CN102663064B - A kind of disposal route of favorites data and device - Google Patents
A kind of disposal route of favorites data and device Download PDFInfo
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Abstract
This application provides a kind of disposal route and device of favorites data, to solve prior art Manual arranging operation very loaded down with trivial details, and time-consuming problem.Described method comprises: the sequencing requests receiving favorites data, and wherein said sequencing requests comprises required parameter; The field data that described request parameter is corresponding is obtained from favorites data, and the favorites data of field described in foundation described request parameter marshalling; Favorites data based on described sequence obtains user behavior information; According to described user behavior information, the network resource information of generating recommendations, and together show with the favorites data of described sequence.The application can automatically arrange the collection data in collection according to sequencing requests and be shown to user, do not need user's Manual arranging collection, simple to operate, save time, and the accuracy of collating sequence can be ensured, based on the favorites data of described sequence, user behavior can also be analyzed, the network resource information of generating recommendations.
Description
Technical field
The application relates to browser technology, particularly relates to a kind of disposal route and device of favorites data.
Background technology
Usually when surfing the Net, the network address of the webpage that oneself can prefer and often log in by user is preserved, and the file preserving described network address is called collection.Collection is the get profit assistant of user when using browser to surf the Net, and when thinking afterwards again to browse, directly can open collection, directly clicks the network address of preserving and just opens corresponding webpage, need not again input network address or use other mode.
Collection has two kinds of forms at present: one is local collection, and the network address of collection is stored in this locality, such as, with the addition of the network address oneself liked, http://www.a.com, cannot find this network address in user's computer at home in the collection of company computer; Another kind is network collection, as long as have recorded the log-on message of the network collection of certain block browser, in the terminal of interconnection network, after using same money browser to log in, just can browse the collection content that use has been added, keep synchronous any.
Along with the time of online is more and more longer, the webpage browsed gets more and more, and the network address of user's collection also can get more and more.Further, because content interested in user's different time sections is different, the content in collection can be caused disorderly and unsystematic.User wants can only Manual arranging when arranging collection, manually classifies, complex operation, and expends time in.
Summary of the invention
This application provides a kind of disposal route and device of favorites data, to solve prior art Manual arranging operation very loaded down with trivial details, and time-consuming problem.
In order to solve the problem, this application discloses a kind of disposal route of favorites data, comprising:
Receive the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter;
The field data that described request parameter is corresponding is obtained from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Favorites data based on described sequence obtains user behavior information;
According to described user behavior information, the network resource information of generating recommendations, and press from both sides data with the collection of described sequence and together show.
Preferably, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.
Preferably, the required parameter of described sequencing requests comprises field parameter and parameters sortnig,
From favorites data, field data corresponding to described request parameter is read then, and the favorites data of field described in foundation described request parameter marshalling, comprising:
The field data corresponding with described field parameter is read from favorites data;
Described field data is sorted according to described parameters sortnig, and determines the clooating sequence of described favorites data.
Preferably, described method also comprises:
Client functionality function is generated originally according to the clooating sequence of favorites data;
Read described client functionality function originally, and show described favorites data according to described clooating sequence.
Preferably, be time sequencing at described collating sequence;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the time-sequencing request received, from favorites data, read the time field that time field parameter is corresponding, wherein said time-sequencing request comprises time field parameter and time-sequencing parameter;
Time field sorted according to time-sequencing parameter, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is name order;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the title sequencing requests received, from favorites data, read the name field that name field parameter is corresponding, wherein said title sequencing requests comprises name field parameter and title parameters sortnig;
Sorted according to title parameters sortnig by name field, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is Type of website order;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the byte orderings request received, from favorites data, read the name field that name field parameter is corresponding, wherein said byte orderings request comprises name field parameter and byte orderings parameter;
Sorted according to byte orderings parameter by described name field, correspondence determines the clooating sequence of favorites data.
Preferably, described described name field is sorted according to byte orderings parameter before, also comprise:
Analyze the Type of website that in favorites data, each name field is corresponding.
Preferably, described method also comprises:
Search information according to what input, search favorites data.
Preferably, the step of searching favorites data described in is:
Search information according to what input, the web page title collected or network address are searched.
Preferably, the described collection data acquisition user behavior information based on described sequence comprises:
The network address corresponding to the collection data of described sequence and the Type of website thereof carry out the counting in predetermined amount of time;
Draw network address quantity and network address title thereof that in each Type of website, user stores.
Preferably, described according to described user behavior information, the network resource information step of generating recommendations comprises:
According to the Type of website title that described network address quantity is maximum, matching network resource recommendation table;
Obtain the recommendation network resource information be associated.
Preferably, described recommendation information is at least one in the access information of webpage network address, the access information of web application, webpage connector.
