CN105488154A - Theme application recommendation method and device - Google Patents
Theme application recommendation method and device Download PDFInfo
- Publication number
- CN105488154A CN105488154A CN201510850302.2A CN201510850302A CN105488154A CN 105488154 A CN105488154 A CN 105488154A CN 201510850302 A CN201510850302 A CN 201510850302A CN 105488154 A CN105488154 A CN 105488154A
- Authority
- CN
- China
- Prior art keywords
- user
- subject
- keyword
- subject categories
- user data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
Abstract
The invention claims a theme application recommendation method and device. The method comprises the following steps: acquiring user data corresponding to a user identification according to the user identification; analyzing the user data to extract key words in the user data; classifying the extracted key words according to the theme type to obtain the classified category set; analyzing the classified category set to determine the priority of the theme category, wherein the theme category comprises every theme application meeting the theme category; acquiring a target theme application in the theme category with the highest priority, wherein the target theme application is the application program with the highest weight value in the theme category with the highest priority; pushing the target theme application to a terminal device corresponding to the user identification. The theme application meeting the user requirement and user preference is obtained through the analysis of the user individual data, and the quality and efficiency of acquiring the theme application by the user are improved.
Description
Technical field
The disclosure relates to information sifting technology, particularly relates to a kind of subject application recommend method and device.
Background technology
Along with the fast development of network and infotech, the popularity rate of mobile terminal is more and more higher.
Preset the matic mould of acquiescence in current mobile terminal, if user changes the matic mould after wishing to start shooting, select in the matic mould that can provide at mobile terminal, or log in the website providing the matic mould to apply, select download voluntarily.Adopt preset Default Subject pattern, stereotyped, not high to the attractability of user, poor user experience; Selected the matic mould liked by user voluntarily, then need user to select in the matic mould of magnanimity, and the probability really choosing the matic mould self liked is not high.
disclosure
For overcoming Problems existing in correlation technique, the disclosure provides a kind of subject application recommend method and device, and described technical scheme is as follows:
According to the first aspect of disclosure embodiment, a kind of subject application recommend method is provided, comprises:
The user data corresponding with described user ID is obtained according to user ID;
Described user data is analyzed, extracts the keyword in described user data;
According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out;
Category set after described classification is analyzed, to determine the priority of described subject categories;
Each subject application meeting described subject categories is included in described subject categories;
Obtain the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority;
Push described target topic and be applied to terminal device corresponding to described user ID.
Optionally, described user data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
Optionally, described user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity; Accordingly, before the described user data corresponding with described user ID according to user ID acquisition, also comprise:
Set up user ID binding relationship table, correspond to each other to make user ID described in corresponding each unique with individual subscriber identity.
Optionally, describedly to analyze described user data, the keyword extracted in described user data comprises:
According to the label substance comprised in described subject categories, extract information corresponding with described label substance in described user data as described keyword;
Or, from described user data, extract keyword based on natural language processing NLP technology.
Optionally, described according to subject categories, the keyword extracted is sorted out, obtains the category set after sorting out and comprise:
According to subject categories, cluster analysis is carried out to the keyword extracted, each keyword is subdivided in each category set after cluster analysis.
Optionally, described cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.
Optionally, described category set after described classification to be analyzed, to determine the priority of described subject categories, comprising:
To in the category set after described classification comprise keyword quantity add up, according in category set comprise the quantity order from more to less of keyword, determine the priority height of the subject categories corresponding with described category set.
Optionally, before the target topic application in the subject categories that described acquisition priority is the highest, also comprise:
The weighted value of described subject application is determined according to the clicking rate of subject application, positive rating.
According to the second aspect of disclosure embodiment, a kind of subject application recommendation apparatus is provided, comprises:
First acquisition module, for obtaining the user data corresponding with described user ID according to user ID;
Analysis module, for analyzing described user data, extracts the keyword in described user data;
Classifying module, for according to subject categories, sorts out the keyword extracted, and obtains the category set after sorting out;
Determination module, for analyzing the category set after described classification, to determine the priority of described subject categories;
Each subject application meeting described subject categories is included in described subject categories;
Second acquisition module, for obtaining the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority;
Pushing module, is applied to terminal device corresponding to described user ID for pushing described target topic.
