CN101615197A - A kind of personalized network resource recommended method of connection speed Network Based - Google Patents
A kind of personalized network resource recommended method of connection speed Network Based Download PDFInfo
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Abstract
The invention discloses a kind of personalized network resource recommended method of connection speed Network Based.May further comprise the steps: utilize custom browser, the connection speed of recording user and the website of browsing; Utilize the connection speed that obtains, train the artificial neural network of measurable this user and any website connection speed; To the Internet resources of user's desire visit, the utilization correlation search engine finds out that all have the website of this resource on the internet; Use the connection speed of this user of neural network prediction and the website that all are found out; Sorted from small to large according to user's connection speed in all websites of finding out, as the result of resource recommendation.The present invention has effectively utilized user's web-based history Visitor Logs, the method of using artificial intelligence has been predicted the connection speed of user and each website, the individual subscriber network condition has been combined in the access to netwoks process, make the use of Internet resources can use user bandwidth to a greater extent, experience for the user provides better internet.
Description
Technical field
The present invention relates to computer search and web technology field, relate in particular to a kind of personalized network resource recommended method of connection speed Network Based.
Background technology
In recent years, a series of research activities has appearred, studying personalized or user oriented search engine and algorithm, as be published in 2007 the 16 international web-seminar (WWW ' 07:Proceedings ofthe 16
ThInternational conference on World Wide Web) the one piece of article " the extensive evaluation and the analysis of personalized search strategy " on (" A large-scale evaluation and analysis of personalizedsearch strategies ").One piece of article in the 23 U.S. artificial intelligence association in 2008 meeting " based on the user oriented webpage sort algorithm of user concerned time " (" A user-oriented webpage rankingalgorithm based on user attention time ") lining, the author also proposes to set up the personalized solution of a user oriented web page search engine.The present invention is the network connection situation that is used for optimizing specially the personal user.In the present invention, we have studied user oriented optimum network to greatest extent and connect and select, and this is seldom related in the past research and invention work.
Because service quality is very crucial in the network insertion of web browser and many other types, any method that can improve service quality all has huge commercial value.Some solutions have the people to propose, and some has then dropped into commercial the use.In these solutions, the most successful large scale business software is to utilize simple idea, can open a plurality of linked network content supplier automatically and do parallel the download or visit.An example is a software (http://www.xunlei.com/) that is called a sudden peal of thunder, and this is one of most popular Chinese software.Yet, use this class method, web page contents supplier's website will be subjected to tremendous influence, because it is to visit webpage by auto-programming, rather than the final user, therefore, online advertisement will lose their value on these webpages.The enterprise that this problem has caused providing this type of service quality to improve serves and some the law court's cases between the web site contents supplier.In the present invention, we have proposed a kind of based on data mining method, have considered that the user network situation comes the recommendation network website, can provide best service quality for the personal user.
Summary of the invention
The objective of the invention is to overcome the deficiencies in the prior art, a kind of personalized network resource recommended method of connection speed Network Based is provided.
The personalized network resource recommended method of connection speed Network Based may further comprise the steps:
1) utilizes custom browser, the connection speed between recording user and all websites of browsing;
2) connection speed between the website that utilize to obtain trains the artificial neural network of connection speed between measurable user and any website;
3) to the Internet resources of user's desire visit, the utilization correlation search engine finds out that all have the website of these Internet resources on the internet;
4) connection speed between the website found out of end user's artificial neural networks predictive user and step 3);
5) connection speed between all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result.
Connection speed step between all websites that the described custom browser of utilizing, recording user and its were browsed:
(a) to each website of user capture, write down each user and send request of access to the website and obtain the time interval that the website is responded to the user, be designated as user's tie-time of website;
(b) to each website of user capture, the speed of download when writing down each user from the website data download is designated as the user bandwidth of website;
(c) if the user repeatedly visits this website, then with in the nearest week or the mean value of nearest 10 times user's tie-time as user's tie-time of this website, with in the nearest week or the mean value of nearest 10 times user bandwidth as the user bandwidth of this website.