Preferably, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
Preferably, the network resource information of described user behavior information and/or described recommendation obtains from server side.
Accordingly, disclosed herein as well is a kind for the treatment of apparatus of favorites data, comprising:
Receiver module, for receiving the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter;
Obtain and order module, for obtaining field data corresponding to described request parameter from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Obtain behavioural information module, obtain user behavior information for the favorites data based on described sequence;
Generate and display module, for according to described user behavior information, the network resource information of generating recommendations, and press from both sides data with the collection of described sequence and together show.
Preferably, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.
Preferably, described acquisition order module, comprising:
Reading submodule, for reading the field data corresponding with described field parameter from favorites data;
Sorting sub-module, for described field data being sorted according to described parameters sortnig, and determines the clooating sequence of favorites data;
Wherein, described request parameter comprises field parameter and parameters sortnig.
Preferably, described device also comprises:
Generating function module, generates client functionality function for the clooating sequence according to favorites data;
Display data module, for reading described client functionality function, and shows described favorites data according to described clooating sequence.
Preferably, described collating sequence is time sequencing, described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the time-sequencing request received, from favorites data, read the time field that time field parameter is corresponding, wherein said time-sequencing request comprises time field parameter and time-sequencing parameter;
Sorting sub-module, for time field being sorted according to time-sequencing parameter, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is web site name order, and described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the title sequencing requests received, from favorites data, read the name field that name field parameter is corresponding, wherein said title sequencing requests comprises name field parameter and title parameters sortnig;
Sorting sub-module, for being sorted according to title parameters sortnig by name field, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is Type of website order, and described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the byte orderings request received, from favorites data, read the name field that name field parameter is corresponding, wherein said byte orderings request comprises name field parameter and byte orderings parameter;
Sorting sub-module, for being sorted according to byte orderings parameter by name field, correspondence determines the clooating sequence of favorites data.
Preferably, described device also comprises:
Analyze submodule, for analyzing the Type of website that in favorites data, each name field is corresponding.
Preferably, described device also comprises:
Searching module, for searching information according to what input, searching favorites data.
Preferably, described in search module, also for according to input search information, to collection web page title or network address search.
Preferably, described acquisition behavioural information module, comprising:
Counting submodule, the network address corresponding for the collection data to described sequence and the Type of website thereof carry out the counting in predetermined amount of time;
Bear fruit module, for the network address quantity and network address title thereof that show that in each Type of website, user stores.
Preferably, described generation display module, comprising:
Matched sub-block, for according to the maximum Type of website title of described network address quantity, matching network resource recommendation table;
Obtain submodule, for obtaining the recommendation network resource information be associated.
Preferably, described recommendation network resource information is at least one in the access information of webpage network address, the access information of web application, webpage connector.
Preferably, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
Preferably, the network resource information of described user behavior information and/or described recommendation obtains from server side.
Compared with prior art, the application comprises following advantage:
First, can receive the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter, obtains the data field that described request parameter is corresponding from favorites data, and the favorites data of field described in foundation described request parameter marshalling.Favorites data based on described sequence obtains user behavior information, according to described user behavior information, and the network resource information of generating recommendations, and press from both sides data with the collection of described sequence and together show.。The application automatically arranges the collection data in collection according to sequencing requests and is shown to user, do not need user's Manual arranging collection, simple to operate, save time, and the accuracy of collating sequence can be ensured, based on the favorites data of described sequence, user behavior can also be analyzed, the network resource information of generating recommendations.
Secondly, collection can be arranged according to multiple clooating sequence in the application, can comprise according to time arrangement, according to the arrangement of web site name order with according to Type of website order arrangement etc., and in often kind of collating sequence, sort method be various.User uses very convenient, and can meet the various demands of user, and method flexibly, fast.
Again, also in collection, be provided with locating function in the application, search information according to what input, can search network address corresponding in collection fast according to web page title or network address, user is easy to use, quick.
Again, the application can analyze user's network address quantity that in each Type of website, user stores within certain time period, the network resource information that right rear line recommends the Type of website that described network address stored number is maximum to be correlated with.More can improving the function of browser collection folder, making user when browsing collection, be more prone to find the website and related web site oneself wanting to log in.
Accompanying drawing explanation
Fig. 1 is the process flow figure of a kind of favorites data described in the embodiment of the present application;
Fig. 2 is the process flow figure of a kind of favorites data described in the application's preferred embodiment;
Fig. 3 arranges favorites data sort method in the method flow diagram of collection according to time sequencing described in the embodiment of the present application;
Fig. 4 is the method flow diagram arranging collection described in the embodiment of the present application according to web site name order;
Fig. 5 is the method flow diagram arranging collection described in the embodiment of the present application according to Type of website order;
Fig. 6 is user behavior orientation analysis method flow diagram in the disposal route of a kind of favorites data described in the embodiment of the present application;
Fig. 7 is the treating apparatus structural drawing of a kind of favorites data described in the embodiment of the present application.
