CN103399918B - A kind of method improving the searched rate in website - Google Patents

Abstract

The invention discloses a method for improving the search rate of websites, which belongs to the field of the Internet and search engines. The invention collects factors and patterns that affect search engines, and uses a linear iterative algorithm to iteratively obtain weights, thereby obtaining a quantifiable ranking for websites. , and can put forward reasonable suggestions for website optimization according to the value of the product of each influencing factor and weight value, which reduces the cost and improves the efficiency of website promotion.

Description

A method to increase the search rate of the website

technical field

The invention belongs to the field of the Internet and search engines, and in particular relates to a method for increasing the search rate of a website.

Background technique

With the continuous development of the Internet economy, "using search engines as a platform to bring traffic by adjusting the ranking of web pages on search results pages" has become a marketing method, the so-called search engine marketing (SEM, Search Engine Marketing) . SEM mainly includes two modes: paid commercial promotion optimization and search engine optimization (SEO, Search Engine Optimization). Paid SEM generally refers to the bidding ranking mechanism, while SEO refers to the optimization behavior to increase the number and ranking position of web pages in the natural search results of search engines (non-commercial promotion results). This behavior can improve the user experience and conversion rate for the website, and at the same time provide the website with an ecological self-marketing solution, allowing the website to occupy a leading position in the industry, thereby gaining brand benefits, especially when the corporate website lacks sufficient funds In the case of publicity and promotion, SEO is undoubtedly the best website promotion method with low cost, quick effect and long-lasting effect, so more and more companies pay attention to it. Moreover, as Baidu's review of PPCs has become increasingly stringent, many PPCs have been adjusted, which has attracted more website operators to seek to improve their rankings in search engines through website optimization.

However, in the actual process of SEO optimization, website managers often implement optimization only based on experience, which not only consumes the energy of the managers, but also is slow and expensive, and reduces the creativity of the enterprise itself. Therefore, it is necessary to develop a tool that automatically analyzes the SEO quality of websites to assist website managers in SEO optimization.

Contents of the invention

Aiming at the deficiencies of the prior art, the present invention proposes a method for increasing the search rate of a website, so as to quantify the ranking of the website, reduce the cost, clarify the solution, and improve the efficiency of website promotion.

A method for increasing the search rate of a website, comprising the following steps:

Step 1. Determine the factors that affect the quality of the website search engine, including the page file size of the website under test, the ratio of the number of lines of script code in the page to the total number of lines of code, the degree of matching between the name of the website under test and keywords in the website page, The ratio of the size of the dynamic picture file in the website to the size of the website page file, the ratio of the size of the animation file in the website to the size of the website page, and iteratively determine the threshold value of each of the above five factors;

Step 1-1. The user sets the page file size of the first known website, the ratio of the number of script code lines in the page to the total number of code lines, the matching degree of the name of the website under test and the keyword in the website page, The initial weights of the five factors, the ratio of the size of the dynamic picture file in the website to the size of the website page file, and the ratio of the size of the animation file in the website to the size of the website page, ensure that the sum of the initial weights of the five factors is 1;

Step 1-2, calculate the first known website initialization score according to the values of the five factors of the website and their respective initial weights;

Steps 1-3, calculating the website initialization score according to the values and initial weights of the five factors of the second known website;

Steps 1-4, by calculating the ratio of each factor score to the total score in the first known website, five new weights of the five factors are obtained respectively;

Steps 1-5, recalculating the score of the second known website according to the five new weights, and making a difference between the score obtained above and the initial score of the second website;

Steps 1-6, judging whether the difference obtained in steps 1-5 is approximately 0, if so, then complete the final determination of the weight, and according to the five factors of the first known website or the second known website, Then obtain the threshold value of each score of the five factors in the website, and the iterative process ends; otherwise, substitute the obtained weight into the first known website, and repeat steps 1-4 and 1-5;