Optionally, described user data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
Optionally, described user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity; Accordingly, described device also comprises:
Setting up module, for setting up user ID binding relationship table, corresponding to each other to make user ID described in corresponding each unique with individual subscriber identity.
Optionally, described analysis module comprises:
First extracts submodule, for according to the label substance comprised in described subject categories, extracts information corresponding with described label substance in described user data as described keyword;
Second extracts submodule, for extracting keyword based on natural language processing NLP technology from described user data.
Optionally, described classifying module comprises:
Cluster submodule, for according to subject categories, carries out cluster analysis to the keyword extracted;
Divide submodule, for being subdivided into by each keyword in each category set after the cluster analysis of described cluster submodule.
Optionally, described cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.
Optionally, described determination module comprises:
Statistics submodule, in the category set after described classification comprise keyword quantity add up;
Determine submodule, for according in category set comprise the quantity order from more to less of keyword, determine the priority height of the subject categories corresponding with described category set.
Optionally, described device also comprises:
Weighted value determination module, determines the weighted value of described subject application for the clicking rate according to subject application, positive rating.
According to the third aspect of disclosure embodiment, a kind of subject application recommendation apparatus is provided, comprises:
Processor;
For storing the storer of the executable instruction of described processor;
Wherein, described processor is used for obtaining the user data corresponding with described user ID according to user ID; Described user data is analyzed, extracts the keyword in described user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after described classification is analyzed, to determine the priority of described subject categories; Each subject application meeting described subject categories is included in described subject categories; Obtain the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority; Push described target topic and be applied to terminal device corresponding to described user ID.
The method that embodiment of the present disclosure provides and device can comprise following beneficial effect:
In one embodiment, by obtaining the user data corresponding with user ID according to user ID; This user data is analyzed, extracts the keyword in user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after sorting out is analyzed, to determine the priority of subject categories; Wherein, each subject application meeting this subject categories is included in subject categories; Obtain the target topic application in the highest subject categories of priority, this target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority; Push this target topic and be applied to terminal device corresponding to user ID.Achieve and draw according to user individual data analysis the subject application meeting user's request, hobby, improve quality and efficiency that user obtains subject application.
In another embodiment, user data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.Thus make that the coverage of user data is wide, type is many, contribute to going out as far as possible accurately from large extracting data, comprehensive user personalized information, improve the recommendation quality of subject application.
In another embodiment, user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity; By setting up user ID binding relationship table, correspond to each other to make each corresponding user ID unique with individual subscriber identity.Thus get user data as much as possible according to each user ID of binding, make that the coverage of user data expands, type increases, contribute to going out accurate as far as possible, comprehensive user personalized information from large extracting data, improve the recommendation quality of subject application.
In another embodiment, by according to the label substance comprised in subject categories, information corresponding with label substance in user data is extracted as keyword; Or, from user data, extract keyword based on natural language processing NLP technology.Thus the extraction efficiency improved useful information in user data, and then improve the efficiency recommending user individual subject application.
In another embodiment, by according to subject categories, cluster analysis is carried out to the keyword extracted, each keyword is subdivided in each category set after cluster analysis, thus effectively improve the classification accuracy of category set, and then improve the accuracy of the interested subject categories of consumer positioning.
In another embodiment, cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.Thus provide diversified clustering method, to adapt to different clustered demand.
In another embodiment, the quantity that institute in the category set after sorting out comprises keyword is added up, according in category set comprise the quantity order from more to less of keyword, determine the priority of the subject categories corresponding with category set just.Thus for user provides, matching is better, quality is higher, and the subject application of demand of being more close to the users.
In another embodiment, by the weighted value of the clicking rate according to subject application, positive rating determination subject application, thus the subject application providing quality higher for user.
Should be understood that, it is only exemplary and explanatory that above general description and details hereinafter describe, and can not limit the disclosure.
