CN103051930A - Method and system for recommending mobile video based on flow analysis and user behavior analysis - Google Patents
Method and system for recommending mobile video based on flow analysis and user behavior analysis Download PDFInfo
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Abstract
The invention relates to a method and a system for recommending a mobile video based on flow analysis and user behavior analysis. The method comprises the following steps of: capturing a video source from major video stations by simulating a station browsing behavior of a user by using a crawler; extracting the meta information of a video; intelligently weighting the meta information, and establishing an index; generating a user video recommendation policy according to data acquired by a mobile terminal; and when the user performs on-demand operation, transcoding a user video into an optimum video code stream according to a reported bandwidth applied by the mobile terminal in the user video recommendation policy, and providing the video code stream for the user for watching. The invention has the advantages that the optimum video code stream can be obtained by real-time transcoding according to the flow using habit of the user, a dynamic change video recommendation policy of a video on-demand behavior and the current customization flow package of the user, and then provided for the user for watching, so the problem of over-high flow cost for watching stream media by the user in the prior art is solved to a certain extent, and user experience is improved.
Description
Technical field
The present invention relates to the mobile video recommended technology, particularly a kind of mobile video recommend method and system based on flow analysis and user behavior analysis.
Background technology
Existing traffic monitoring technology is flow analysis, and it is in the situation of Real Time Monitoring network traffics, takes to change the monitor video definition and take out frame when network is busy and reduce the code check of watching video, reduces consumption network device resource (flow) as far as possible.Make its definition that when network is busy, rationally reduces video improve network traffics, the network free time, can watch with higher definition, obtain preferably video-see quality.
It is the basis of realizing personalized recommendation that film recommendation technology (user behavior analysis) is set up user model.The film recommendation technology mainly is to carry out the research of film recommendation service at the media server system platform, the user is by Broadband Media gateway accessing system, the media server stores film of system and film ontology model information, receive and the recording user program request, search the film relevant information, preserve user's historical record to generate user model, then form the film recommendation tabulation of mating with user model according to algorithm.
Development along with 3G network technology, multimedia technology and mobile video, video data sharply increases, therefore the user often has no time to attend to the loss of flow when watching video, great number flow cost and the rate watching video and brought with it make the user disappointing.On the other hand, the user is also because have no way of doing it in the face of vast as the open sea video resource.Can sum up existing Video Applications system and exist following defective: 1, effectively not distinguish the user: a small amount of a large amount of Internet resources of CU.2, can't realize class-of-service: network is not made the overall arrangement for the QOS ability, can not distinguish for different business.3, video traffic indifference: with other video website, the equal service competition in the Internet, operator's no significant difference and advantage.4, Internet resources lack effectively management: can't accurately learn what how many resources of CU, can't dynamically adjust Internet resources.5, analysis means is comprehensive not: present video recommend based on technological means all comparatively independent, the flow operation of operator on the one hand, comprise its traffic monitoring, the situation analysis of user's use traffic etc., to pass through user behavior on the other hand, be that the video duration watched of user, number of times etc. carry out the analysis user behavior, two technological means are managed separately, and therefore existing video recommended technology has to be strengthened.
So, the user in the urgent need to a kind of can be according to user self interest and traffic demand, recommend targetedly the Intelligent Service of corresponding video for the user, i.e. " individualized video recommendation service ", the flow operating position can be scientifically analyzed in this service, the Real Time Monitoring flow uses and rate, carries out flow control and flow in good time and reminds.
Summary of the invention
The purpose of this invention is to provide a kind of mobile video recommend method based on flow analysis and user behavior analysis, can recommend strategy according to the dynamic change video of customer flow use habit, video request program behavior, and customize at present the flow set meal in conjunction with the user, real-time transcoding provides the user to watch for the video flowing of user's optimum, thereby watch the too high problem of flow media flux expense to a certain degree solving present user, and improve user's experience.