Step 2. Collect the page file size of the website according to the URL of the website to be tested, the number of script code lines in the page, the total number of code lines, the name of the website to be tested, keywords in the website page, the size of dynamic picture files in the website, and the number of lines in the website. Animation file size, and determine the page file size of the website under test according to the above seven parameters, the ratio of the number of script code lines in the page to the total number of code lines, the matching degree between the name of the website under test and the keywords in the website page, and the Five factors are the ratio of the size of the dynamic picture file to the size of the website page file, and the ratio of the size of the animation file in the website to the size of the website page;

Step 3. Comparing the calculated scores of the five factors with their respective thresholds to realize the adjustment of the web pages of the website;

If the page file size score of the website under test is greater than the threshold, then reduce the page file size; otherwise, display the result;

If the ratio score of the number of script code lines in the page of the website under test to the total number of code lines is greater than the threshold, then reduce the amount of script code in the page; otherwise, display the result;

If the matching degree score between the name of the website under test and the keyword in the website page is greater than the threshold, then optimize the keyword of the website; otherwise, display the result;

If the ratio score between the size of the dynamic picture file in the tested website and the website page file size is greater than the threshold, then reduce the number of dynamic picture files; otherwise display the result;

If the ratio score of the size of the animation file in the website under test to the size of the website page is greater than the threshold, then reduce the number of animation files; otherwise, display the result.

According to the values of the five factors of the website and their initial weights described in steps 1-2, calculate the website initialization score, the formula is as follows:

$\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, a represents the score detected according to the initial weight; p _1i represents the calculation result of the i-th influencing factor of the first known website; w _i represents the weight corresponding to the influencing factor.

According to the values and initial weights of the five factors of the second known website described in steps 1-3, calculate the initialization score of the website, the formula is as follows:

$\mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Wherein, b represents the detection score of the second known website, p _2i represents the calculation result of the i-th influencing factor of the second known website, and w _i represents the weight corresponding to the influencing factor.

The five new weights of the five factors are respectively obtained by calculating the ratio of each factor score to the total score in the first known website as described in steps 1-4. The formula is as follows:

${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Among them, w′ _i represents the weight corresponding to the i-th influencing factor p _1i after adjustment, and w _i represents the weight corresponding to the influencing factor.

Advantages of the present invention:

The present invention is a method for improving the search rate of websites. By collecting the factors and patterns that affect the search engine, the linear iterative algorithm is used to iteratively obtain weights, so that a quantifiable score can be obtained for the website ranking, and it can target each influencing factor. The value of the product of the weight and the value puts forward reasonable suggestions for website optimization, which reduces the cost and improves the efficiency of website promotion.

Description of drawings

Fig. 1 is the flow chart of the method for improving website search rate of an embodiment of the present invention;

Fig. 2 is the product coordinate diagram of each influencing factor and the initial weight value of the first website of an embodiment of the present invention;

Fig. 3 is a coordinate diagram of each influencing factor of the second website and the weight product after one iteration in an embodiment of the present invention;

Fig. 4 is a scoring threshold coordinate diagram of an embodiment of the present invention.

detailed description

An embodiment of the present invention will be further described below in conjunction with the accompanying drawings.

The development environment hardware configuration of the embodiment of the present invention is Windows operating system: Microsoft Windows 7; CPU: Intel Centrino2 memory: 2GB; hard disk: 320GB.

A method for increasing the search rate of a website, the flow chart of the method is shown in Figure 1, comprising the following steps:

Step 1. Determine the factors that affect the quality of the website search engine, including the page file size of the website under test, the ratio of the number of lines of script code in the page to the total number of lines of code, the degree of matching between the name of the website under test and keywords in the website page, The ratio of the size of the dynamic picture file in the website to the size of the website page file, the ratio of the size of the animation file in the website to the size of the website page, and iteratively determine the threshold value of each of the above five factors;