Accompanying drawing explanation
Accompanying drawing to be herein merged in instructions and to form the part of this instructions, shows and meets embodiment of the present disclosure, and is used from instructions one and explains principle of the present disclosure.
Fig. 1 is the process flow diagram of a kind of subject application recommend method according to an exemplary embodiment;
Fig. 2 is the process flow diagram of a kind of subject application recommend method according to another exemplary embodiment;
Fig. 3 is the block diagram of a kind of subject application recommendation apparatus according to an exemplary embodiment;
Fig. 4 is the block diagram of a kind of subject application recommendation apparatus according to another exemplary embodiment;
Fig. 5 is the block diagram of a kind of subject application recommendation apparatus 500 according to an exemplary embodiment.
Embodiment
Here will be described exemplary embodiment in detail, its sample table shows in the accompanying drawings.When description below relates to accompanying drawing, unless otherwise indicated, the same numbers in different accompanying drawing represents same or analogous key element.Embodiment described in following exemplary embodiment does not represent all embodiments consistent with the disclosure.On the contrary, they only with as in appended claims describe in detail, the example of apparatus and method that aspects more of the present disclosure are consistent.
Fig. 1 is the process flow diagram of a kind of subject application recommend method according to an exemplary embodiment, as shown in Figure 1, the present embodiment is applied in terminal (client device) with this subject application recommend method and illustrates, such as, computer end, mobile terminal device, as PAD, mobile phone and all electronic equipments etc. with display interface.For mobile terminal, the theme shown after being provided with start in it, theme by the interface can embodying style, comprising the color of window, the Composition of contents such as layout, icon style of control, by changing these vision contents to reach the object at enhancement system interface.Such as, theme can comprise style, desktop wallpaper, screen protection, mouse pointer, system sounds event, icon etc., and wherein, style contains again the key element such as outward appearance as the outward appearance of window, font, color, button.Different themes makes mobile terminal present different styles, and then embodies hobby and the individual character of mobile terminal user individual, enriches and meet people day by day to extend and visual effect a kind of vision of mobile terminal monotonicity.Theme is normally in the terminal preset or downloaded by user according to personal like and install subject application and formed by subject application before mobile terminal dispatches from the factory by equipment vendor.
The method of the present embodiment comprises the following steps:
In a step 101, the user data corresponding with user ID is obtained according to user ID.
User ID is the information for identifying user identity, and same user can have multiple user ID, and such as: user logs in different application programs by mobile terminal, each application program can a corresponding mark, as login account; Can also be all identification informations for identifying user identity such as Bank Account Number, phone number of user.By these user ID, the user data produced in the different application environment corresponding to it can be got.Such as: user logs in micro-letter application platform by micro-signal code, browses on the platform and releases news, then the information that the above-mentioned user associated with this user's micro-signal code is browsed and the information that user issues just can be obtained by as user data is collected.It should be noted that the acquisition of above-mentioned user data needs according to whether determining through subscriber authorisation.
In a step 102, user data is analyzed, extract the keyword in user data.
The user data got is analyzed, such as, gets the geographical location information of user, place name can be extracted as keyword; According to customer consumption record, the name can extracting the businessman that user consumes is referred to as keyword; According to the content of microblog that user issues, in extraction content of microblog, subject content is as keyword etc.
In step 103, according to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out.
Subject categories is the theme the category division that application provider carries out according to the style of stored subject application.Such as subject categories can comprise star, cuisines, travelling, leisure, landscape, automobile, animation etc.According to subject categories, the scattered key word information extracted in a step 102 is included in corresponding subject categories, obtain the category set after sorting out, can include the keyword of varying number in each category set, keyword also can repeat in the category set of multiple classification.Such as: the keyword got has: KFC, Pizza Hut, cinema, the Forbidden City etc., then possiblely to classify as: theme as in the classification of cuisines and include { KFC, Pizza Hut }; Include { KFC, Pizza Hut, cinema, the Forbidden City } in the classification of leisure; Include { the Forbidden City } etc. in the classification of tourism.
At step 104, the category set after classification is analyzed, to determine the priority of subject categories.
