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: "the tagrec framework as a toolkit for the development of tag based recommender systems"
  Abstract: Recommender systems have become important tools to support users in identifying relevant content in an overloaded information space. To ease the development of recommender systems, a number of recommender frameworks have been proposed that serve a wide range of application domains. Our TagRec framework is one of the few examples of an open-source framework tailored towards developing and evaluating tag-based recommender systems. In this paper, we present the current, updated state of TagRec, and we summarize and reflect on four use cases that have been implemented with TagRec: (i) tag recommendations, (ii) resource recommendations, (iii) recommendation evaluation, and (iv) hashtag recommendations. To date, TagRec served the development and/or evaluation process of tag-based recommender systems in two large scale European research projects, which have been described in 17 research papers. Thus, we believe that this work is of interest for both researchers and practitioners of tag-based recommender systems.

Connected through hyperedge HE-1 (induced by source paper "evaluating tag recommendations for e book annotation using a semantic similarity metric"):
  with members:
    - "distributed representations of sentences and documents"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-2 (induced by source paper "overcoming the imbalance between tag recommendation approaches and real world folksonomy structures with cognitive inspired algorithms"):
  with members:
    - "modeling cognitive processes in social tagging to improve tag recommendations"
    - "temporal effects on hashtag reuse in twitter a cognitive inspired hashtag recommendation approach"
    - "utilizing online social network and location based data to recommend products and categories in online marketplaces"
    - "forgetting the words but remembering the meaning modeling forgetting in a verbal and semantic tag recommender"
    - "recommending items in social tagging systems using tag and time information"
    - "semantic stability in social tagging streams"

Connected through hyperedge HE-3 (induced by source paper "modeling activation processes in human memory to improve tag recommendations"):
  with members:
    - "modeling cognitive processes in social tagging to improve tag recommendations"
    - "utilizing online social network and location based data to recommend products and categories in online marketplaces"
    - "forgetting the words but remembering the meaning modeling forgetting in a verbal and semantic tag recommender"
    - "socrecm a scalable social recommender engine for online marketplaces"
    - "recommending items in social tagging systems using tag and time information"
    - "long time no see the probability of reusing tags as a function of frequency and recency"

Connected through hyperedge HE-4 (induced by source paper "studying confirmation bias in hashtag usage on twitter"):
  with members:
    - "temporal effects on hashtag reuse in twitter a cognitive inspired hashtag recommendation approach"
    - "the bursty dynamics of the twitter information network"

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)