id: 06094973
dt: a
an: 06094973
au: Zhang, Chenjing; Chang, Le; Sha, Chaofeng; Wang, Xiaoling; Zhou, Aoying
ti: Keywords filtering over probabilistic XML data.
so: Sheng, Quan Z. (ed.) et al., Web technologies and applications. 14th
    Asia-Pacific web conference, APWeb 2012, Kunming, China, April 11‒13,
    2012. Proceedings. Berlin: Springer (ISBN 978-3-642-29252-1/pbk).
    Lecture Notes in Computer Science 7235, 183-194 (2012).
py: 2012
pu: Berlin: Springer
la: EN
cc: 
ut: probabilistic XML; keywords filtering; SLCA
ci: 
li: doi:10.1007/978-3-642-29253-8_16
ab: Summary: Probabilistic XML data is widely used in many web applications.
    Recent work has been mostly focused on structured query over
    probabilistic XML data. A few of work has been done about keyword
    query. However only the independent and the mutually-exclusive
    relationship among sibling nodes are discussed. This paper addresses
    the problem of keyword filtering over probabilistic XML data, and we
    propose PrXML$^{\mathrm{exp, ind, mux}}$ model to represent a more
    general relationship among XML sibling nodes, for keywords filtering
    over probabilistic XML data. $kdptab$ is defined as keyword
    distribution probability table of one subtree. The Dot product,
    Cartesian product, and addition operation of kdptab are also defined.
    In PrXML$^{\mathrm{exp, ind, mux}}$ model, XML document is scanned
    bottom-up and achieve keyword filtering based on SLCA semantics
    efficiently in our method. Finally, the features and efficiency of our
    method are evaluated with extensive experimental results.
rv: