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: "design patterns for fusion based object retrieval"
  Abstract: We address the task of ranking objects (such as people, blogs, or verticals) that, unlike documents, do not have direct term-based representations. To be able to match them against keyword queries, evidence needs to be amassed from documents that are associated with the given object. We present two design patterns, i.e., general reusable retrieval strategies, which are able to encompass most existing approaches from the past. One strategy combines evidence on the term level (early fusion), while the other does it on the document level (late fusion). We demonstrate the generality of these patterns by applying them to three different object retrieval tasks: expert finding, blog distillation, and vertical ranking.

Connected through hyperedge HE-1 (induced by source paper "web table extraction retrieval and augmentation a survey"):
  with members:
    - "auto completion for data cells in relational tables"
    - "recommending related tables"
    - "tablenet an approach for determining fine grained relations for wikipedia tables"
    - "table2vec neural word and entity embeddings for table population and retrieval"
    - "generating titles for web tables"
    - "ad hoc table retrieval using semantic similarity"
    - "on the fly table generation"
    - "entitables smart assistance for entity focused tables"

Connected through hyperedge HE-2 (induced by source paper "table2vec neural word and entity embeddings for table population and retrieval"):
  with members:
    - "tabvec table vectors for classification of web tables"
    - "ad hoc table retrieval using semantic similarity"
    - "on the fly table generation"
    - "entitables smart assistance for entity focused tables"
    - "distributed representations of words and phrases and their compositionality"
    - "answering table queries on the web using column keywords"

Connected through hyperedge HE-3 (induced by source paper "ad hoc table retrieval using semantic similarity"):
  with members:
    - "entitables smart assistance for entity focused tables"
    - "word entity duet representations for document ranking"
    - "scientific table search using keyword queries"
    - "modelling user preferences using word embeddings for context aware venue recommendation"
    - "a dual embedding space model for document ranking"
    - "neural enquirer learning to query tables with natural language"
    - "line large scale information network embedding"
    - "deepwalk online learning of social representations"

Connected through hyperedge HE-4 (induced by source paper "on the fly table generation"):
  with members:
    - "ad hoc table retrieval using semantic similarity"
    - "smarttable a spreadsheet program with intelligent assistance"
    - "entitables smart assistance for entity focused tables"
    - "relink a research framework and test collection for entity relationship retrieval"
    - "matchzoo a toolkit for deep text matching"
    - "a deep relevance matching model for ad hoc retrieval"
    - "neural enquirer learning to query tables with natural language"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-5 (induced by source paper "early fusion strategy for entity relationship retrieval"):
  with members:
    - "relink a research framework and test collection for entity relationship retrieval"
    - "timemachine entity centric search and visualization of news archives"

Connected through hyperedge HE-6 (induced by source paper "target type identification for entity bearing queries"):
  with members:
    - "learning joint query interpretation and response ranking"

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)