As a rule, so-called user individual refers to the embodiment having oneself speciality on popular basis, its avatar can be embodied by the usual behavior of user, as the type of merchandise often bought, the topic often browsed, the frequent film watched etc., therefore, by analyzing each category set, analyze the interest place of user, and then according to the level of interest of user, obtain the subject categories priority of each category set.
In step 105, obtain the target topic application in the highest subject categories of priority, target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority.
Each subject application meeting subject categories is included in subject categories, after determining the subject categories that user is most interested in, need in this subject categories, select a subject application and recommend user, the mode of selection can be applied as this target topic by obtaining the subject application that in this subject categories, weighted value is the highest.This weighted value can be that the overall target such as number of times, clicking rate, positive rating be downloaded according to this theme carries out evaluating obtaining, also can be carry out assessing obtaining according to the use habit of individual subscriber, such as, each subject application in the style of the subject application once bought according to user or downloaded and the subject categories of the current limit priority selected compares, and calculates the weighted value of each subject application.
In step 106, push target topic and be applied to terminal device corresponding to user ID.
Propelling movement mode can be: when user places an order and buys mobile terminal device, by analyzing user data, is preloaded onto in the mobile device corresponding to this user ID by target topic application; Or interval predetermined period, by the information obtained after the Users'Data Analysis in predetermined period, initiatively pushes new target topic application to user, according to the hobby of different times, can upgrade the theme of mobile terminal at any time to make user.
In sum, the subject application recommend method that the present embodiment provides, by obtaining the user data corresponding with user ID according to user ID; This user data is analyzed, extracts the keyword in user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after sorting out is analyzed, to determine the priority of subject categories; Wherein, each subject application meeting this subject categories is included in subject categories; Obtain the target topic application in the highest subject categories of priority, this target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority; Push this target topic and be applied to terminal device corresponding to user ID.Achieve and draw according to user individual data analysis the subject application meeting user's request, hobby, improve quality and efficiency that user obtains subject application.
Fig. 2 is the process flow diagram of a kind of subject application recommend method according to another exemplary embodiment, as shown in Figure 2, the present embodiment is applied in terminal (client device) with this subject application recommend method and illustrates, the implementation that can there is multiple combination embodiment illustrated in fig. 1, below be only described for one combination implementation wherein: on the basis of a upper embodiment, the method for the present embodiment comprises the following steps:
In step 201, set up user ID binding relationship table, correspond to each other to make each corresponding user ID unique with individual subscriber identity.
User ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity.Mobile terminal identification can be phone number, the subscriber identification card number (SubscriberIdentityModule of user, be called for short " SIM "), international mobile subscriber identity (InternationalMobileSubscriberIdentificationNumber, be called for short " IMSI ") etc.Set up the incidence relation between each user ID independent of each other, make scattered user ID corresponding with same user identity, thus make the relation that corresponds to each other having possessed binding between each user ID.The user data that user adopts the arbitrary user ID in this binding relationship table to produce can be positioned as the user data of same user identity.
In step 202., the user data corresponding with user ID is obtained according to user ID.
User data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
In step 203, user data is analyzed, extract the keyword in user data.
The realization of this step can be passed through, and according to the label substance comprised in subject categories, extracts information corresponding with label substance in user data as keyword.Usually the label substance embodying this subject categories is comprised in a subject categories, also the label substance embodying this subject application style or key element is usually included in each subject application, according to label substance, user data is screened, effectively can improve the extraction efficiency of key message in user data, and then improve the efficiency recommending user individual subject application.Such as: the label occurred in subject categories is " landscape " has " sea ", " Aegean ", " sandy beach "; And have in user data: to the searching record etc. of search location " Greece " when wedding gauze kerchief purchaser record, tour site are browsed, " sea ", " Aegean ", " sandy beach " usually and marriage scene there is incidence relation, then the keyword that " wedding gauze kerchief ", " Greece " in user data etc. obtains as semantic association can be extracted.These are only citing, be that the semantic matches of mass data and the technology of semantic association are applied according to label substance to selecting of keyword in practical operation, the application does not do concrete restriction to this.
