally, we empirically evaluate i-HUMO's performance on real data. Our extensive experiments show that i-HUMO is effective in enforcing quality guarantees, and compared with the state-of-the-art alternatives, it can achieve better quality control with reduced human cost.

Includes members:
  Member "enabling quality control for entity resolution a human and machine cooperative framework":
    also connected through other hyperedges:
      (none)
  Member "sigma simple greedy matching for aligning large knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a benchmarking study of embedding based entity alignment for knowledge graphs")
  Member "crowder crowdsourcing entity resolution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "crowdsourced collective entity resolution with relational match propagation")

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.HC(Human-Computer Interaction)