The present invention adopts following scheme to realize: a kind of mobile video recommend method based on flow analysis and user behavior analysis is characterized in that:
Step S01: use reptile by the behavior of analog subscriber view site, from each large video website crawl video source;
Step S02: the meta information that extracts video;
Step S03: after this meta information is weighted Intelligent treatment, set up index, and storage administration unified in just described index;
Step S04: portable terminal gathers size, period, visual classification and the video length data that the user watches the flow of video;
Step S05: the data according to this portable terminal collection generate this user video recommendation strategy, and recommend policy update to be saved to a central database user video;
Step S06: when the user carries out the program request operation, pick out the video link that meets the user at present most according to the video element information of storing in the database, use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to this portable terminal in the described user video recommendation strategy simultaneously, offer the user and watch.
In an embodiment of the present invention, be that homepage from each large video website begins to adopt multithreading recurrence crawl video source among the described step S01.
In an embodiment of the present invention, described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.
In an embodiment of the present invention, described power Intelligent treatment is according to the static prime information of video and video flow information, and video is carried out cluster, the line index of going forward side by side ordering; Along with the variation of video click volume and access times, adopt a predetermined time interval mode that video is carried out the secondary index collating sort; Each visual classification inside will be weighted ordering according to video multidate information and video flow information simultaneously; Described static prime information comprises label, title, classification and the brief introduction of video; Described video flow information comprises code check, size and the coded format of video; Described multidate information is click volume and the access times of video.
In an embodiment of the present invention, administrative staff can interfere described index order by the weight of setting described prime information and flow information.
Another object of the present invention provides a kind of mobile video commending system based on flow analysis and user behavior analysis.
The present invention adopts following scheme to realize: a kind of mobile video commending system based on flow analysis and user behavior analysis is characterized in that comprising:
One video polymerization analysis unit, this video polymerization analysis unit are responsible for from each large video website crawl video source, and extract the meta information of video, be weighted Intelligent treatment after, set up index, storage administration unified in the index of setting up the most at last;
One customer flow and behavioural analysis unit, this customer flow and behavioural analysis unit will be located at data that flow collection unit, user behavior collecting unit and the network bandwidth detection module of customer mobile terminal upload and generate this user video and recommend strategy, and recommend policy update to be saved to a central database user video;
One Service Management Unit, this Service Management Unit is mainly realized the service management of whole system, comprise video is examined issue, video resource is managed and manually participate in flow and user behavior analysis, recommend strategy to carry out manual intervention to the video that generates; And
One operation support interface unit, this operation support interface unit are the external unified interface of system, and it provides provider customer's flow inquiry service, the payment interface of the video of partly paying and the short multimedia message interface that the user is carried out the video recommendation.
In an embodiment of the present invention, described video polymerization analysis unit comprises:
One video handling module, this video handling module use reptile by the behavior of analog subscriber view site, begin to adopt multithreading recurrence crawl video source from the homepage of each large video website;
One video content analysis module for the meta information of the video that extracts described video handling module crawl, and after being weighted Intelligent treatment, is set up index, and storage administration unified in the index of setting up the most at last; And
One video intelligent real-time transcoding and Streaming Media handover module, this video intelligent real-time transcoding and Streaming Media handover module are picked out the video link that meets the user at present most according to the video element information of storing in the database, to recommend tactful portable terminal to use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to the family video simultaneously, and offer the user and watch.
In an embodiment of the present invention, described weighting intelligence place is static prime information and the video flow information according to video, video is carried out cluster, the line index of going forward side by side ordering; Along with the variation of video click volume and access times, adopt a predetermined time interval mode that video is carried out the secondary index collating sort; Each visual classification inside will be weighted ordering according to video multidate information and video flow information simultaneously; Described static prime information comprises label, title, classification and the brief introduction of video; Described video flow information comprises code check, size and the coded format of video; Described multidate information is click volume and the access times of video.
In an embodiment of the present invention, described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.
The invention has the beneficial effects as follows:
1, optimizes existing video recommended technology, solve one-sided consideration flow or user behavior and cause its video to recommend not intelligence and comprehensively problem, break existing technology estrangement, connection traffic monitoring and user behavior analysis technology form systematic intelligent video and push pipeline.
