ABSTRACT:R
As we know web programming needs a lot of human resource
&this makes it resource consuming.
Resources like time power, patience...Etc,
Nowadays website
developer software’s are available like bluevoda,yahoo site builder…etc
But they increase complexity if extra resources are need to
be added or any kind of alteration is needed and its is difficult to accurately
design a webpage.
The key factors for designing creating a web template are
platform, clients demand, clients data (clients refers to publisher/owner of
site).
Based on this if we use a source code directory containing
all possible codes of a particular web programming language & shuffle up
with clients data based on clients demand with a probability approach, quick
web templates are created.
By algorithm, theoretically one can generate
millions of web templates in an single
hour if clients data and clients demand is loaded &the algorithm is smartly
programmed with efficient artificial
intelligence module.model:
CLIENT DATA:
It includes data
which is to be published on webpage. It is sequential set of data elements like
images, text, logos, video, flash apps, java applets, &other extra resource
which is to be published on site.
CLIENTS DEMAND:
it is the necessity or quality of pages needed by the
clients, it contains integer rating Or ranking of type of appearance of site
which is demanded by client. Based on this priority range for entity and also
shuffler rate is entered here. manually clients demand can be entered or a
predefined rating can be used to eliminate time. The structure of clients data
ia as shown below.
As shown in block diagram,
Shuffler rate and predefined ranking is assigned to pages as
per clients demand based on this priorities are selected and the block is
transferred to probability block.
ENTITIES:AS shown in block diagram ,entities
n1,n2,n3……………..n are parameters which decide the appearance of data in webpage.
Ex: n1àcharacter
style, n2àimage
resolution.n3 àcharacter
position………………..nànth
parameter
PROBABILITY BASED APPROACH BY CLIENTS DEMAND:
it is calculated for each interval of n value as shown in block diagram.
*everyone is familiar with combination formula
nCN where no. of n selections are based on rate of N
But here n is entity property and N is shuffler rate.
*Now from limits range, lim à(a0,an)
where a0 to an is the range of priority
of entity.
*a0 and an is dependent on N
Eg: let N=2, entities n=24
Let they predefined rating be of 23-27 range (let it be
rating for a average site)
Now a0 & an get a value between 23 t0 27 with any two
selections done by artificial intelligence module based on clients quality
demand.
SOURCE CODE SELECTOR WITH ARTIFICIAL INTELLIGENCE MODULE :
This block based on probability approach selects the source code from source
code directory & copies into pages
of web templates.
An AI module selects or arranges and calculates extra math
probability to make appearance of page better.
SOURCE CODE DIRECTORY: it is code book containing all possible
source codes of a particular web programming language.
WEB-TEMPLATES: As shown in block diagram, the structure
contains series of pages. The source code is copied here. The no. of templates depend on shuffler rate
N
ALGORITHM:
STEP 1: load client data and client demand.
STEP 2: select entities as per client’s data.
STEP 3: Probability based approach is started, artificial
intelligence module calculates
Approximate probability
required to improve/select page.
STEP 4: Select source code from source directory and arrange
them in code.
STEP 5: As per shuffler rate templates are created.
Case history (example):
*A business xyz, has a small scale business, wants site with
a good appearance design a site based on above referred algorithm.
Ans: Good site(needs no funky, entertaining , …etc,)
business oriented site
Clients data:- type entities
Image 1 company logo n1
Image 2 owners picture n2
Image 3 office building n3
Image 4 employees
picture n4
Java applet time/date n5
Text 1 company name n6
Text 2 office
address n7
Text 3
quotes n8
Text 4
owner’s info n9
Text 5 about
company n10
Text 6 achievements n11
Clients demand:
Let there be a standard predefined value for kind of site
xyz is demanding.
Let demanded page be 1.
Let the shuffler rate be 2 demanded by client. Two
priorities are selected.
The above operations can totally be replaced by single predefined value
Operation: for image1, company logo entity n1 has now two
possible positions on page & two possible resolutions. Based on standard
predefined value two priorities are selected i.e.
Let a0=4 an =5, since N=2.
n1CN ;range of n1: lim-->(4
to 5)
I.e. out of so many n1 values, property stored at 4 t0 5
range is copied by source code in to two
pages present in two templates.
Position of this on page is decided by artificial intelligence module.
Similar operation is carried out for n2, n3 and n4
For n5 it’s a java applet no modification in code but
position on page is decided by A I module.
For n6 to n11 are text with parameters with math similar to
image operations referred above.
The final result will have two templates with a single page.
it may look like above figure.
A I module plays a
crucial role..it should be programmed smartly.
crucial role..it should be programmed smartly.
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