Embodiment
For enabling above-mentioned purpose, the feature and advantage of the application more become apparent, below in conjunction with the drawings and specific embodiments, the application is described in further detail.
With reference to Fig. 1, give the process flow figure of a kind of favorites data described in the embodiment of the present application.
Step 11, receive the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter;
When user will arrange browser collection folder, first can send the sequencing requests of favorites data to browser client, after browser client receives the sequencing requests of favorites data, first read favorites data corresponding to collection.
Wherein, described favorites data is for preserving the collection data stored in collection, and each collection data comprises: the network address of collection, web page title, web site name and collection time etc.Described sequencing requests comprises required parameter, can know the field of request and clooating sequence etc., such as, know that user wants acquisition time field by required parameter, then temporally order sequence from the near to the remote, to arrange collection.
Step 12, obtains the field data that described request parameter is corresponding from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Can read requests parameter is corresponding from data file field data, then field data is sorted by the regulation in required parameter, can the favorites data corresponding to described field data sort.
Such as, in required parameter, correspondence is name field, title is sorted according to English alphabet order.The name field that then browser client reads from data file comprises: Sina, Netease, Taobao and Jingdone district, is Jingdone district, Sina, Taobao and Netease by web site name according to the order that English alphabet order sorts.
Above-mentioned by after the data sorting in data file, the collection data in collection can be shown according to described clooating sequence, as network address.
Such as, above-mentioned is Jingdone district, Sina, Taobao and Netease by web site name according to the order that English alphabet order sorts.When showing the network address in collection, the network address of Jingdone district, Taobao, Netease and Sina can be seen successively.
Step 13, based on the collection data acquisition user behavior information of described sequence;
Above-mentioned favorites data is sorted after, can based on the collection data acquisition user behavior information of described sequence, such as, if sort according to time sequencing to favorites data, then obtain the favorites data in a period of time, then analyze described favorites data, obtain user behavior information.
Step 14, according to described user behavior information, the network resource information of generating recommendations, and together show with the favorites data of described sequence.
Above-mentionedly obtain user behavior information, then according to the network resource information of described user behavior information generating recommendations, then the favorites data of described network resource information and sequence can be shown jointly.
Such as, in the favorites data in nearest 3 months of user, 50% is the web page address of shopping website, then can generate shopping series advertisements, described shopping series advertisements and favorites data according to time sequence can be presented in collection jointly.
In sum, can receive the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter, obtains the data field that described request parameter is corresponding from favorites data, and the favorites data of field described in foundation described request parameter marshalling.Favorites data based on described sequence obtains user behavior information, according to described user behavior information, and the network resource information of generating recommendations, and press from both sides data with the collection of described sequence and together show.The application automatically arranges the collection data in collection according to sequencing requests and is shown to user, do not need user's Manual arranging collection, simple to operate, save time, the accuracy of collating sequence can be ensured, based on the favorites data of described sequence, user behavior can also be analyzed, the network resource information of generating recommendations.
Preferably, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.
With reference to Fig. 2, give the process flow diagram of favorites data sort method in the disposal route of a kind of favorites data described in the application's preferred embodiment.
Step 201, according to the collating sequence that user selects, sends corresponding sequencing requests;
The sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.In concrete enforcement, can collect in part the option arranging arranging order at browser, such as according to time sequence and by web site name (website) sort, user can select collating sequence.
According to the collating sequence that user selects, send corresponding sequencing requests to browser client.
Step 202, according to the sequencing requests received, reads the favorites data that collection is corresponding;
Wherein said sequencing requests comprises required parameter, and required parameter comprises field parameter and parameters sortnig.
Step 203, reads the field data corresponding with described field parameter from favorites data;
Favorites data is for storing the collection data in collection, and each collection data comprises: the network address of collection, web page title, web site name and collection time etc.
Such as, data 001 are collected: the network address of collection is www.xx1.com/1245; Web page title is xx1-xuenf-234; Web site name is xx1; The collection time is 2012-2-15,20:34;
Collection data 002: the network address of collection is www.xx2.com/1447; Web page title is xx1-xuxebg-ce4; Web site name is xx2; The collection time is 2012-3-1,02:04.
Such as, field parameter is time field, and field parameter corresponding to described time field is the collection time, and the field data of reading is respectively the 2012-2-15-20:34 of 001 correspondence, 002 corresponding 2012-3-1,02:04.
