CN103530347A - Internet resource quality assessment method and system based on big data mining - Google Patents
Internet resource quality assessment method and system based on big data mining Download PDFInfo
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Abstract
The invention provides an internet resource quality assessment method and system based on big data mining. The method includes the steps that the step (101), internet data are collected, and mass sample data are obtained in a sampling or random mode; the step (102), noise points of the sample data are removed through the data mining, so that the sample data have smoothness; the step (103), a K-Means algorithm is used for obtaining a passing value and a scale of the sample data, so that scores of a plurality of indexes of the sample data are determined; the step (104), according to correlated indexes of internet resource quality assessment, an internet resource quality assessment model is determined; the step (105), based on the obtained scores of all the indexes and the quality assessment model, the assessment result of internet resource quality is determined. According to the technical scheme, data decision supports are provided for a network operator and an ICP operator to improve perceived quality of a user, and the perfect quality assessment model enables a final quality score of the data to be more accurate.
Description
Technical field
The invention belongs to quality analysis field, internet, be specifically related to a kind of Internet resources method for evaluating quality and system based on large data mining.
Background technology
At present, most of mobile operator HeICP manufacturer is in order to solve because Internet resources quantity is many and the complicated problem that cannot determine its quality of data situation of bringing, most of employing extracted the quality that a small amount of sample data is analyzed its quality condition, and can only provide the grade of quality or the mark of scholarly forecast of resource, can not provide a reasonably accurate mark, its analysis result can not really react the quality condition of its resource, also some manufacturer adopts the data mining based on carrying out in a large number, but its treatment cycle is longer, efficiency is low, cost is high, complexity is high, if made mistakes in process, will re-start processing with careless mistake, treatment cycle and cost have greatly been increased.
Summary of the invention
The object of the invention is to, solve and cannot determine its quality of data situation problem because of what Internet resources data volume was many and complexity is brought, thereby a kind of Internet resources method for evaluating quality based on large data mining is provided.
For achieving the above object, the invention provides a kind of Internet resources method for evaluating quality based on large data mining, described method comprises:
Step 101) gather internet data, adopt sampling or random mode to obtain Massive Sample data;
Step 102) by data mining, remove the noise spot of sample data, make sample data there is flatness;
Step 103) use that K-Means algorithm draws sample data and scale value and scale, thereby determine the mark of some indexs of sample data, described index comprises: dns resolution time, TCP link setup time, the first byte time and excess time;
Step 104) according to obtain and scale value and scale carry out Internet resources quality evaluation;
Wherein, described dns resolution time, TCP link setup time, the first byte time and excess time are all in seconds.
Above-mentioned steps 102) further comprise:
Step 102-1) according to Internet resources quality evaluation index of correlation item, choose required data, and the Data Integration of choosing is become to the data set for data mining, described index of correlation comprises dns resolution time, TCP link setup time, the first byte time and excess time;
Step 102-2) based on data set, pass through cleaning and reduction operation, generate for the target data of excavating core.
Above-mentioned steps 103) further comprise:
Step 103-1), from n data object, select arbitrarily k object as initial cluster center; And for other data object of be left, according to the similarity of remaining data object and these initial cluster centers, respectively each data object in remaining data object is dispensed in certain initial cluster center the most similar to data object;
Step 103-2) calculate the cluster centre of each new cluster that obtains, constantly repeat this process until canonical measure function starts convergence, obtain and scale value and scale value, described and scale value is that canonical measure function starts the focus point of corresponding cluster centre till convergence, described scale value is the radius of corresponding cluster centre and the business of a certain setting value till canonical measure function starts to restrain, and the span of described setting value is: 0-100;
Step 103-3) based on obtain and scale value and scale value obtain the mark of each index, formula is:
Mark=the threshold value of each index-(index item-and scale value)/scale;
Wherein, the numerical values recited that the value of index item is each actual index item of Internet resources being carried out to quality evaluation and gathering, the numerical values recited of this index item is to be obtained by special Internet resources quality detection system acquisition, and described index item comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time; Minute system that the size of described threshold value adopts during to parameter mark is relevant, and being specially this threshold value is 60 percent of full marks, and when employing centesimal system, the threshold value at this place is 60, and when employing 150 score value, this place's fixed value is 90.
In technique scheme, the similarity of data object and cluster centre is weighed by the distance of data object and cluster centre; The cluster centre of described new cluster refers to the average of all data objects that this cluster centre comprises.