Or this step can also be passed through, from user data, extract keyword based on natural language processing NLP (naturallanguageprocessing is called for short " NLP ") technology.Being picked out by the keyword meeting natural language in user data by NLP technology, is coherent between select word and word, words border define a kind of best of breed adopting and context can be allowed the most clear and the most coherent and errorless in the syntax.
In step 204, according to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out.
Specifically by according to subject categories, cluster analysis can be carried out to the keyword extracted, each keyword is subdivided in each category set after cluster analysis.Optionally, cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.Cluster analysis is a concept in data mining, and it is the process set of physics or abstract object being divided into the multiple classes be made up of similar object.Element in each category set obtained by cluster analysis, it has certain approximate or similar feature to each other.Cluster analysis effectively can improve the classification accuracy of category set, and then improves the accuracy of the interested subject categories of consumer positioning.Meanwhile, diversified clustering method, also can be used for adapting to different clustered demand.Such as, K-mean algorithm algorithm is quick and simple, is applicable to carry out high efficiency process to large-scale dataset.This algorithm can be adopted to carry out cluster analysis when the keyword enormous amount extracted.
In step 205, the category set after classification is analyzed, to determine the priority of subject categories.
Specifically can be added up by the quantity comprising keyword to institute in the category set after sorting out, according in category set comprise the quantity order from more to less of keyword, determine the priority of the subject categories corresponding with category set just.Usually when user is interested in a certain theme, also can correspondingly increase to the visit capacity that this theme associates, accordingly, the quantity of the keyword associated with this theme also can growth at double.Therefore, by keyword number quantitative statistics in category set, the priority of subject categories interested to user is determined fast.Meanwhile, the method only needs the quantity of application summation algorithm to keyword to add up, and algorithm is simple, and treatment effeciency is high, contributes to determining priority-level fast.
In step 206, according to the clicking rate of subject application, the weighted value of positive rating determination subject application.
The provider of subject application can the positive rating after server end uses the clicking rate of subject application and user add up, to determine the weighted value of each subject application, thus the subject application providing quality high for user, promote Consumer's Experience.The height of weighted value can also by analyzing the use habit of individual subscriber, and assessment obtains.Such as, each subject application in the style of subject application once bought according to user or downloaded and the subject categories of the current limit priority selected compares, and calculates the weighted value of each subject application.Such as, user bought 3 Dynamic Themes, 2 musical themes, 1 small icon layout theme, then the weighted value of Dynamic Theme in each theme in the subject categories of the current limit priority selected can be increased by 3; Music categories topic weights value increases by 2; Small icon layout topic weights value increases by 1.Thus to determine and the subject application selecting weighted value high is pushed to user.
In step 207, obtain the target topic application in the highest subject categories of priority, target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority.
In a step 208, push target topic and be applied to terminal device corresponding to user ID.
In sum, the subject application recommend method that the present embodiment provides, further by the multiple user ID of binding, to get user data as much as possible, make that the coverage of user data expands, type increases, contribute to going out accurate as far as possible, comprehensive user personalized information from large extracting data, improve the recommendation quality of subject application; By extracting keyword according to label substance or based on natural language processing NLP technology from user data, improve the extraction efficiency to useful information in user data, and then improve the efficiency recommending user individual subject application; Cluster analysis is carried out further by the keyword extracted, scattered keyword is sorted out and forms category set, effectively improve the accuracy of category set classification, and by category set comprise keyword quantity add up, determine the priority of the interested subject categories of user, and by the weighted value of each subject application in the subject categories that priority is the highest, determine and meet user's request most and the high subject application of quality.The method achieve and draw according to user individual data analysis the subject application meeting user's request, hobby, improve quality and efficiency that user obtains subject application.
Following is disclosure device embodiment, may be used for performing disclosure embodiment of the method.For the details do not disclosed in disclosure device embodiment, please refer to disclosure embodiment of the method.