Adopt the method of iterative algorithm in the embodiment of the present invention, obtain data drawing (as shown in Fig. 2～Fig. 4) by detecting the website of same keyword ranking in the search engine, abscissa is each influence factor, and ordinate is this influence factor The corresponding calculation value. Then, by obtaining the difference between the maximum value and the minimum value of each influencing factor as the initial value of the weight of the influencing factor. Input the results in the data set into the BP iterative algorithm for training. After the completion, the weight of the BP iterative algorithm is added to the initial weight, the average value of the two is taken, and finally the balance weight is processed to avoid accidental errors. obvious error. The main steps in the weight balancing process are as follows:

Step 1-1. Determine the first known website. In this embodiment, the website of Northeastern University is selected. The page file size p ₁ =25/50=0.48, the ratio p ₂ of the number of script code lines in the page to the total number of code lines =12/250=0.048, the degree of matching between the name of the website to be tested and the keyword in the website page p ₃ =0.8, the ratio of the size of the dynamic picture file in the website to the file size of the website page p ₄ =0, the animation file in the website The ratio of the size to the website page size p ₅ =0 The initial weight of the five factors w _i (i=1, 2,...,5) = 0.2 (as shown in Table 1), satisfying the initial weight of the five factors The sum of the values w _i (i=1, 2, ..., 5) is 1;

Table 1

Among them, the initialization weight is defined by the system and has no practical significance, it is only the initial value of the weight in the iterative algorithm.

Step 1-2, calculate the website initialization score according to the values of the five factors of the website and their initial weights;

The formula is as follows:

$\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0.2656</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span>$

Among them, a represents the score detected according to the initial weight; p _1i represents the calculation result of the i-th influencing factor of the first known website; w _i represents the weight corresponding to the influencing factor.

The website ranking score can be calculated by formula (1). This formula is a linear iterative algorithm model. By using the above iterative formula and simply changing the initial value, a vector machine with very rich and different weights and thresholds can be generated. Therefore, the initial value w _i is selected, and then through continuous iterative calculations, the weight of each influencing factor can be gradually refined. The present invention uses pattern recognition to gradually refine unknown weights through iterative methods.

Step 1-3. According to the second known website, the website of the School of Software of Northeastern University is used in the embodiment of the present invention, and the values of the five factors p _j (j=1, 2, ..., 5), p ₁ = 1.02, p ₂ =0.1875, p ₃ =0.7, p ₄ =0.3, p ₅ =25.6; and the initial weight w _i (i=1,2,...,5)=0.2 in step 1-1, Calculate the initialization score of the website; the first known website described in step 1-1 and the second known website described in step 1-3 are websites with a high retrieval rate and a top ranking in retrieval.

The formula is as follows:

$\mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 5.5615</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

Wherein, b represents the detection score of the second known website, p _2i represents the calculation result of the i-th influencing factor of the second known website, and w _i represents the weight corresponding to the influencing factor.

Steps 1-4, by calculating the ratio of each factor score to the total score in the first known website, respectively obtain five new weights of five factors; if the weight of a certain influencing factor is adjusted to 0 , then use the whole to subtract the weights that are not 0 and distribute them evenly;

The formula is as follows:

${\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 1</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

After calculation, the result is as follows:

w ₁ '=0.361

w ₂ '=0.036

w ₃ '=0.602

w ₄ '=0.0005

w ₅ '=0.0005

Among them, w' _i represents the adjusted weight corresponding to the i-th influencing factor p _i .

Steps 1-5, recalculate the score of the second known website according to the five new weights, and make a difference between the score obtained above and the initial score of the second website, and then remove the absolute value;

The formula is as follows:

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; |</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; 5</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&times;</span>{{\mathrm{<span\; class="notranslate">\; w</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}^{<span\; class="notranslate">\; \&prime;</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; |</span><span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 4.75218</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 4</span>}<span\; class="notranslate">\; )</span>$

Wherein, s represents the difference between the scoring result of the second website under test after the weight is modified and the scoring result before modification.

