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When it applies, it is shown that access increases if the number of non-top pages is increased.
Now, when adding contents to the site, it assumes that a keyword is diversified enough and the number of accesses of the visitor (s-) who has searched assumes that it is proportional to the number of non-top pages in a site by this.
The number of non-top pages of the Japanese site of a Sonobe Laboratory (it is hereafter described as P) was 39 pages.
The ratio R of those (s-) who have searched among visitors is function [ of P ] R (P).
Actual measurement R of P= 39 (39) :
NPJ:0.71,
APJ:0.71,
NPE:0.81,
APE:0.65,
Since it has gathered very much, it is assumed that it is R(39) =0.72 here.
Since ratios other than -, s, and s- (namely, d-) are having assumed that a visitor's (s-) number of accesses was proportional to the number of non-top pages in a site in a top to general P although it was R(39):1-R (39) at the time of P= 39 and it is set to R(39) xP / 39:1-R (39), R (P) is.
R(P) =1 - (1/(1+ (R (39) /(1-R (39))) (xP/39)))
becoming ., for example, :
R(0)=0,
R(1)=0.062,
R(10)=0.40,
R(39)=0.72,
R(100)=0.87,
R(390)=0.96,
R(1000)=0.985,
R(10000)=0.9985,
R(100000)=0.99985,
.
Next, the ratio of what came to the non-top page among the visitors (s-) who have searched (sN-) is from statistics. :
NPJ:0.98,
APJ:0.98,
NPE:0.98,
APE:0.96,
since -- here, it is assumed that it is 0.98
Furthermore, the ratio of the visitor (what contains t or T in an access pattern) who will look at a top page among the visitors (sN-) who have searched the non-top page is the above-mentioned
table 1
.
Like (h) and (the ratio which showed the top page to the visitor who has searched the non-top page) of a (main index statistical table), since it is 0.892 in APJ, it is assumed that it is 0.89 here.
If amount of increases deltad=delta[ of top page access by addition display ] d (P) is expressed with the ratio which set the whole number of visitors to 1
deltad(P) =R (P) x0.98x0.89=0.87xR (P)
coming out -- for example
deltad(0) =0,
deltad(1) =0.054,
deltad(10) =0.35,
deltad(39) =0.63,
deltad(100) =0.76,
deltad(390) =0.84,
deltad(1000) =0.857,
deltad(10000) =0.869,
deltad(100000) =0.870,
.
If the above formula is used
"
top page access after applying ‚Ì‹Zp -- before application -- comparing -- the number of deltad(P) x visitors -- it increases
"
It is predicted.
Therefore, it is if a site scale is set as six kinds as follows (this).
Model A
It carries out.
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A non-top page
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Annual visitor
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Site
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The number of the increases in access
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1 page
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300 persons
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Small scale site
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16 times
increase
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10 pages
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3,000 persons
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Small-scale site
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1,000 times
increase
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39 pages
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12,000 persons
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Minor scale site
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7,600 times
increase
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100 pages
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30,000 persons
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Middle-scale site
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23,000 times
increase
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1,000 pages
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300,000 persons
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Large-scale site
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260,000 times
increase
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10,000 pages
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3,000,000 persons
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It is overly a large-scale site.
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2,600,000 times
increase
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It becomes.
The model of the above-mentioned trial calculation is changed and it is the site (this) where the number of annual visitors is the same and which had a non-top page 10 times but, respectively.
Model B
It carries out.
Let's also make the trial calculation of the install effect.
Increment is the number of deltad(P) x visitors.
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A non-top page
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Annual visitor
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Site
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The number of the increases in access
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10 pages
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300 persons
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Small scale site
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105 times
increase
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100 pages
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3,000 persons
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Small-scale site
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2,300 times
increase
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390 pages
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12,000 persons
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Minor scale site
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10,000 times
increase
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1,000 pages
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30,000 persons
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Middle-scale site
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26,000 times
increase
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10,000 pages
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300,000 persons
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Large-scale site
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260,000 times
increase
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10,000 pages
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3,000,000 persons
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It is overly a large-scale site.
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2,600,000 times
increase
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‚Æ, -- "
To the site below middle-scale, a big effect can be acquired especially.
" Things are understood.
The above "every year" is . which can be transposed also to arbitrary fixed periods, such as "monthly."
Since it is actually influenced, of course by various elements including the individuality of a site, this trial calculation is a standard.
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