TY - CONF
T1 - VOGUE
T2 - 6th Biennial Conference on Innovative Data Systems Research, CIDR 2013
AU - Bhowmick, Sourav S.
AU - Choi, Koon Kau
AU - Zhou, Shuigeng
N1 - Funding Information:
for a framework to support comprehensive empirical study of vogue. In contrast to traditional paradigm, each query in vogue must be formulated by a set of real users for empirical study. Furthermore, each query can follow many different query formulation sequences. The challenge here is that it is prohibitively expensive to find and engage a large number of users who are willing to formulate a large number of visual queries. In fact, our experience suggests that such aspiration strongly deters end users to participate in the empirical study. To address this limitation, we are currently building a synthetic visual query simulator that simulates visual graph query formulation by real users. A key feature of this simulator is that it leverages principles from hci on visual task completion to simulate users’ interaction behaviors. It is then integrated with the vogue architecture to simulate our proposed paradigm of blending query formulation and query processing. Acknowledgement: Shuigeng Zhou was supported by the Research Innovation Program of Shanghai Municipal Education Committee under grant No. 13ZZ003. We would also like to thank Changjiu Jin for implementing several features of vogue.
PY - 2013/1
Y1 - 2013/1
N2 - Due to the complexity of graph query languages, the need for visual query interfaces that can reduce the burden of query formulation is fundamental to the spreading of graph data management tools to wider community. We present a novel hci (human-computer interaction)-aware graph query processing paradigm, where instead of processing a query graph after its construction, it interleaves visual query construction and processing to improve system response time. We present the architecture of a system called vogue that exploits gui latency to prune false results and prefetch candidate data graphs by employing a novel action-aware indexing and query processing schemes. We discuss various non-traditional design challenges and innovative features of vogue and highlight its practicality in evaluating subgraph queries.
AB - Due to the complexity of graph query languages, the need for visual query interfaces that can reduce the burden of query formulation is fundamental to the spreading of graph data management tools to wider community. We present a novel hci (human-computer interaction)-aware graph query processing paradigm, where instead of processing a query graph after its construction, it interleaves visual query construction and processing to improve system response time. We present the architecture of a system called vogue that exploits gui latency to prune false results and prefetch candidate data graphs by employing a novel action-aware indexing and query processing schemes. We discuss various non-traditional design challenges and innovative features of vogue and highlight its practicality in evaluating subgraph queries.
UR - http://www.scopus.com/inward/record.url?scp=85084014819&partnerID=8YFLogxK
M3 - Conference paper
AN - SCOPUS:85084014819
SP - 1
EP - 10
Y2 - 6 January 2013 through 9 January 2013
ER -