Fig. 3 is the block diagram of a kind of subject application recommendation apparatus according to an exemplary embodiment, and this subject application recommendation apparatus can realize becoming the some or all of of electronic equipment by software, hardware or both combinations.This subject application recommendation apparatus can comprise:
First acquisition module 31, for obtaining the user data corresponding with user ID according to user ID.
Analysis module 32, for analyzing user data, extracts the keyword in user data.
Classifying module 33, for according to subject categories, sorts out the keyword extracted, and obtains the category set after sorting out.
Determination module 34, for analyzing the category set after classification, to determine the priority of subject categories.
Wherein, each subject application meeting subject categories is included in subject categories.
Second acquisition module 35, for obtaining the target topic application in the highest subject categories of priority, target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority.
Pushing module 36, is applied to terminal device corresponding to user ID for pushing target topic.
In sum, the subject application recommendation apparatus that the present embodiment provides, by obtaining the user data corresponding with user ID according to user ID; This user data is analyzed, extracts the keyword in user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after sorting out is analyzed, to determine the priority of subject categories; Wherein, each subject application meeting this subject categories is included in subject categories; Obtain the target topic application in the highest subject categories of priority, this target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority; Push this target topic and be applied to terminal device corresponding to user ID.Achieve and draw according to user individual data analysis the subject application meeting user's request, hobby, improve quality and efficiency that user obtains subject application.
Fig. 4 is the block diagram of a kind of subject application recommendation apparatus according to another exemplary embodiment, and this subject application recommendation apparatus can realize becoming the some or all of of electronic equipment by software, hardware or both combinations.Based on said apparatus embodiment,
User data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
Optionally, user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity; Accordingly, device also comprises:
Setting up module 37, for setting up user ID binding relationship table, corresponding to each other to make each corresponding user ID unique with individual subscriber identity.
Optionally, analysis module 32 comprises:
First extracts submodule 321, for according to the label substance comprised in subject categories, extracts information corresponding with label substance in user data as keyword.
Second extracts submodule 322, for extracting keyword based on natural language processing NLP technology from user data.
Optionally, classifying module 33 comprises:
Cluster submodule 331, for according to subject categories, carries out cluster analysis to the keyword extracted.
Divide submodule 332, for being subdivided into by each keyword in each category set after the cluster analysis of cluster submodule.
Optionally, cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.
Optionally, determination module 34 comprises:
Statistics submodule 341, for sort out after category set in comprise keyword quantity add up.
Determine submodule 342, for according in category set comprise the quantity order from more to less of keyword, determine the priority height of the subject categories corresponding with category set.
Optionally, this device also comprises:
Weighted value determination module 38, for the weighted value of the clicking rate according to subject application, positive rating determination subject application.
About the device in above-described embodiment, wherein the concrete mode of modules executable operations has been described in detail in about the embodiment of the method, will not elaborate explanation herein.
Fig. 5 is the block diagram of a kind of subject application recommendation apparatus 500 according to an exemplary embodiment.Such as, subject application recommendation apparatus 500 can be mobile phone, computing machine, digital broadcast terminal, messaging devices, game console, tablet device, Medical Devices, body-building equipment, personal digital assistant, router, telegon etc.
With reference to Fig. 5, device 500 can comprise following one or more assembly: processing components 502, storer 504, electric power assembly 506, multimedia groupware 508, audio-frequency assembly 510, the interface 512 of I/O (I/O), sensor module 514, and communications component 516.
The integrated operation of the usual control device 500 of processing components 502, such as with display, call, data communication, camera operation and record operate the operation be associated.Processing components 502 can comprise one or more processor 520 to perform instruction, to complete all or part of step of above-mentioned method.In addition, processing components 502 can comprise one or more module, and what be convenient between processing components 502 and other assemblies is mutual.Such as, processing components 502 can comprise multi-media module, mutual with what facilitate between multimedia groupware 508 and processing components 502.
Storer 504 is configured to store various types of data to be supported in the operation of device 500.The example of these data comprises the instruction of any application program for operating on device 500 or method, contact data, telephone book data, message, picture, video etc.Storer 504 can be realized by the volatibility of any type or non-volatile memory device or their combination, as static RAM (SRAM), Electrically Erasable Read Only Memory (EEPROM), Erasable Programmable Read Only Memory EPROM (EPROM), programmable read only memory (PROM), ROM (read-only memory) (ROM), magnetic store, flash memory, disk or CD.