Connection speed between the website that described utilization obtains trains the artificial neural network step of connection speed between measurable user and any website:
(d) set up an artificial neural network, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the tie-time estimated value between expression user and website;
(e) set up an artificial neural network in addition, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the bandwidth estimation value between expression user and website;
(f) respectively with step (a) and the user's tie-time historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (d) to be set up is preserved the neural network after the training;
(g) respectively with step (b) and the user bandwidth historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (e) to be set up is preserved the neural network after the training.
Described Internet resources to user's desire visit, utilization correlation search engine find out that all have the website step of these Internet resources on the internet:
(h) use search engine, the given key word of user is carried out the Internet resources search, obtain preceding 30～100 Search Results websites;
(i) if the Internet resources that the user needs are text, then, calculate the text similarity between them to per two in the Search Results; If its similarity is greater than 95%, then these two of marks are identical content;
(j) if the Internet resources of user's needs are other forms, then to per two in the Search Results, 10 offset location of picked at random, the data of comparison 1K byte length on each offset location in this data file of two; If this data file of two is identical in the data of all 10 positions, then they is labeled as and has identical content;
(k) the Search Results list of websites that obtains in the set-up procedure (h): all websites with identical content all are integrated in the middle of the search result items that this content the most preceding occurs, are combined into a search result items.
Connection speed step between the website that described end user's artificial neural networks predictive user and step 3) are found out:
(l), use step (f) gained neural network estimating user and the connection speed between each website wherein to each has comprised the search result items of two or more websites in step (k) the gained search result list; Use step (g) gained neural network estimating user and the bandwidth between each website wherein.
Connection speed between described all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result step:
(m) if the network resource data size that the user needs less than 100K, to each has comprised the search result items of two or more websites in step (k) the gained search result list, website is wherein estimated that according to step (l) user who obtains resequences the tie-time from small to large;
(n) if the network resource data size that the user needs greater than 100K, to each has comprised the search result items of two or more websites in the resultant search result list of step (k), resequenced from big to small according to the user bandwidth that step (l) estimation obtains in website wherein;
(o) with adjusted search result list, as this user's resource recommendation result.
The present invention has effectively utilized user's web-based history Visitor Logs, the method of using artificial intelligence has been predicted the connection speed between user and each website, personal network's situation of user has been combined in the access to netwoks process, make the use of Internet resources can use user bandwidth to a greater extent, experience for the user provides better internet.
Description of drawings
Fig. 1 is the system flowchart of embodiment;
Fig. 2 is the virtual network architecture synoptic diagram that uses in the virtual network experiment;
Embodiment
The personalized network resource recommended method of connection speed Network Based may further comprise the steps:
1) utilizes custom browser, the connection speed between recording user and all websites of browsing;
2) connection speed between the website that utilize to obtain trains the artificial neural network of connection speed between measurable user and any website;
3) to the Internet resources of user's desire visit, the utilization correlation search engine finds out that all have the website of these Internet resources on the internet;
4) connection speed between the website found out of end user's artificial neural networks predictive user and step 3);
5) connection speed between all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result.
Connection speed step between all websites that the described custom browser of utilizing, recording user and its were browsed:
(a) to each website of user capture, write down each user and send request of access to the website and obtain the time interval that the website is responded to the user, be designated as user's tie-time of website;
(b) to each website of user capture, the speed of download when writing down each user from the website data download is designated as the user bandwidth of website;
(c) if the user repeatedly visits this website, then with in the nearest week or the mean value of nearest 10 times user's tie-time as user's tie-time of this website, with in the nearest week or the mean value of nearest 10 times user bandwidth as the user bandwidth of this website.