Step 204, sorts described field data according to described parameters sortnig, and determines the clooating sequence of described favorites data;
Such as, clooating sequence is time order from the near to the remote, then sorted according to time order from the near to the remote the above-mentioned collection time, and correspondence determines that the clooating sequence of favorites data is 002,001.
Step 205, according to the clooating sequence client functionality function of favorites data;
Above-mentionedly determine that the clooating sequence of favorites data is 002,001, correspondence can client functionality function accordingly.
Step 206, reads described client functionality function, and shows described favorites data according to described clooating sequence.
After above-mentioned generation client functionality function, can described client functionality function be sent to server.
After server receives client functionality function, can show described favorites data according to described clooating sequence, the order of favorites data is 002, and 001.
The sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.Collating sequence in collection comprises multiple, such as, according to time sequencing, by web site name order, according to websites collection order etc., certainly also comprise other collating sequences, the application does not limit this.
One, collection is arranged according to time sequencing
With reference to Fig. 3, give the method flow diagram arranging collection described in the embodiment of the present application according to time sequencing.
Step 301, reads favorites data;
Wherein, described time-sequencing request comprises time field parameter and time-sequencing parameter.
If user select according to time sequencing arrange collection, can transmitting time sequencing requests to browser client, such as, the required parameter in time-sequencing request is 1.
After client receives time-sequencing request, can read favorites data, wherein said time-sequencing request comprises required parameter, and described request parameter comprises: time field parameter and time-sequencing parameter,
If the required parameter in time-sequencing request is 1, then time field parameter can be 11, in time-sequencing parameter according to the time by being 12 as far as near order, be 13 etc. according to order from the near to the remote.
Step 302, according to the time-sequencing request received, reads the time field that time field parameter is corresponding from favorites data;
According to time field parameter 11, read time field corresponding in each collection data of favorites data, e.g., the 2012-2-15-20:34 of 001 correspondence, 002 corresponding 2012-3-1,02:04.
Step 303, sorts time field according to time-sequencing parameter, and correspondence determines the clooating sequence of favorites data;
If time-sequencing parameter is 12, then the clooating sequence of favorites data is 001,002;
If time-sequencing parameter is 12, then the clooating sequence of favorites data is 002,001.
Step 304, shows described favorites data according to described clooating sequence.
Client functionality function can be generated according to the clooating sequence of the above-mentioned collection data determined, then described client functionality function is sent to server.Server can according to described client function according to described clooating sequence display favorites data.
Two, collection is arranged according to web site name order
With reference to Fig. 4, give the method flow diagram arranging collection described in the embodiment of the present application according to web site name order.
Step 401, reads favorites data;
Wherein, described title sequencing requests comprises name field parameter and title parameters sortnig.
If what user selected arranges collection according to web site name (website) order, can send title sequencing requests to browser client, such as, the required parameter in time-sequencing request is 2.
After client receives title sequencing requests, can read favorites data, wherein said title sequencing requests comprises required parameter, and described request parameter comprises: name field parameter and title parameters sortnig,
If the required parameter in title sequencing requests is 2, then name field parameter can be 21, be 22 according to English alphabet positive sequence in title parameters sortnig, be 23 according to English alphabet inverted order, storing network address quantity according to web site name is sequentially 24 from more to less, and the network address quantity stored according to web site name from less to more order is 25.
Step 402, according to the title sequencing requests received, reads the name field that name field parameter is corresponding from favorites data;
If corresponding 3 network address of Sina, corresponding 1 network address of Netease, corresponding 5 network address of corresponding 10 network address of Taobao and Jingdone district in collection.
According to name field parameter 21, name field corresponding in each favorites data of read data files, e.g., Sina, Netease, Taobao and Jingdone district.
Step 403, sorts name field according to title parameters sortnig, and correspondence determines the clooating sequence of favorites data;
If title parameters sortnig is 22, then the clooating sequence of favorites data is corresponding 1 network address, corresponding 3 network address of Sina of 10 network address corresponding to 5 network address corresponding to Jingdone district, Taobao, Netease;
If title parameters sortnig is 23, then the clooating sequence of favorites data is corresponding 3 network address of Sina, 1 network address that Netease is corresponding, 10 network address that Taobao is corresponding, 5 network address that Jingdone district is corresponding;
If title parameters sortnig is 24, then the clooating sequence of favorites data is 10 network address corresponding to Taobao, 5 network address that Jingdone district is corresponding, corresponding 3 network address of Sina, 1 network address that Netease is corresponding;
If title parameters sortnig is 25, then the clooating sequence of favorites data is 1 network address corresponding to Netease, corresponding 3 network address of Sina, 5 network address that Jingdone district is corresponding, 10 network address that Taobao is corresponding.
Step 404, according to described clooating sequence display favorites data.
