Gqfast: Fast Graph Exploration With Context-Aware Autocompletion
2017 IEEE 33RD INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE 2017)(2017)
摘要
There is an increasing demand to explore similar entities in big graphs. For example, in domains like biomedical science, identifying similar entities may contribute to developing new drugs or discovering new diseases. In this paper, we demonstrate a graph exploration system, called GQFast, which provides a graphical interface to help users efficiently explore similar entities. Methodologically, GQFast first builds efficient indices combining column database optimizations and compression techniques, then it explores similar entities by using the indices. GQFast operates on the real-world Pubmed dataset consisting of over 23 million biomedical entities and 1.3 billion relationships. Relying on GQFast's high performance, GQFast provides (i) type-ahead-search to instantly visualize search results while a user is typing a query; and (ii) context-aware query completion to guide users typing queries.Video: https://youtu.be/UtiKg9WcbK0
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关键词
GQFast system,fast graph exploration,context-aware autocompletion,graphical interface,column database optimizations,compression techniques,Pubmed dataset,type-ahead-search,context-aware query completion
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