Connection speed between the website that described utilization obtains trains the artificial neural network step of connection speed between measurable user and any website:
(d) set up an artificial neural network, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the tie-time estimated value between expression user and website;
(e) set up an artificial neural network in addition, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the bandwidth estimation value between expression user and website;
(f) respectively with step (a) and the user's tie-time historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (d) to be set up is preserved the neural network after the training;
(g) respectively with step (b) and the user bandwidth historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (e) to be set up is preserved the neural network after the training.
Described Internet resources to user's desire visit, utilization correlation search engine find out that all have the website step of these Internet resources on the internet:
(h) use search engine, the given key word of user is carried out the Internet resources search, obtain preceding 30～100 Search Results websites;
(i) if the Internet resources that the user needs are text, then, calculate the text similarity between them to per two in the Search Results; If its similarity is greater than 95%, then these two of marks are identical content;
(j) if the Internet resources of user's needs are other forms, then to per two in the Search Results, 10 offset location of picked at random, the data of comparison 1K byte length on each offset location in this data file of two; If this data file of two is identical in the data of all 10 positions, then they is labeled as and has identical content;
(k) the Search Results list of websites that obtains in the set-up procedure (h): all websites with identical content all are integrated in the middle of the search result items that this content the most preceding occurs, are combined into a search result items.
Connection speed step between the website that described end user's artificial neural networks predictive user and step 3) are found out:
(l), use step (f) gained neural network estimating user and the connection speed between each website wherein to each has comprised the search result items of two or more websites in step (k) the gained search result list; Use step (g) gained neural network estimating user and the bandwidth between each website wherein.
Connection speed between described all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result step:
(m) if the network resource data size that the user needs less than 100K, to each has comprised the search result items of two or more websites in step (k) the gained search result list, website is wherein estimated that according to step (l) user who obtains resequences the tie-time from small to large;
(n) if the network resource data size that the user needs greater than 100K, to each has comprised the search result items of two or more websites in the resultant search result list of step (k), resequenced from big to small according to the user bandwidth that step (l) estimation obtains in website wherein;
(o) with adjusted search result list, as this user's resource recommendation result.
The embodiment flowage structure of the personalized network resource recommended method of connection speed Network Based as shown in Figure 1.You and background end two parts before this personalized recommendation system comprises, background end comprises custom browser 10, resource recommendation result 80; Preceding you comprises user's historical data 20, artificial neural network 30, general search engine 40, basic search result 50, user's tie-time and bandwidth prediction 60, the merger of Search Results and adjustment 70.
Custom browser 10: by the form of plug-in unit, at existing Internet resources browser such as Firefox, but the module of the user bandwidth of the user's tie-time when embedding the each access site of recording user among the Internet Explorer during with the transmission data.
User's historical data 20: the data of the user bandwidth of the user's tie-time during each access websites of obtaining by custom browser 10 during with the transmission data; Wherein the user of certain website is defined as each user the tie-time and sends request of access obtains this address response to the user the time interval to this website, if the user repeatedly visits this website, then with in the nearest week or the mean value of nearest 10 times user's tie-time be as the criterion; Speed of download when the user bandwidth of certain website is defined as each user from this website data download, if the user repeatedly visits this website, then with in the nearest week or the mean value of nearest 10 times user bandwidth be as the criterion.
Artificial neural network 30: in an embodiment, we have used two artificial neural networks that are 4 layers, and the input layer of one of them artificial neural network is the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; Its output layer is a real number, the tie-time estimated value between expression user and this website; The input layer of another person's artificial neural networks is the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; Its output layer is a real number, the user bandwidth estimated value between expression user and this website; Each neuron in other two-layer in these two neural networks is a sigmod function, and per two neurons between adjacent two layers all link to each other; Utilize back-propagation algorithm (back-propagation), constantly use user's historical data 20 that it is trained on the backstage.
General search engine 40 a: user interface is provided, calls the Internet resources search service; In the present embodiment, this interface is used and is realized with jsp; When the user submits a query requests to, call general network search engine (such as Google) and obtain Search Results.
Basic search result 50: after utilizing general search engine 40 to search for, preceding 100 results in its return results are resolved and obtained to its result of page searching, and, then the document is downloaded and deposited to this locality if this resource is a document.