The problem of 2, solution information, network over loading: can also provide resource to read in advance to predictable result, the Optimized Service quality reduces offered load.
3, solve the problem that user individual pushes: the personalized film recommendation service is to solve the film resource to increase user's's " information is got lost " effective ways rapidly.By the user being watched the analysis of video custom, strengthen the analysis to user personality demand and behavior thereof.Use for the film program request, the architecture, film data modeling, the user interest preference model that have provided the personalized film recommendation service are studied, realization need not the user and inputs the required relevant individual character interest information of traditional recommend method and can return the film recommendation relevant with the current interest of user tabulation, proposed based on ontological film model, and set up the user interest preference model, provided in conjunction with the user profile feedback recommendation results being carried out adaptive adjustment algorithm in the recommendation process.
4, solve flow and expend excessive problem: carry out in real time traffic monitoring and flow analysis, give the prompting of user's certain flow by traffic monitoring, and monitoring state of network in the lump, adjust in real time the video of corresponding code stream, reduce the video flow loss; Flow situation analysis by the user uses provides foundation for operator specifies the preferential strategy of corresponding set meal.In a word, the proposition of this scheme and realization can greatly reduce loss and the mobile video of customer flow and watch cost, satisfy user benefit.
Description of drawings
Fig. 1 is the inventive method schematic flow sheet.
Fig. 2 is system principle diagram of the present invention.
Fig. 3 is video polymerization analysis cellular construction schematic diagram of the present invention.
Embodiment
The present invention will be further described below in conjunction with drawings and Examples.
As shown in Figure 1, present embodiment provides a kind of mobile video recommend method based on flow analysis and user behavior analysis, it is characterized in that:
Step S01: use reptile by the behavior of analog subscriber view site, from each large video website crawl video source;
Step S02: the meta information that extracts video;
Step S03: after this meta information is weighted Intelligent treatment, set up index, and storage administration unified in just described index;
Step S04: portable terminal gathers size, period, visual classification and the video length data that the user watches the flow of video;
Step S05: the data according to this portable terminal collection generate this user video recommendation strategy, and recommend policy update to be saved to a central database user video;
Step S06: when the user carries out the program request operation, pick out the video link that meets the user at present most according to the video element information of storing in the database, use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to this portable terminal in the described user video recommendation strategy simultaneously, offer the user and watch.
. be that homepage from each large video website begins to adopt multithreading recurrence crawl video source among the described step S01.
In an embodiment of the present invention, described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.Described power Intelligent treatment is according to the static prime information of video and video flow information, and video is carried out cluster, the line index of going forward side by side ordering; Along with the variation of video click volume and access times, adopt a predetermined time interval mode that video is carried out the secondary index collating sort; Each visual classification inside will be weighted ordering according to video multidate information and video flow information simultaneously; Described static prime information comprises label, title, classification and the brief introduction of video; Described video flow information comprises code check, size and the coded format of video; Described multidate information is click volume and the access times of video.
In order to guarantee the hommization of system, in the present embodiment, administrative staff can also interfere described index order by the weight of setting described prime information and flow information.In the present embodiment, system offers the user and watches and also possess multiple play mode and select, to cater to different user different type of machines viewing demand.This broadcast ratio mainly comprises: 16:9 pattern, 4:3 pattern, 1.85:1 pattern, 2.35:1 pattern and screen mode toggle.
