Download Efficient Data Minin..

ABSTRACT
we
describe
association
an
approach
rules(tars)
mined
based
rules,
on
tree-based
which
provide
approximate, intensional information on both the structure
and the contents of xml documents and can be stored in
xml format as well. There are two main approaches to xml
document
access:
keyword-based
search
and
query-
answering. The idea of mining association rules to provide
summarized representations of xml documents has been
investigated in many proposals either by using languages
xquery, jquery etc., and techniques developed in the xml
context or by implementing graph-or-tree-based algorithms.
in this paper, we introduce a proposal for mining and
storing tars (tree-based association rules) as a means to
represent intensional knowledge in native xml.
Modules:
Data storage and search:
we describe an approach based on tree-based association
rules(tars)
mined
rules,
which
provide
approximate,
intensional information on both the structure and the
contents of xml documents and can be stored in xml format
as well. There are two main approaches to xml document
access: keyword-based search and query-answering. the
idea of mining association rules to provide summarized
representations of xml documents has been investigated in
many proposals either by using languages xquery.
file organization blacks
We do not store the data in a single file because, in hadoop
and mapreduce framework, a file is the smallest unit of
input to a mapreduce job and, in the absence of caching, a
file is always read from the disk. if we have all the data in
one file, the whole file will be input to jobs for each query.
Instead, we divide the data into multiple smaller files.
User index based search:
We introduce indexes on tars to further speed up the access
to mined trees - and in general of intentional query
answering. In general, path indexes are proposed to quickly
answer queries that follow some frequent path template,
and are built by indexing only those paths having highly
frequent queries. We start from a different perspective: we
want to provide quick, and often approximate, answers also
to casual queries.
Query plan generation:
We define the query plan generation problem, and show that
generating the best (i.e., least cost) query plan for the ideal
model as well as for the practical is computationally
expensive. then, we will present a heuristic and a greedy
approach to generate an approximate solution to generate
the best plan.
Running example:
We will use the following query as a running example in this
section.
Running example
select ?v, ?x, ?y, ?z where{
?x xml : type ub : graduatestudent
?y xml : type ub : university
?z ?v ub : department
?x ub : memberof ?z
?x ub : undergraduatedegreefrom ?y }
Existing System:
Semantic web technologies are being developed to present data in
standardized way such that such data can be retrieved and
understood by both human and machine. Historically, web pages are
published in plain html files which are not suitable for reasoning.
1. No user data privacy
2. Existing commercial tools and technologies do not scale well in
cloud
3. Computing settings.
PROPOSED SYSTEM:
Integrates the functionalities proposed in our approach. Given an XML
document, it enables users to extract intensional knowledge and
compose traditional queries as well as queries over the intensional
knowledge, receiving both extensional and intensional answers. Users
formulate
XQueries
over
the
original
data,
and
queries
are
automatically translated and executed on the intensional knowledge.
document, given the support, confidence and the files where the
extracted TARs and their index are to be stored.
the original document, to give users the possibility to compare the two
kinds of information.
original XML document. Users have to write an extensional query.
1. TREE RULER ARCHITECTURE