According to the clooating sequence client functionality function of the above-mentioned favorites data determined, then described client functionality function can be sent to server.Server can according to described client function according to described clooating sequence display favorites data.
Three, collection is arranged according to Type of website order
With reference to Fig. 5, give the method flow diagram arranging collection described in the embodiment of the present application according to Type of website order.
Step 501, reads favorites data;
Wherein, described byte orderings request comprises name field parameter and byte orderings parameter.
If user select according to Type of website order arrange collection, can type of time sequencing requests to browser client, such as, the required parameter in byte orderings request is 3.
After client receives byte orderings request, can read favorites data, wherein said byte orderings request comprises required parameter, and described request parameter comprises: name field parameter and byte orderings parameter,
If the required parameter in byte orderings request is 3, then name field parameter can be 31, be 32 according to English alphabet positive sequence in byte orderings parameter, be 33 according to English alphabet inverted order, the network address quantity stored according to type from more to less order is 34, and the network address quantity stored according to type from less to more order is 35.
Step 502, according to the byte orderings request received, reads the name field that name field parameter is corresponding from several favorites data;
If corresponding 3 network address of Sina, corresponding 1 network address of Netease, corresponding 5 network address of corresponding 10 network address of Taobao and Jingdone district in collection.
According to name field parameter 31, read name field corresponding in each collection data of favorites data, e.g., Sina, Netease, Taobao and Jingdone district.
Step 503, analyzes the Type of website that in favorites data, each name field is corresponding;
Can the Type of website corresponding to each web site name preset in the application, be saved in configuration file, can configuration file be read, analyze the Type of website that in favorites data, each name field is corresponding.
Such as, analyzing Netease and Sina in favorites data is social class website, and Jingdone district and Taobao are shopping class website.
Step 504, sorts name field according to byte orderings parameter, and correspondence determines the clooating sequence of favorites data;
If title parameters sortnig is 32, then the clooating sequence of favorites data is shopping class website: 10 network address that 5 network address corresponding to Jingdone district, Taobao are corresponding; Social class website: 1 network address, corresponding 3 network address of Sina that Netease is corresponding;
If title parameters sortnig is 23, then the clooating sequence of favorites data is social class website: corresponding 3 network address of Sina, 1 network address that Netease is corresponding; Shopping class website: 10 network address that Taobao is corresponding, 5 network address that Jingdone district is corresponding;
If title parameters sortnig is 24, then the clooating sequence of favorites data is shopping class website: 10 network address that Taobao is corresponding, 5 network address that Jingdone district is corresponding; Social class website: corresponding 3 network address of Sina, 1 network address that Netease is corresponding;
If title parameters sortnig is 25, then the clooating sequence of favorites data is social class website: 1 network address that Netease is corresponding, corresponding 3 network address of Sina; Shopping class website: 5 network address that Jingdone district is corresponding, 10 network address that Taobao is corresponding.
Step 505, according to described clooating sequence display favorites data.
Client functionality function can be generated according to the clooating sequence of the above-mentioned favorites data determined, then described client functionality function is sent to server.Server can according to described client function according to described clooating sequence display favorites data.
In sum, in the application, collection can be arranged according to multiple clooating sequence, can comprise according to time arrangement, according to the arrangement of web site name order with according to Type of website order arrangement etc., and in often kind of collating sequence, sort method be various.User uses very convenient, and can meet the various demands of user, and method flexibly, fast.
Preferably, described method also comprises:
Search information according to what input, search the network address in collection.
Concrete grammar as: according to input search information, to collection web page title or network address search.
In prior art, if user wants certain network address of searching collection in collection, need searching one by one, very time-consuming.
Also in collection, locating function is provided with in the application, when user wants the network address of some collections of searching, can input and search information accordingly, what then the client of browser can input according to user searches information, searches network address corresponding in collection.
User can input the key word of web page title, and such as, user inputs one-piece dress, may can find collect in multiple shopping website about one-piece network address.
And for example, user inputs www.xx, may find www.xx1.com, www.xx2.com and www.xx.com.cn.
In sum, also in collection, be provided with locating function in the application, search information according to what input, can search network address corresponding in collection fast according to web page title or network address, user is easy to use, quick.
In the application, can the described collection data acquisition user behavior information based on described sequence, and recommend corresponding Internet resources, concrete grammar comprises:
With reference to Fig. 6, give a kind of favorites data described in the embodiment of the present application disposal route in user behavior orientation analysis method flow diagram.
Step 601, the network address corresponding to the collection data of described sequence and the Type of website thereof carry out the counting in predetermined amount of time;
Such as, read the favorites data of described sequence, search the time field in each favorites data and name field, the collection time of each collection data can be read, therefrom can extract the network address of user's collection in nearest 3 months, according to described name field, described favorites data is classified, the Type of website that statistics is corresponding.