Please refer to Fig. 2, the present invention also provides a kind of mobile video commending system based on flow analysis and user behavior analysis, it is characterized in that comprising:
One video polymerization analysis unit, this video polymerization analysis unit are responsible for from each large video website crawl video source, and extract the meta information of video, be weighted Intelligent treatment after, set up index, storage administration unified in the index of setting up the most at last;
One customer flow and behavioural analysis unit, this customer flow and behavioural analysis unit will be located at data that flow collection unit, user behavior collecting unit and the network bandwidth detection module of customer mobile terminal upload and generate this user video and recommend strategy, and recommend policy update to be saved to a central database user video;
One Service Management Unit, this Service Management Unit is mainly realized the service management of whole system, comprise video is examined issue, video resource is managed and manually participate in flow and user behavior analysis, recommend strategy to carry out manual intervention to the video that generates; And
One operation support interface unit, this operation support interface unit are the external unified interface of system, and it provides provider customer's flow inquiry service, the payment interface of the video of partly paying and the short multimedia message interface that the user is carried out the video recommendation.
Concrete, please refer to Fig. 3, in the present embodiment, described video polymerization analysis unit comprises:
One video handling module, this video handling module use reptile by the behavior of analog subscriber view site, begin to adopt multithreading recurrence crawl video source from the homepage of each large video website;
One video content analysis module for the meta information of the video that extracts described video handling module crawl, and after being weighted Intelligent treatment, is set up index, and storage administration unified in the index of setting up the most at last; And
One video intelligent real-time transcoding and Streaming Media handover module, this video intelligent real-time transcoding and Streaming Media handover module are picked out the video link that meets the user at present most according to the video element information of storing in the database, to recommend tactful portable terminal to use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to the family video simultaneously, and offer the user and watch.In the present embodiment, described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.
In an embodiment of the present invention, described weighting Intelligent treatment: be that these information will directly be set up inverted index according to these information by system with the static prime information as video such as the label of video, title, classification, brief introduction; The code check of video, size, coded format etc. are the flow information of video; The click volume of video and access times are multidate informations; System at first in static prime information and video flow information according to video, carries out cluster to video, the line index of going forward side by side ordering, and this Index process, the operation personnel can by the artificial weight of setting prime information and flow information, interfere this index order.Variation along with video click volume and access times, the present embodiment system can adopt by 1 day, 3 days, the week interval mode video is carried out the secondary index collating sort, as: visual classification is video code flow＞1Mbs, video size 〉=video of 100MB, at present access times＞=1000 visual classification=actions gathers, and the rest may be inferred for other visual classifications; Each visual classification inside will be weighted ordering (this weight operation personnel still can adjust interference in operation) according to video multidate information and video flow information simultaneously.
Can sum up, advantage of the present invention is as follows:
1, by native system and telecom operators' degree of depth cooperation, can exclusively provide the flow discount: call idle resource between telecom operators' net, when vitalizing the idle resource, for the user obtains discount (the flow discount can reach 5 foldings) under 2G/3G networking state.
2, break video website door pattern, be user's recommendation of providing personalized service: (1) watches behavior for user's history, the interested content of personalized recommendation user; (2) agree with the practical work focus, the very first time pushes the added prompting of popular video to the user.
3, abundant video content source provides one-stop service: enlist the services of the mainstream media video resource, the combination by popular search, individual character recommendation, association's search isotype realizes the magnanimity video playback based on this platform.
4, multiple play mode is selected, and caters to different user different type of machines viewing demand: provide 5 kinds of broadcast ratios mainly to comprise: 16:9 pattern, 4:3 pattern, 1.85:1 pattern, 2.35:1 pattern and screen mode toggle.
5, based on flow consumption sensitiveness, provide traffic monitoring and inquiry service: take sky/moon as the unit interval, realize the statistics to data flow use value, the while is added up preferential value according to the idle use traffic.
The above only is preferred embodiment of the present invention, and all equalizations of doing according to the present patent application claim change and modify, and all should belong to covering scope of the present invention.
Claims (9)
1. mobile video recommend method based on flow analysis and user behavior analysis is characterized in that:
Step S01: use reptile by the behavior of analog subscriber view site, from each large video website crawl video source;
Step S02: the meta information that extracts video;
Step S03: after this meta information is weighted Intelligent treatment, set up index, and storage administration unified in just described index;
Step S04: portable terminal gathers size, period, visual classification and the video length data that the user watches the flow of video;
Step S05: the data according to this portable terminal collection generate this user video recommendation strategy, and recommend policy update to be saved to a central database user video;
Step S06: when the user carries out the program request operation, pick out the video link that meets the user at present most according to the video element information of storing in the database, use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to this portable terminal in the described user video recommendation strategy simultaneously, offer the user and watch.
