TY  - CONF
ID  - www2009103
UR  - http://www2009.eprints.org/103/
A1  - Meng, Xiangfu
A1  - Ma, Z. M.
A1  - Yan, Li
Y1  - 2009/04//
N2  - To deal with the problem of empty or too little answers returned
from a Web database in response to a user query, this paper
proposes a novel approach to provide relevant and ranked query
results. Based on the user original query, we speculate how much
the user cares about each specified attribute and assign a
corresponding weight to it. This original query is then rewritten as
an approximate query by relaxing the query criteria range. The
relaxation order of all specified attributes and the relaxed degree
on each specified attribute are varied with the attribute weights.
For the approximate query results, we generate users? contextual
preferences from database workload and use them to create a
priori orders of tuples in an off-line preprocessing step. Only a
few representative orders are saved, each corresponding to a set of
contexts. Then, these orders and associated contexts are used at
query time to expeditiously provide ranked answers. Results of a
preliminary user study demonstrate that our query relaxation and
results ranking methods can capture the user?s preferences
effectively. The efficiency and effectiveness of our approach is
also demonstrated by experimental result.

TI  - Answering Approximate Queries over Autonomous Web Databases
SP  - 1021
M2  - Madrid, Spain
AV  - public
EP  - 1021
T2  - 18th International World Wide Web Conference
ER  -