User's tie-time and bandwidth prediction 60: end user's artificial neural networks 30, its user tie-time and user bandwidth are predicted in each website among the basic search result.
The merger of Search Results and adjustment 70:1) merger: if the Internet resources that the user needs are text, then, use " text similarity estimation source code " (" the Code for estimating document similarity ") in the open source code package of Microsoft (Microsoft) to calculate the text similarity between them to per two in the Search Results; If its similarity is greater than 95%, then these two of marks are identical content; If the Internet resources of user's needs are other forms, then to per two in the Search Results, 10 offset location of picked at random, the data of comparison 1K byte length on each offset location in this data file of two; If this data file of two is identical in the data of all 10 positions, then they is labeled as and has identical content; The website that then all is had identical content all is integrated in the middle of the search result items that this content the most preceding occurs, is combined into a search result items; 2) adjust: if the network resource data size that the user needs is less than 100K, to each has comprised the search result items of two or more websites in the Search Results, with net wherein
Stand according to user's tie-time and bandwidth prediction 60 estimate the user resequence from small to large the tie-time; If the network resource data size that the user needs is greater than 100K, to each has comprised the search result items of two or more websites in the Search Results, with wherein website according to user's tie-time and bandwidth prediction 60 estimate user bandwidth resequence from big to small;
Resource recommendation result 80: obtain user oriented personalized resource recommendation result after the merger of process Search Results and the process of adjustment 70; This recommendation results has fully taken into account personal network's situation of user, makes the use of Internet resources can use user bandwidth to a greater extent, can experience for the user provides better internet.
The experimental result of table 1～2 demonstrates the superiority of this method clearly;
Table 1～table 2 is data of testing acquisition in the virtual network of a simulation internet situation; The network structure of this virtual network as shown in Figure 2; Each website is under the multitiered network structure that is formed by some gateway tissues; Total about 30000 computing machines in this virtual network, be distributed in three different Internet service providers (ISP) under; Gateways at different levels if more near the network root then its time delay more little and bandwidth near netting twine is big more, if more away from the network root then its time delay big more and bandwidth near netting twine is more little; Be about 1/100 of inner each gateway delay time of same ISP the time delay of the main line gateway between the different I SP, bandwidth is about 50 times; In our experiment, we have set up 500 different resource data, and each duplicates 2000 parts, are randomly dispersed in the computing machine in the virtual network; User's resource query request each time supposes that search engine can return wherein 90% website, and random alignment; The probability that the i item in the site list is returned in our suppose user clicks search is
In table 1～table 2, listed before and after use the method for the invention embodiment, the user obtains the spended time altogether of its resource requirement; Each row represents that respectively user's resource requirement is of a size of the 10K byte in each experiment, obtains the required time of this resource when 1M byte and 100M byte; When each row is represented not use embodiment of the invention system respectively, use embodiment of the invention system and have 10000 in advance, 50000, the experimental data during 100000 user's historical records; Each experimental data is the same experiment flow average data after 100 times repeatedly, and experimental data unit is millisecond (ms); In the experiment of table 1, the user is set and is in than on the computing machine away from the network root, i.e. analog dialup network user situation; In the experiment of table 2, the user is set and is in than on the computing machine near the network root, promptly simulates the broadband network user situation;
Table 1
| The 10K byte | The 1M byte | The 100M byte | |
| Do not use the present invention | 285.3ms | ?23472ms | ?2290176ms |
| Article 10000, record | 117.8ms | ?10445ms | ?1662668ms |
| Article 50000, record | 118.6ms | ?8791ms | ?945567ms |
| Article 100000, record | 80.1ms | ?7077ms | ?841838ms |
Table 2
| The 10K byte | The 1M byte | The 100M byte | |
| Do not use the present invention | 135.8ms | ?3808ms | ?486680ms |
| Article 10000, record | 123.1ms | ?3610ms | ?435579ms |
| Article 50000, record | 125.9ms | ?4275ms | ?340575ms |
| Article 100000, record | 152.2ms | ?6794ms | ?422088ms |