Steps 1-6, judging whether the difference obtained in steps 1-5 is approximately 0, if so, then complete the final determination of the weight, and according to the five factors of the first known website or the second known website, Then obtain the threshold value of each score of the five factors in the website, and the iterative process ends; otherwise, substitute the obtained weight into the first known website, and repeat steps 1-4 and 1-5;

According to the calculation of the score values of each influencing factor of the target website, the optimization direction existing in the website is judged, and reasonable suggestions are provided.

S _i =p _2i ×w″ _i (5)

Wherein, S _i is the scoring threshold of the i-th factor of the second known website, and w″ _i is the final weight of the i-th factor;

w″ ₁ =0.104

w″ ₂ =0.39

w″ ₃ =0.286

w″ ₄ =0.109

w″ ₅ =0.201

Select the second website as the standard website, after calculation

S ₁ =0.10608

S ₂ =0.73125

S ₃ =0.2022

S ₄ =0.0327

S ₅ =5.1456

Step 2, gather the page file size of this website, the script code line in the page according to the website address of the website to be tested (the home page http://epub.cnki.net/kns/default.htm of China National Knowledge Network is adopted in the embodiment of the present invention) number, total code lines, the name of the website under test, keywords in the website page, the size of the dynamic picture file in the website and the size of the animation file in the website, and determine the page file size of the website under test, the script in the page according to the above seven parameters The ratio of the number of lines of code to the total number of lines of code, the matching degree between the name of the website under test and the keywords in the website page, the ratio of the size of the dynamic picture file in the website to the file size of the website page, the size of the animation file in the website and the size of the website page The ratio of size to five factors;

C _i ＝(p′ _i ·w″ _i ) (6)

Among them, C _i represents the score of the i-th influencing factor of the target website; w″ _i represents the weight after determination; p′ _i is the i-th factor of the detected website;

C ₁ =0.1248

C ₂ =0

C ₃ =0

C ₄ =0

C ₅ =0

Step 3. Comparing the calculated scores of the five factors with their respective thresholds to realize the adjustment of the web pages of the website;

If the page file size score of the website under test is greater than the threshold, reduce the page file size to 50K; otherwise, display the result;

If the page size is too large, the page download speed will be slow. At the same time, some search engines only crawl part of the content of the page, so that the expected ranking effect cannot be obtained.

If the ratio score of the number of script code lines in the page of the website under test to the total number of code lines is greater than the threshold, then reduce the amount of script code in the page; otherwise, display the result;

Excessive scripts will interfere with search engine crawlers analyzing webpage content, virtually reducing keyword density and affecting the distribution of webpage weights.

If the matching degree score between the name of the website under test and the keyword in the website page is greater than the threshold, then optimize the keyword of the website; otherwise, display the result;

If the name of the website does not match the keyword on the page, it will reduce the relevance of the website in this keyword search.

If the ratio score between the size of the dynamic picture file in the tested website and the website page file size is greater than the threshold, then reduce the number of dynamic picture files; otherwise display the result;

Search engines cannot parse the content in dynamic pictures very well, resulting in the lack of search engines' acquisition of website content.

If the ratio score of the size of the animation file in the website under test to the size of the website page is greater than the threshold, then reduce the number of animation files; otherwise, display the result.

Since search engines are very unfriendly to Flash and cannot find hidden links in it, this must be absolutely eliminated. Although Google has started to search the content in Flash now, for important links such as the main navigation, it is absolutely not possible to use Flash to make, and it is not intuitive, and the download speed is also slow. It is very unfriendly to both search engines and users. of.

Provide solutions to the scores of various influencing factors and give feedback to users, who modify their websites through the above suggestions.