The various assemblies that electric power assembly 506 is device 500 provide electric power.Electric power assembly 506 can comprise power-supply management system, one or more power supply, and other and the assembly generating, manage and distribute electric power for device 500 and be associated.
Multimedia groupware 508 is included in the screen providing an output interface between described device 500 and user.In certain embodiments, screen can comprise liquid crystal display (LCD) and touch panel (TP).If screen comprises touch panel, screen may be implemented as touch-screen, to receive the input signal from user.Touch panel comprises one or more touch sensor with the gesture on sensing touch, slip and touch panel.Described touch sensor can the border of not only sensing touch or sliding action, but also detects the duration relevant to described touch or slide and pressure.In certain embodiments, multimedia groupware 508 comprises a front-facing camera and/or post-positioned pick-up head.When device 500 is in operator scheme, during as screening-mode or video mode, front-facing camera and/or post-positioned pick-up head can receive outside multi-medium data.Each front-facing camera and post-positioned pick-up head can be fixing optical lens systems or have focal length and optical zoom ability.
Audio-frequency assembly 510 is configured to export and/or input audio signal.Such as, audio-frequency assembly 510 comprises a microphone (MIC), and when device 500 is in operator scheme, during as call model, logging mode and speech recognition mode, microphone is configured to receive external audio signal.The sound signal received can be stored in storer 504 further or be sent via communications component 516.In certain embodiments, audio-frequency assembly 510 also comprises a loudspeaker, for output audio signal.
I/O interface 512 is for providing interface between processing components 502 and peripheral interface module, and above-mentioned peripheral interface module can be keyboard, some striking wheel, button etc.These buttons can include but not limited to: home button, volume button, start button and locking press button.
Sensor module 514 comprises one or more sensor, for providing the state estimation of various aspects for device 500.Such as, sensor module 514 can detect the opening/closing state of device 500, the relative positioning of assembly, such as described assembly is display and the keypad of device 500, the position of all right pick-up unit 500 of sensor module 514 or device 500 1 assemblies changes, the presence or absence that user contacts with device 500, the temperature variation of device 500 orientation or acceleration/deceleration and device 500.Sensor module 514 can comprise proximity transducer, be configured to without any physical contact time detect near the existence of object.Sensor module 514 can also comprise optical sensor, as CMOS or ccd image sensor, for using in imaging applications.In certain embodiments, this sensor module 514 can also comprise acceleration transducer, gyro sensor, Magnetic Sensor, pressure transducer or temperature sensor.
Communications component 516 is configured to the communication being convenient to wired or wireless mode between device 500 and other equipment.Device 500 can access the wireless network based on communication standard, as WiFi, 2G or 3G, or their combination.In one exemplary embodiment, communications component 516 receives from the broadcast singal of external broadcasting management system or broadcast related information via broadcast channel.In one exemplary embodiment, described communications component 516 also comprises near-field communication (NFC) module, to promote junction service.Such as, can based on radio-frequency (RF) identification (RFID) technology in NFC module, Infrared Data Association (IrDA) technology, ultra broadband (UWB) technology, bluetooth (BT) technology and other technologies realize.
In the exemplary embodiment, device 500 can be realized, for performing said method by one or more application specific integrated circuit (ASIC), digital signal processor (DSP), digital signal processing appts (DSPD), programmable logic device (PLD) (PLD), field programmable gate array (FPGA), controller, microcontroller, microprocessor or other electronic components.
In the exemplary embodiment, additionally provide a kind of non-transitory computer-readable recording medium comprising instruction, such as, comprise the storer 504 of instruction, above-mentioned instruction can perform said method by the processor 520 of device 500.Such as, described non-transitory computer-readable recording medium can be ROM, random access memory (RAM), CD-ROM, tape, floppy disk and optical data storage devices etc.