Above-mentioned canonical measure function adopts mean square deviation.
Above-mentioned steps 104) further comprise:
Step 104-1), according to the index of correlation of Internet resources quality evaluation, determine the Evaluation Model on Quality of Internet resources, and set the weighted value of each index in Evaluation Model on Quality;
Step 104-2) mark of each index based on obtaining and Evaluation Model on Quality, determine the assessment result of Internet resources quality.
Above-mentioned steps 104-1) adopt following Evaluation Model on Quality to draw the scoring of Internet resources quality:
Final score=dns resolution mark S1*DNS resolves weights W 1+TCP link setup mark S2*TCP link setup weights W 2+ first byte S3* the first byte weights W 3+ remainder bytes mark S4* remainder bytes weights W 4;
Wherein, dns resolution weight S1, TCP link setup weights W 2, the first byte weights W 3 and remainder bytes weights W 4 are weighted values of each index of arranging, and these weighted values are all percentages, and four weighted value sums one of are percentage hundred.
In order to realize said method, the present invention also provides a kind of Internet resources data quality accessment system based on large data mining, it is characterized in that, described system comprises:
Obtain the module of sample data, for gathering internet data, obtain sample data;
Sample data pretreatment module, for remove the noise spot of sample data by data mining, makes sample data have flatness;
Index mark acquisition module, for using that K-Means algorithm draws sample data and scale value and scale, thereby the mark of determining some indexs of sample data, described index comprises: dns resolution time, TCP link setup time, the first byte time and excess time;
Evaluation Model on Quality design module, for the index of correlation according to Internet resources quality evaluation, determines the Evaluation Model on Quality of Internet resources, and described index of correlation comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time;
Assessment result is calculated output module, for mark and the Evaluation Model on Quality of each index based on obtaining, determines the assessment result of Internet resources quality;
Wherein, described dns resolution time, TCP link setup time, the first byte time and excess time are all in seconds.
Above-mentioned sample data pretreatment module further comprises: data set obtains submodule, for index related according to Internet resources quality evaluation, chooses required data from sample data, and the Data Integration of choosing is become to the data set for data mining;
Target data is obtained submodule, for passing through cleaning and reduction operation based on data set, generates for the target data of excavating core.
These parameters mark acquisition module further comprises:
Initial cluster center and new cluster generate submodule, for from Massive Sample data, select arbitrarily k object as initial cluster center; And for other data object of be left, according to the similarity of remaining data object and these initial cluster centers, respectively each data object in remaining data object is dispensed in the initial cluster center the most similar to data object, obtains the new cluster that each initial clustering is corresponding;
And scale value and scale value are obtained submodule, for calculating the cluster centre of each new cluster that obtains, constantly repeat this process until canonical measure function starts convergence, obtain and scale value and scale value, described and scale value is the focus point of cluster centre that canonical measure function starts corresponding certain new cluster till convergence, described scale value is that canonical measure function starts the radius of cluster centre and the business of a certain fixed value of corresponding certain new cluster till convergence, and the span of described fixed value is: 0-100;
Index mark obtains submodule, for based on obtain and scale value and scale value obtain the mark of each index, formula is:
Mark=the threshold value of each index-(index item-and scale value)/scale;
Wherein, the numerical value that the value of index item is each index item, this numerical value is to get by Internet resources are carried out to quality testing, described index item comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time; Minute system that the size of described threshold value adopts during to parameter mark is relevant, be specially this threshold value and be full marks 60 percent, when employing centesimal system, the threshold value at this place is 60, when employing 150 score value, this place's fixed value is 90.
Compared with prior art, technical advantage of the present invention is: technical solution of the present invention takes full advantage of data study and excavation and the data modeling technology based on large data, can more rapidly and efficiently to Massive Sample data, carry out data mining, perfect and sound quality score model makes the massfraction of final data more accurate, and for mobile operator HeICP manufacturer, improving user-perceptive quality provides data decision support.Technical scheme of the present invention can effectively solve Internet resources mass data and determines its quality condition problem in a word.
Accompanying drawing explanation
Fig. 1 the invention provides the process flow diagram of the Internet resources method for evaluating quality based on large data mining.
Embodiment
Below in conjunction with embodiment, technical scheme of the present invention is described in detail.
