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 "report on the sigir 2019 workshop on ecommerce ecom19"):
  Abstract: The SIGIR 2019 Workshop on eCommerce (ECOM19), was a full day workshop that took place on Thursday, July 25, 2019 in Paris, France. The purpose of the workshop was to serve as a platform for publication and discussion of Information Retrieval and NLP research and their applications in the domain of eCommerce. The workshop program was designed to bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to product search and recommendation in the eCommerce domain. A second goal was to run a data challenge on real-world eCommerce data. The workshop drew contributions from both industry as well as academia, in total the workshop received 38 submissions, and accepted 24 (63%). There were two keynotes by invited speakers, a poster session where all the accepted submissions were presented, a panel discussion, and three short talks by invited speakers.

Includes members:
  Member "an empirical comparison of faiss and fenshses for nearest neighbor search in hamming space":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fast and exact nearest neighbor search in hamming space on full text search engines")
  Member "production ranking systems a review":
    also connected through other hyperedges:
      (none)
  Member "personalized query auto completion through a lightweight representation of the user context":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an image is worth a thousand features scalable product representations for in session type ahead personalization")
  Member "ranking sentences from product description bullets for better search":
    also connected through other hyperedges:
      (none)
  Member "leverage implicit feedback for context aware product search":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explainable product search with a dynamic relation embedding model")
  Member "spelling correction as a foreign language":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "github typo corpus a large scale multilingual dataset of misspellings and grammatical errors")

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.IR(Information Retrieval)