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: "timemachine entity centric search and visualization of news archives"
  Abstract: We present a dynamic web tool that allows interactive search and visualization of large news archives using an entity-centric approach. Users are able to search entities using keyword phrases expressing news stories or events and the system retrieves the most relevant entities to the user query based on automatically extracted and indexed entity profiles. From the computational journalism perspective, TimeMachine allows users to explore media content through time using automatic identification of entity names, jobs, quotations and relations between entities from co-occurrences networks extracted from the news articles. TimeMachine demo is available at this http URL

Connected through hyperedge HE-1 (induced by source paper "early fusion strategy for entity relationship retrieval"):
  with members:
    - "relink a research framework and test collection for entity relationship retrieval"
    - "design patterns for fusion based object retrieval"

Connected through hyperedge HE-2 (induced by source paper "learning from the news predicting entity popularity on twitter"):
  with members:
    - "breaking the news first impressions matter on online news"
    - "popmine tracking political opinion on the web"
    - "characterizing the life cycle of online news stories using social media reactions"
    - "the pulse of news in social media forecasting popularity"
    - "dynamical classes of collective attention in twitter"

Connected through hyperedge HE-3 (induced by source paper "sentiment aggregate functions for political opinion polling using microblog streams"):
  with members:
    - "popmine tracking political opinion on the web"
    - "a meta analysis of state of the art electoral prediction from twitter data"
    - "i wanted to predict elections with twitter and all i got was this lousy paper a balanced survey on election prediction using twitter data"

Connected through hyperedge HE-4 (induced by source paper "sentibubbles topic modeling and sentiment visualization of entity centric tweets"):
  with members:
    - "popmine tracking political opinion on the web"

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)