Table 3～table 4 is that the embodiment of the invention is used the experimental data under real China Internet; In the experiment of table 3,6 Dial-up Network users from different regions have used embodiment of the invention system; In the experiment of table 4,6 broadband network users from different regions have used embodiment of the invention system; After using fortnight, to the exemplary resource on 3 kinds of internets: text, PDF document and online game installation file conduct interviews; Each row represents that respectively user's resource requirement is a web page text in each experiment, obtains the required time of this resource when PDF document and recreation installation file; The expression when not using embodiment of the invention system and use experimental data after the embodiment of the invention system respectively of each row; Each experimental data is the similar resource average data after 100 times repeatedly; The average data size of above-mentioned three class resources is respectively the 10.6K byte, 3.49M byte, 784M byte; Experimental data unit is millisecond (ms);
Table 3
| 10.6K text | 3.49M PDF document | The 784M game file | |
| Do not use the present invention | ?1390ms | ?362291ms | ?71264384ms |
| Use the present invention | ?733.1ms | ?99992ms | ?25726443ms |
Table 4
| 10.6K text | 3.49M PDF document | The 784M game file | |
| Do not use the present invention | ?1082ms | ??99615ms | ??12490914ms |
| Use the present invention | ?693.0ms | ??64531ms | ??7765583ms |
Above table shows, the present invention has effectively utilized user's web-based history Visitor Logs, the method of using artificial intelligence has been predicted the connection speed between user and each website, personal network's situation of user has been combined in the access to netwoks process, make the use of Internet resources can use user bandwidth to a greater extent, can experience for the user provides better internet.
The above is the preferred embodiment of the personalized network resource recommended method of a kind of connection speed Network Based of the present invention only, is not in order to limit the scope of essence technology contents of the present invention.The personalized network resource recommended method of a kind of connection speed Network Based of the present invention; its essence technology contents is to be defined in widely in claims; any technology entity or method that other people are finished; if it is identical with the definien of institute in claims; or the change of same equivalence, all will be regarded as being covered by within this scope of patent protection.
Claims (6)
1. the personalized network resource recommended method of a connection speed Network Based is characterized in that may further comprise the steps:
1) utilizes custom browser, the connection speed between recording user and all websites of browsing;
2) connection speed between the website that utilize to obtain trains the artificial neural network of connection speed between measurable user and any website;
3) to the Internet resources of user's desire visit, the utilization correlation search engine finds out that all have the website of these Internet resources on the internet;
4) connection speed between the website found out of end user's artificial neural networks predictive user and step 3);
5) connection speed between all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result.
2. the personalized network resource recommended method of a kind of connection speed Network Based according to claim 1 is characterized in that the described custom browser of utilizing, the connection speed step between all websites that recording user and its were browsed:
(a) to each website of user capture, write down each user and send request of access to the website and obtain the time interval that the website is responded to the user, be designated as user's tie-time of website;
(b) to each website of user capture, the speed of download when writing down each user from the website data download is designated as the user bandwidth of website;
(c) if the user repeatedly visits this website, then with in the nearest week or the mean value of nearest 10 times user's tie-time as user's tie-time of this website, with in the nearest week or the mean value of nearest 10 times user bandwidth as the user bandwidth of this website.
3. the personalized network resource recommended method of a kind of connection speed Network Based according to claim 1, it is characterized in that the connection speed between website that described utilization obtains, train the artificial neural network step of connection speed between measurable user and any website:
(d) set up an artificial neural network, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the tie-time estimated value between expression user and website;
(e) set up an artificial neural network in addition, it is input as the characteristic of a website: comprise that one is expressed as the network ip address of 32 integers and the hourage that the integer of 1 value between 0～23 is used to represent the current time; It is output as a real number, the bandwidth estimation value between expression user and website;
(f) respectively with step (a) and the user's tie-time historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (d) to be set up is preserved the neural network after the training;
(g) respectively with step (b) and the user bandwidth historical data that (c) obtains as training set, the neural network of using back-propagation algorithm training step (e) to be set up is preserved the neural network after the training.
