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Theorem 4: (10), individually, as one situation :
"" element contents.
Theorem 5: (11), (12), (13), the three cases can be
classified one situation: .
Theorem 67: the cases of (15) and (10) are the same, as
a judgement event:
element content.
Theorem 7: (16), (17), (18), the three cases as a
judgement event class: .
Theorem 8: (19) as a judgement event alonely:
According to the 7 judgement events summarized in
this article, and then expand the SAX API, then we can
create the SCTP index.
Through the analysis above ,the algorithm process of
building CSTP as follows:
Input: XML and encoding table
Output: CSTP Compressed index
Begin:
Start with SAX //parse sequencely,
new (Node3)// to build the first node;
s = new (Node1);
push (S3, s);
if (xml root tag has property value)
{
p = new (Node3);
s.attribute = p;
P-> left = property value;
}
while (* PP) / / there is also property
{
q = new (Node3);
p->right = q;
p = q;
q->left = property value;
}
p->right = NULL;
while (xml document did not be finished)
{
Case 1: / / read the string form: <
... ...
Case 2: / / read the string form : <
... ...
Case 3: //the third case: contents
... ...
Case 4: / /,be similar to Case 3
... ...
Case 5: / /
... ...
Case 6: / / read the string form :
... ...
Case 7: / / read the string form:
( must be Children)
... ...
}
There is another way to build an index: build nodes
using the contents of judgement event, rather than the
previous one, then it’s different to categorize the 25
original events. Of course, the specific implementation
of the algorithm is also different from the process above,
don’t give it’s detail here.
Ⅲ. THE QUERY ALGORITHM BASED ON CSTP
A. Tthe Analysis of The Process and Character of Query
Query process of Xpath is similar to Xquery’s, but the
latter’s is more complicated to achieve. Only discuss the
XPath query at this. Analyse the query process and the
character of it on the CSTP index before discussing the
XPath query, as follows:
For simple path query: I : t / t / t
1 2
L
m
.The t 1
may
be the root element node of tree-graph of CSTP, that may
be not. If it is not the root element node, such as a third
layer node in the tree-graph of CSTP, when users submit
query expression, then the computer would begin to visit
differrent chain on the second layer of the CSTP treegraph.
If there is no t 1
, then visit the the differrent chain
constituted with the children of the second node on the
second layer (the second node may be in the same name
item). Continue to do until find t 1
, we can see that the
computer will compare many times. Suppose, there are N
elements nodes on the second layer of the CSTP, and
there are M elements nodes in the different chain, each
node on the second layer has on average N 2 child nodes
of different chain, then such a query’s time complexity is
O( N1 + N2
⋅ N ) ≈ O( N2
⋅ N ) . To a mass of data, N is a
rather large number. And if the expression t 1
supplied by
user does not exist, which will make computer visit
through CSTP tree-graph. Time cost is obviously very
high. Of course, if additional information such as start
layer can be specified, and new a head node on each layer
of CSTP tree-graph, so that can significantly reduce the
query time, but this would obviously lead to an
unnecessary number of additional work. Therefore,
suppose, t
1
is on the first layer of , this path
expression is called a full path expression. If the path
expression submitted by the user is not full, we can predefined
certain rules, then generate the full path
expression automatically when the user query.
B. Analysis of Algorithm and Efficiency Based on XPath
Query
According to the analysis above, we can query
efficiently in the compressed structure. At the same time,
in accordance with coding table generated by DTD ,we
can design decompression algorithms at the process of
query.
Because of the complexity of XML itself and CSTP
index, only give the qualitative analysis and comparison
at this.
Basing on the high repeatability of XML tag data this
paper introduce TP relation to convert the original tree
structure of XML into CSTP structure in this paper. And
the introduction of the same name items and different
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