As shown in Figure 1, the invention provides a kind of method that Internet resources cannot be determined its quality of alleviating, the method provides the quality score of its data for the situation of Internet resources mass data, and described method comprises:
Step 101) prepare a large amount of raw sample datas, at least five hundred ten thousand data;
Step 102) by data mining, sample data is removed to data noise, make data there is flat China's property;
Step 103) use that K-Means algorithm draws data and scale value and scale, thus each index mark of specified data;
Step 104) determine its quality score model;
Step 105) by quality score model, determine the quality score of Internet resources.
Embodiment
Take certain, to economize certain telecom operators' Internet resources management platform be example:
First, about 1000W domain name of the emphasis website that this province is paid close attention to is carried out the detection of quality condition, obtain about sampled data of 1,000 ten thousand, secondly, sampled data is carried out to data mining and remove noise, make data have more flatness, again, use K-Means algorithm in conjunction with data quality model obtain the index that domain name quality is relevant scale and and scale value, finally, service property (quality) methods of marking and Rating Model obtain the final mass mark of domain name, this operator is used after this patent, can obtain very accurately the domain name quality condition of this province, Wei Gai operator is follow-up carries out that resource is introduced and scheduling of resource provides Data support, promoted greatly this province user's perceived quality, when Wei Gai operator has saved a large amount of costs, also obtain higher user satisfaction.
In sum, the present invention adopts after above method, can assess any website on internet or the quality condition of domain name, and can provide concrete massfraction, for Virtual network operator HeICP operator, improve user-perceptive quality data decision support is provided, the present invention takes full advantage of data study and excavation and the data modeling technology based on large data, can more rapidly and efficiently to Massive Sample data, carry out data mining, perfect and sound quality score model makes the massfraction of final data more accurate.
Above embodiment is only unrestricted in order to technical scheme of the present invention to be described.Although the present invention is had been described in detail with reference to embodiment, those of ordinary skill in the art is to be understood that, technical scheme of the present invention is modified or is equal to replacement, do not depart from the spirit and scope of technical solution of the present invention, it all should be encompassed in the middle of claim scope of the present invention.
Claims (10)
1. the Internet resources method for evaluating quality based on large data mining, described method comprises:
Step 101) gather internet data, adopt sampling or random mode to obtain Massive Sample data;
Step 102) by data mining, remove the noise spot of sample data, make sample data there is flatness;
Step 103) use that K-Means algorithm draws sample data and scale value and scale, thereby determine the mark of some indexs of sample data, described index comprises: dns resolution time, TCP link setup time, the first byte time and excess time;
Step 104) according to obtain and scale value and scale carry out Internet resources quality evaluation;
Wherein, described dns resolution time, TCP link setup time, the first byte time and excess time are all in seconds.
2. the Internet resources method for evaluating quality based on large data mining according to claim 1, is characterized in that described step 102) further comprise:
Step 102-1) according to Internet resources quality evaluation index of correlation item, choose required data, and the Data Integration of choosing is become to the data set for data mining, described index of correlation comprises dns resolution time, TCP link setup time, the first byte time and excess time;
Step 102-2) based on data set, pass through cleaning and reduction operation, generate for the target data of excavating core.
3. the Internet resources method for evaluating quality based on large data mining according to claim 1, is characterized in that described step 103) further comprise:
Step 103-1), from n data object, select arbitrarily k object as initial cluster center; And for other data object of be left, according to the similarity of remaining data object and these initial cluster centers, respectively each data object in remaining data object is dispensed in certain initial cluster center the most similar to data object;
Step 103-2) calculate the cluster centre of each new cluster that obtains, constantly repeat this process until canonical measure function starts convergence, obtain and scale value and scale value, described and scale value is that canonical measure function starts the focus point of corresponding cluster centre till convergence, described scale value is the radius of corresponding cluster centre and the business of a certain setting value till canonical measure function starts to restrain, and the span of described setting value is: 0-100;
Step 103-3) based on obtain and scale value and scale value obtain the mark of each index, formula is:
Mark=the threshold value of each index-(index item-and scale value)/scale;
Wherein, the numerical values recited that the value of index item is each actual index item of Internet resources being carried out to quality evaluation and gathering, the numerical values recited of this index item is to be obtained by special Internet resources quality detection system acquisition, and described index item comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time; Minute system that the size of described threshold value adopts during to parameter mark is relevant, and being specially this threshold value is 60 percent of full marks, and when employing centesimal system, the threshold value at this place is 60, and when employing 150 score value, this place's fixed value is 90.