4. the personalized network resource recommended method of a kind of connection speed Network Based according to claim 1, it is characterized in that described Internet resources to user's desire visit, the utilization correlation search engine finds out that all have the website step of these Internet resources on the internet:
(h) use search engine, the given key word of user is carried out the Internet resources search, obtain preceding 30～100 Search Results websites;
(i) if the Internet resources that the user needs are text, then, calculate the text similarity between them to per two in the Search Results; If its similarity is greater than 95%, then these two of marks are identical content;
(j) if the Internet resources of user's needs are other forms, then to per two in the Search Results, 10 offset location of picked at random, the data of comparison 1K byte length on each offset location in this data file of two; If this data file of two is identical in the data of all 10 positions, then they is labeled as and has identical content;
(k) the Search Results list of websites that obtains in the set-up procedure (h): all websites with identical content all are integrated in the middle of the search result items that this content the most preceding occurs, are combined into a search result items.
5. the personalized network resource recommended method of a kind of connection speed Network Based according to claim 1 is characterized in that the connection speed step between website that described end user's artificial neural networks predictive user and step 3) find out:
(l), use step (f) gained neural network estimating user and the connection speed between each website wherein to each has comprised the search result items of two or more websites in step (k) the gained search result list; Use step (g) gained neural network estimating user and the bandwidth between each website wherein.
6. the personalized network resource recommended method of a kind of connection speed Network Based according to claim 1, it is characterized in that the connection speed between described all websites of finding out according to user and step 3) sorts from small to large, as network resource recommended result step:
(m) if the network resource data size that the user needs less than 100K, to each has comprised the search result items of two or more websites in step (k) the gained search result list, website is wherein estimated that according to step (l) user who obtains resequences the tie-time from small to large;
(n) if the network resource data size that the user needs greater than 100K, to each has comprised the search result items of two or more websites in the resultant search result list of step (k), resequenced from big to small according to the user bandwidth that step (l) estimation obtains in website wherein;
(o) with adjusted search result list, as this user's resource recommendation result.
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| CN106503036A (en) * | 2016-09-14 | 2017-03-15 | 深圳市金立通信设备有限公司 | A kind of method for downloading web data and terminal device |
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2009
- 2009-07-30 CN CN2009101010476A patent/CN101615197B/en not_active Expired - Fee Related
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| CN102663048A (en) * | 2012-03-29 | 2012-09-12 | 奇智软件（北京）有限公司 | Method and device for providing search result |
| CN102663048B (en) * | 2012-03-29 | 2017-04-12 | 天津奇思科技有限公司 | Method and device for providing search result |
| CN102651033A (en) * | 2012-04-09 | 2012-08-29 | 百度在线网络技术（北京）有限公司 | Method and device for recommending online resource |
| CN104065523A (en) * | 2013-03-19 | 2014-09-24 | 腾讯科技（深圳）有限公司 | Connection rate detection method and device |
| CN104065523B (en) * | 2013-03-19 | 2019-08-27 | 腾讯科技（深圳）有限公司 | Connection speed detection method and device |
| CN103500231A (en) * | 2013-10-25 | 2014-01-08 | 乐视网信息技术（北京）股份有限公司 | Multi-media file recommending method and device |
| WO2016023442A1 (en) * | 2014-08-12 | 2016-02-18 | 优视科技有限公司 | Network request method, network fluctuation measurement method and apparatus, and terminal |
| CN104239468A (en) * | 2014-09-02 | 2014-12-24 | 百度在线网络技术（北京）有限公司 | Method and device for reordering recommended information |
| CN106503036A (en) * | 2016-09-14 | 2017-03-15 | 深圳市金立通信设备有限公司 | A kind of method for downloading web data and terminal device |
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