Step 602, draws network address quantity and network address title thereof that in each Type of website, user stores;
The above-mentioned network address to described extraction, can analyze the Type of website corresponding to described network address, carry out statistics and analysis to each Type of website according to preset configuration file, then can draw network address quantity and network address title thereof that in each Type of website, user stores.
Such as, add up the quantity of the network address that each Type of website stores, then can obtain the Type of website that user stores maximum network address.As user saved the network address of 10 shopping class websites in 3 months, the network address of 7 network game class websites.
Step 603, according to the Type of website title that described network address quantity is maximum, matching network resource recommendation table;
The above-mentioned network address quantity and network address title thereof having shown that in each Type of website, user stores, therefore can count the Type of website title that described network address quantity is maximum, then described Type of website title be mated with described network resource recommended table.
Wherein, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
Such as, doing shopping class website can corresponding shopping advertisement, Net silver plug-in unit etc.
Step 604, obtains the recommendation network resource information be associated.
Recommendation network resource information corresponding to described Type of website title can be obtained by coupling.
Wherein, described recommendation network resource information is at least one in the access information of webpage network address, the access information of web application, webpage connector.
Such as, the above-mentioned maximum Type of website of user's network address stored number that counts, for shopping class website, therefore can recommend the advertisement of shopping class to user.
Preferably, the network resource information of described user behavior information and/or described recommendation obtains from server side.
User behavior information described in the application can obtain from server side, and accordingly, the network resource information of described recommendation also can obtain from server side, and this is a kind of obtain manner certainly, and the application is not limited to this.
In sum, the application can analyze user's network address quantity that in each Type of website, user stores within certain time period, the network resource information that right rear line recommends the Type of website that described network address stored number is maximum to be correlated with.More can improving the function of browser collection folder, making user when browsing collection, be more prone to find the website and related web site oneself wanting to log in.
Collecting data described in the application can for the network address of collecting in browser.
With reference to Fig. 7, give the treating apparatus structural drawing of a kind of favorites data described in the embodiment of the present application.
Accordingly, present invention also provides a kind of collating unit of browser collection folder, comprising:
Receiver module 11, for receiving the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter;
Obtain and order module 12, for obtaining field data corresponding to described request parameter from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Obtain behavioural information module 15, obtain user behavior information for the favorites data based on described sequence;
Generate and display module 16, for according to described user behavior information, the network resource information of generating recommendations, and press from both sides data with the collection of described sequence and together show.
Preferably, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.
Described acquisition order module 12, comprising:
Reading submodule 121, for reading the field data corresponding with described field parameter from favorites data;
Sorting sub-module 122, for described field data being sorted according to described parameters sortnig, and determines the clooating sequence of favorites data;
Wherein, described request parameter comprises field parameter and parameters sortnig.
Preferably, described device also comprises:
Generating function module 13, generates client functionality function for the clooating sequence according to favorites data;
Display data module 14, for reading described client functionality function, and shows described favorites data according to described clooating sequence.
Preferably, described device also comprises:
Searching module 17, for searching information according to what input, searching the network address in collection.
Preferably, described in search module 17, also for according to input search information, to collection web page title or network address search.
Described acquisition behavioural information module 15, comprising:
Counting submodule 151, the network address corresponding for the collection data to described sequence and the Type of website thereof carry out the counting in predetermined amount of time;
Bear fruit module 152, for the network address quantity and network address title thereof that show that in each Type of website, user stores.
Described generation display module 16, comprising:
Matched sub-block 161, for according to the maximum Type of website title of described network address quantity, matching network resource recommendation table;
Obtain submodule 162, for obtaining the recommendation network resource information be associated.
Preferably, described recommendation network resource information is at least one in the access information of webpage network address, the access information of web application, webpage connector.
Preferably, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
Preferably, the network resource information of described user behavior information and/or described recommendation obtains from server side
Described collection data can for the network address of collecting in browser.
Preferably, described collating sequence is time sequencing, described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the time-sequencing request received, from favorites data, read the time field that time field parameter is corresponding, wherein said time-sequencing request comprises time field parameter and time-sequencing parameter;
Sorting sub-module, for time field being sorted according to time-sequencing parameter, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is web site name order, and described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the title sequencing requests received, from favorites data, read the name field that name field parameter is corresponding, wherein said title sequencing requests comprises name field parameter and title parameters sortnig;
Sorting sub-module, for being sorted according to title parameters sortnig by name field, correspondence determines the clooating sequence of favorites data.
Preferably, described collating sequence is Type of website order, and described device comprises read module, order module and display module, wherein:
Reading submodule, for reading favorites data, according to the byte orderings request received, from favorites data, read the name field that name field parameter is corresponding, wherein said byte orderings request comprises name field parameter and byte orderings parameter;
Analyze submodule, for analyzing the Type of website that in favorites data, each name field is corresponding.