Claims (4)

1. the method improving the searched rate in website, it is characterised in that: comprise the following steps:

Step 1, determine the factor affecting site search engine masses, including foot in the pagefile size of tested website, the page This lines of code and the ratio of total code line number, tested website title with in the matching degree of keyword, website in Website page The size of motion picture files and the size of animation file in the ratio of Website page file size, website and Website page size Ratio, and by the way of iteration, determine the threshold value of above-mentioned five each scores of factor respectively；

Step 1-1, user set according to demand in the pagefile size of first known website, the page scripted code line number with The ratio of total code line number, title and the motion picture files in the matching degree of keyword, website in Website page of tested website Size and the ratio of Website page file size, website in the size of animation file and the ratio these five of Website page size because of The initial weight of element, it is ensured that the initial weight sum of five factors is 1；

Step 1-2, according to the numerical value of these five factors in website and every initial weight thereof, calculate first known website and initialize Score；

Step 1-3, according to the numerical value of five factors in second known website and initial weight, calculate this website and initialize score；

Step 1-4, by calculating each factor scores and the ratio of total score in first known website, try to achieve five factors respectively Five new weights；

Step 1-5, recalculate the score of second known website according to five new weights, and by above-mentioned regain The initial score with second website is divided to do difference；

Step 1-6, judge the difference obtained in step 1-5 whether approximate 0, the most then complete the determination that weights are final, And according to first known website or five factors of second known website, and then obtain five each scores of factor in website Threshold value, iterative process terminates；Otherwise, the weights obtained are substituted into first known website, repeats step 1-4 and step 1- 5；

Step 2, network address according to website to be measured gather scripted code line number, total generation in the pagefile size of this website, the page Animation file in motion picture files size and website in keyword, website in code line number, the title of tested website, Website page Size, and according to scripted code line number in the pagefile size of above-mentioned seven tested websites of parameter determination, the page and total code row The ratio of number, tested website title and Website page in the matching degree of keyword, website the size of motion picture files with The size of animation file and five factors of ratio of Website page size in the ratio of Website page file size, website；

Step 3, will calculate obtain five factor scores respectively compared with respective threshold value, it is achieved the tune to website and webpage Whole；

If the pagefile size score of tested website is more than threshold value, then reduce pagefile size；Otherwise show result；

If scripted code line number and the ratio score of total code line number are more than threshold value in the page of tested website, then reduce foot in the page This size of code；Otherwise show result；

If the title of tested website and the matching degree score of keyword in Website page are more than threshold value, then optimize website keyword； Otherwise show result；

If the size of the motion picture files in tested website is more than threshold value with the ratio score of Website page file size, then reduce Motion picture files quantity；Otherwise show result；

If the size of the animation file in tested website is more than threshold value with the ratio score of Website page size, then reduce animation file Quantity；Otherwise show result.

The method of the searched rate in raising website the most according to claim 1, it is characterised in that: described in step 1-2 according to this net The numerical value of five factors of standing and every initial weight thereof, calculate website and initialize score, and formula is as follows:

$a=\underset{i=1}{\overset{5}{\&Sigma;}}(p_{1i}\&times;w_i)---\left(1\right)$

Wherein, a represents the scoring detected according to initial weight；p_1iRepresent the i-th influence factor of first known website Result of calculation；w_iRepresent the weights corresponding to this influence factor.

The method of the searched rate in raising website the most according to claim 1, it is characterised in that: described in step 1-3 according to second The numerical value of five factors in known website and initial weight, calculate this website and initialize score, and formula is as follows:

$b=\underset{i=1}{\overset{5}{\&Sigma;}}(p_{2i}\&times;w_i)---\left(2\right)$

Wherein, b represents second known website detection score, p_2iRepresent the meter of the i-th influence factor of second known website Calculate result, w_iRepresent the weights corresponding to this influence factor.

The method of the searched rate in raising website the most according to claim 1, it is characterised in that: described in step 1-4 by asking first In individual known website, each factor scores and the ratio of total score, try to achieve five new weights of five factors respectively, and formula is as follows:

$w_i^{\&prime;}=\frac{p_{1i}\&times;w_i}{\underset{i=1}{\overset{5}{\&Sigma;}}(p_{1i}\&times;w_i)}---\left(3\right)$

Wherein, w '_iRepresent the i-th influence factor p after adjusting_1iCorresponding weights, w_iRepresent the power corresponding to this influence factor Value.