4. the Internet resources method for evaluating quality based on large data mining according to claim 3, is characterized in that,
The similarity of data object and cluster centre is weighed by the distance of data object and cluster centre;
The cluster centre of described new cluster refers to the average of all data objects that this cluster centre comprises.
5. the Internet resources method for evaluating quality based on large data mining according to claim 3, is characterized in that, described canonical measure function adopts mean square deviation.
6. the method for demonstration Internet resources quality score directly perceived according to claim 1, is characterized in that, described step 104) further comprise:
Step 104-1), according to the index of correlation of Internet resources quality evaluation, determine the Evaluation Model on Quality of Internet resources, and set the weighted value of each index in Evaluation Model on Quality;
Step 104-2) mark of each index based on obtaining and Evaluation Model on Quality, determine the assessment result of Internet resources quality.
7. the method for demonstration Internet resources quality score directly perceived according to claim 6, is characterized in that, described step 104-1) adopt following Evaluation Model on Quality to draw the scoring of Internet resources quality:
Final score=dns resolution mark S1*DNS resolves weights W 1+TCP link setup mark S2*TCP link setup weights W 2+ first byte S3* the first byte weights W 3+ remainder bytes mark S4* remainder bytes weights W 4;
Wherein, dns resolution weight S1, TCP link setup weights W 2, the first byte weights W 3 and remainder bytes weights W 4 are weighted values of each index of arranging, and these weighted values are all percentages, and four weighted value sums one of are percentage hundred.
8. the Internet resources data quality accessment system based on large data mining, is characterized in that, described system comprises:
Obtain the module of sample data, for gathering internet data, obtain sample data;
Sample data pretreatment module, for remove the noise spot of sample data by data mining, makes sample data have flatness;
Index mark acquisition module, for using that K-Means algorithm draws sample data and scale value and scale, thereby the mark of determining some indexs of sample data, described index comprises: dns resolution time, TCP link setup time, the first byte time and excess time;
Evaluation Model on Quality design module, for the index of correlation according to Internet resources quality evaluation, determines the Evaluation Model on Quality of Internet resources, and described index of correlation comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time;
Assessment result is calculated output module, for mark and the Evaluation Model on Quality of each index based on obtaining, determines the assessment result of Internet resources quality;
Wherein, described dns resolution time, TCP link setup time, the first byte time and excess time are all in seconds.
9. the Internet resources data quality accessment system based on large data mining according to claim 8, it is characterized in that, described sample data pretreatment module further comprises: data set obtains submodule, for index related according to Internet resources quality evaluation, from sample data, choose required data, and the Data Integration of choosing is become to the data set for data mining;
Target data is obtained submodule, for passing through cleaning and reduction operation based on data set, generates for the target data of excavating core.
10. the Internet resources data quality accessment system based on large data mining according to claim 8, is characterized in that, described index mark acquisition module further comprises:
Initial cluster center and new cluster generate submodule, for from Massive Sample data, select arbitrarily k object as initial cluster center; And for other data object of be left, according to the similarity of remaining data object and these initial cluster centers, respectively each data object in remaining data object is dispensed in the initial cluster center the most similar to data object, obtains the new cluster that each initial clustering is corresponding;
And scale value and scale value are obtained submodule, for calculating the cluster centre of each new cluster that obtains, constantly repeat this process until canonical measure function starts convergence, obtain and scale value and scale value, described and scale value is the focus point of cluster centre that canonical measure function starts corresponding certain new cluster till convergence, described scale value is that canonical measure function starts the radius of cluster centre and the business of a certain fixed value of corresponding certain new cluster till convergence, and the span of described fixed value is: 0-100;
Index mark obtains submodule, for based on obtain and scale value and scale value obtain the mark of each index, formula is:
Mark=the threshold value of each index-(index item-and scale value)/scale;
Wherein, the numerical value that the value of index item is each index item, this numerical value is to get by Internet resources are carried out to quality testing, described index item comprises: dns resolution time, TCP link setup time, the first byte time and remainder bytes time; Minute system that the size of described threshold value adopts during to parameter mark is relevant, be specially this threshold value and be full marks 60 percent, when employing centesimal system, the threshold value at this place is 60, when employing 150 score value, this place's fixed value is 90.
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