2. the mobile video recommend method based on flow analysis and user behavior analysis according to claim 1 is characterized in that: be that homepage from each large video website begins to adopt multithreading recurrence crawl video source among the described step S01.
3. the mobile video recommend method based on flow analysis and user behavior analysis according to claim 1, it is characterized in that: described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.
4. the mobile video recommend method based on flow analysis and user behavior analysis according to claim 1, it is characterized in that: described power Intelligent treatment is according to the static prime information of video and video flow information, video is carried out cluster, the line index of going forward side by side ordering; Along with the variation of video click volume and access times, adopt a predetermined time interval mode that video is carried out the secondary index collating sort; Each visual classification inside will be weighted ordering according to video multidate information and video flow information simultaneously; Described static prime information comprises label, title, classification and the brief introduction of video; Described video flow information comprises code check, size and the coded format of video; Described multidate information is click volume and the access times of video.
5. the mobile video recommend method based on flow analysis and user behavior analysis according to claim 4, it is characterized in that: administrative staff can interfere described index order by the weight of setting described prime information and flow information.
6. mobile video commending system based on flow analysis and user behavior analysis is characterized in that comprising:
One video polymerization analysis unit, this video polymerization analysis unit are responsible for from each large video website crawl video source, and extract the meta information of video, be weighted Intelligent treatment after, set up index, storage administration unified in the index of setting up the most at last;
One customer flow and behavioural analysis unit, this customer flow and behavioural analysis unit will be located at data that flow collection unit, user behavior collecting unit and the network bandwidth detection module of customer mobile terminal upload and generate this user video and recommend strategy, and recommend policy update to be saved to a central database user video;
One Service Management Unit, this Service Management Unit is mainly realized the service management of whole system, comprise video is examined issue, video resource is managed and manually participate in flow and user behavior analysis, recommend strategy to carry out manual intervention to the video that generates; And
One operation support interface unit, this operation support interface unit are the external unified interface of system, and it provides provider customer's flow inquiry service, the payment interface of the video of partly paying and the short multimedia message interface that the user is carried out the video recommendation.
7. the mobile video commending system based on flow analysis and user behavior analysis according to claim 6, it is characterized in that: described video polymerization analysis unit comprises:
One video handling module, this video handling module use reptile by the behavior of analog subscriber view site, begin to adopt multithreading recurrence crawl video source from the homepage of each large video website;
One video content analysis module for the meta information of the video that extracts described video handling module crawl, and after being weighted Intelligent treatment, is set up index, and storage administration unified in the index of setting up the most at last; And
One video intelligent real-time transcoding and Streaming Media handover module, this video intelligent real-time transcoding and Streaming Media handover module are picked out the video link that meets the user at present most according to the video element information of storing in the database, to recommend tactful portable terminal to use the current bandwidth that reports with the video code flow of user video transcoding for optimum according to the family video simultaneously, and offer the user and watch.
8. the mobile video commending system based on flow analysis and user behavior analysis according to claim 6, it is characterized in that: described weighting intelligence place is static prime information and the video flow information according to video, video is carried out cluster, the line index of going forward side by side ordering; Along with the variation of video click volume and access times, adopt a predetermined time interval mode that video is carried out the secondary index collating sort; Each visual classification inside will be weighted ordering according to video multidate information and video flow information simultaneously; Described static prime information comprises label, title, classification and the brief introduction of video; Described video flow information comprises code check, size and the coded format of video; Described multidate information is click volume and the access times of video.
9. the mobile video commending system based on flow analysis and user behavior analysis according to claim 6, it is characterized in that: described meta information comprises title, label, click volume, classification, frame per second, code check, coded format and the code check of video.
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