Saturday, 12 April 2014

ALGORITHM & MODEL FOR QUICK GENERATION OF WEBTEMPLATES BASED ON CLIENTS DEMAND.



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.


 








No comments:

Post a Comment