Sorting sub-module, for being sorted according to byte orderings parameter by name field, correspondence determines the clooating sequence of favorites data.
For device embodiment, due to itself and embodiment of the method basic simlarity, so description is fairly simple, relevant part illustrates see the part of embodiment of the method.
Each embodiment in this instructions all adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar part mutually see.
The application can describe in the general context of computer executable instructions, such as program module.Usually, program module comprises the routine, program, object, assembly, data structure etc. that perform particular task or realize particular abstract data type.Also can put into practice the application in a distributed computing environment, in these distributed computing environment, be executed the task by the remote processing devices be connected by communication network.In a distributed computing environment, program module can be arranged in the local and remote computer-readable storage medium comprising memory device.
Finally, also it should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operational zone, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, commodity or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, commodity or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, commodity or the equipment comprising described key element and also there is other identical element.
Above to disposal route and the device of a kind of favorites data that the application provides, be described in detail, apply specific case herein to set forth the principle of the application and embodiment, the explanation of above embodiment is just for helping method and the core concept thereof of understanding the application; Meanwhile, for one of ordinary skill in the art, according to the thought of the application, all will change in specific embodiments and applications, in sum, this description should not be construed as the restriction to the application.
Claims (24)
1. a disposal route for favorites data, is characterized in that, comprising:
Receive the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter, and described request parameter comprises field parameter and parameters sortnig;
The field data that described request parameter is corresponding is obtained from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Favorites data based on described sequence obtains user behavior information;
According to described user behavior information, the network resource information of generating recommendations, and together show with the favorites data of described sequence, wherein, described recommendation network resource information is at least one in the access information of webpage network address, the access information of web application, webpage connector;
Wherein, the described acquisition of the favorites data based on described sequence user behavior information comprises: the network address corresponding to the favorites data of described sequence and the Type of website thereof carry out the counting in predetermined amount of time; Draw network address quantity and network address title thereof that in each Type of website, user stores;
Described according to described user behavior information, the network resource information step of generating recommendations comprises: according to the Type of website title that described network address quantity is maximum, matching network resource recommendation table; Obtain the recommendation network resource information be associated.
2. method according to claim 1, is characterized in that, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprises: at least one sequentially and in Type of website order of time sequencing, web site name.
3. method according to claim 2, is characterized in that, then from favorites data, obtain field data corresponding to described request parameter described in, and the favorites data of field described in foundation described request parameter marshalling, comprising:
The field data corresponding with described field parameter is read from favorites data;
Described field data is sorted according to described parameters sortnig, and determines the clooating sequence of described favorites data.
4. method according to claim 3, is characterized in that, comprises further:
Clooating sequence according to favorites data generates client functionality function;
Read described client functionality function, and show described favorites data according to described clooating sequence.
5. method according to claim 3, is characterized in that, described collating sequence is time sequencing;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the time-sequencing request received, from favorites data, read the time field that time field parameter is corresponding, wherein said time-sequencing request comprises time field parameter and time-sequencing parameter;
Time field sorted according to time-sequencing parameter, correspondence determines the clooating sequence of favorites data.
6. method according to claim 2, is characterized in that, described collating sequence is name order;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the title sequencing requests received, from favorites data, read the name field that name field parameter is corresponding, wherein said title sequencing requests comprises name field parameter and title parameters sortnig;
Sorted according to title parameters sortnig by name field, correspondence determines the clooating sequence of favorites data.
7. method according to claim 2, is characterized in that, described collating sequence is type sequence;
From favorites data, obtain field data corresponding to described request parameter then, and comprise according to the favorites data of field described in described request parameter marshalling:
Read favorites data, according to the byte orderings request received, from favorites data, read the name field that name field parameter is corresponding, wherein said byte orderings request comprises name field parameter and byte orderings parameter;
Sorted according to byte orderings parameter by described name field, correspondence determines the clooating sequence of favorites data.
8. method according to claim 7, is characterized in that, described described name field is sorted according to byte orderings parameter before, also comprise:
Analyze the Type of website that in favorites data, each name field is corresponding.
9. method according to claim 1, is characterized in that, also comprises:
Search information according to what input, search favorites data.
10. method according to claim 9, is characterized in that, described in search favorites data step be:
Search information according to what input, the web page title collected or network address are searched.
11. methods according to claim 1, is characterized in that, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
12. methods according to claim 1, is characterized in that, the network resource information of described user behavior information and/or described recommendation obtains from server side.
The treating apparatus of 13. 1 kinds of favorites data, is characterized in that, comprising:
Receiver module, for receiving the sequencing requests of favorites data, wherein said sequencing requests comprises required parameter, and described request parameter comprises field parameter and parameters sortnig;
Obtain and order module, for obtaining field data corresponding to described request parameter from favorites data, and the favorites data of field described in foundation described request parameter marshalling;
Obtain behavioural information module, obtain user behavior information for the favorites data based on described sequence;
Generate and display module, for according to described user behavior information, the network resource information of generating recommendations, and together show with the favorites data of described sequence, wherein, described recommendation network resource information is at least one in the access information of webpage network address, the access information of web application, webpage connector;
Wherein, described acquisition behavioural information module, comprising: counting submodule, for carrying out the counting in predetermined amount of time to network address corresponding to the favorites data of described sequence and the Type of website thereof; Bear fruit module, for the network address quantity and network address title thereof that show that in each Type of website, user stores;
Described generation display module, comprising: matched sub-block, for according to the maximum Type of website title of described network address quantity, and matching network resource recommendation table; Obtain submodule, for obtaining the recommendation network resource information be associated.
14. devices according to claim 13, it is characterized in that, the sequencing requests of described reception comprises: collating sequence, and described collating sequence comprise: at least one sequentially and in Type of website order of time sequencing, web site name.
15. devices according to claim 14, is characterized in that, described acquisition order module, comprising:
Reading submodule, for reading the field data corresponding with described field parameter from favorites data;
Sorting sub-module, for described field data being sorted according to described parameters sortnig, and determines the clooating sequence of favorites data.
16. devices according to claim 15, is characterized in that, also comprise:
Generating function module, generates client functionality function for the clooating sequence according to favorites data;
Display data module, for reading described client functionality function, and shows described favorites data according to described clooating sequence.
17. devices according to claim 15, is characterized in that, described collating sequence is time sequencing, described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the time-sequencing request received, from favorites data, read the time field that time field parameter is corresponding, wherein said time-sequencing request comprises time field parameter and time-sequencing parameter;
Sorting sub-module, for time field being sorted according to time-sequencing parameter, correspondence determines the clooating sequence of favorites data.
18. devices according to claim 15, is characterized in that, described collating sequence is web site name order, and described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the title sequencing requests received, from favorites data, read the name field that name field parameter is corresponding, wherein said title sequencing requests comprises name field parameter and title parameters sortnig;
Sorting sub-module, for being sorted according to title parameters sortnig by name field, correspondence determines the clooating sequence of favorites data.
19. devices according to claim 15, is characterized in that, described collating sequence is Type of website order, and described acquisition order module, comprising:
Reading submodule, for reading favorites data, according to the byte orderings request received, from favorites data, read the name field that name field parameter is corresponding, wherein said byte orderings request comprises name field parameter and byte orderings parameter;
Sorting sub-module, for being sorted according to byte orderings parameter by name field, correspondence determines the clooating sequence of favorites data.
20. devices according to claim 19, is characterized in that, also comprise:
Analyze submodule, for analyzing the Type of website that in favorites data, each name field is corresponding.
21. devices according to claim 13, is characterized in that, also comprise:
Searching module, for searching information according to what input, searching favorites data.
22. devices according to claim 21, is characterized in that, described in search module, also for according to input search information, to collection web page title or network address search.
23. devices according to claim 13, is characterized in that, described network resource recommended table comprises: the Type of website and the Internet resources according to classification of type.
24. devices according to claim 13, is characterized in that, the network resource information of described user behavior information and/or described recommendation obtains from server side.
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| CN104468482B (en) * | 2013-09-18 | 2018-09-28 | 华为技术有限公司 | A kind of method and device of file ordering |
| CN103559288A (en) * | 2013-11-08 | 2014-02-05 | 惠州Tcl移动通信有限公司 | Method and mobile terminal for intelligent collecting and sharing |
| CN104809116B (en) | 2014-01-24 | 2018-10-19 | 腾讯科技（深圳）有限公司 | A kind of method, apparatus and terminal of collection content |
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| CN104579990B (en) * | 2015-01-23 | 2019-03-01 | 小米科技有限责任公司 | The recommended method and device of router resource |
| CN105989114A (en) * | 2015-02-12 | 2016-10-05 | 广东欧珀移动通信有限公司 | Collection content recommendation method and terminal |
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| US11076042B2 (en) | 2017-02-27 | 2021-07-27 | Huawei Technologies Co., Ltd. | Favorite-object display method and terminal |
| CN110020335B (en) * | 2017-07-28 | 2022-04-26 | 北京搜狗科技发展有限公司 | Favorite processing method and device |
| CN107609157B (en) * | 2017-09-26 | 2020-11-17 | 华北理工大学 | Information processing system and method based on computer network |
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