A kind of non-transitory computer-readable recording medium, when the instruction in described storage medium is performed by the processor of mobile terminal, make mobile terminal can perform a kind of subject application recommend method, described method comprises:
Storer 504, for the executable instruction of storage of processor 520; Processor 520, for obtaining the user data corresponding with user ID according to user ID; User data is analyzed, extracts the keyword in user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after sorting out is analyzed, to determine the priority of subject categories; Each subject application meeting subject categories is included in subject categories; Obtain the target topic application in the highest subject categories of priority, target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of priority; Push target topic and be applied to terminal device corresponding to user ID.
Should be understood that, the disclosure is not limited to precision architecture described above and illustrated in the accompanying drawings, and can carry out various amendment and change not departing from its scope.The scope of the present disclosure is only limited by appended claim.
Claims (17)
1. a subject application recommend method, is characterized in that, comprising:
The user data corresponding with described user ID is obtained according to user ID;
Described user data is analyzed, extracts the keyword in described user data;
According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out;
Category set after described classification is analyzed, to determine the priority of described subject categories;
Each subject application meeting described subject categories is included in described subject categories;
Obtain the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority;
Push described target topic and be applied to terminal device corresponding to described user ID.
2. method according to claim 1, is characterized in that, described user data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
3. method according to claim 1, is characterized in that, described user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity;
Accordingly, before the described user data corresponding with described user ID according to user ID acquisition, also comprise:
Set up user ID binding relationship table, correspond to each other to make user ID described in corresponding each unique with individual subscriber identity.
4. method according to claim 1, is characterized in that, describedly analyzes described user data, and the keyword extracted in described user data comprises:
According to the label substance comprised in described subject categories, extract information corresponding with described label substance in described user data as described keyword;
Or, from described user data, extract keyword based on natural language processing NLP technology.
5. method according to claim 1, is characterized in that, described according to subject categories, sorts out the keyword extracted, and obtains the category set after sorting out and comprises:
According to subject categories, cluster analysis is carried out to the keyword extracted, each keyword is subdivided in each category set after cluster analysis.
6. method according to claim 5, is characterized in that, described cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.
7. method according to claim 1, is characterized in that, describedly analyzes the category set after described classification, to determine the priority of described subject categories, comprising:
To in the category set after described classification comprise keyword quantity add up, according in category set comprise the quantity order from more to less of keyword, determine the priority height of the subject categories corresponding with described category set.
8. method according to claim 1, is characterized in that, before the target topic application in the subject categories that described acquisition priority is the highest, also comprises:
The weighted value of described subject application is determined according to the clicking rate of subject application, positive rating.
9. a subject application recommendation apparatus, is characterized in that, comprising:
First acquisition module, for obtaining the user data corresponding with described user ID according to user ID;
Analysis module, for analyzing described user data, extracts the keyword in described user data;
Classifying module, for according to subject categories, sorts out the keyword extracted, and obtains the category set after sorting out;
Determination module, for analyzing the category set after described classification, to determine the priority of described subject categories;
Each subject application meeting described subject categories is included in described subject categories;
Second acquisition module, for obtaining the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority;
Pushing module, is applied to terminal device corresponding to described user ID for pushing described target topic.
10. device according to claim 9, is characterized in that, described user data comprises at least one item number certificate in the following: geographic information data, trading information data, social platform data, registration information data.
11. devices according to claim 9, is characterized in that, described user ID comprises at least one item in the following: social platform account, communicating number, carry out bank's card number, the mobile terminal identification of binding with individual subscriber identity; Accordingly, described device also comprises:
Setting up module, for setting up user ID binding relationship table, corresponding to each other to make user ID described in corresponding each unique with individual subscriber identity.
12. devices according to claim 9, is characterized in that, described analysis module comprises:
First extracts submodule, for according to the label substance comprised in described subject categories, extracts information corresponding with described label substance in described user data as described keyword;
Second extracts submodule, for extracting keyword based on natural language processing NLP technology from described user data.
13. devices according to claim 9, is characterized in that, described classifying module comprises:
Cluster submodule, for according to subject categories, carries out cluster analysis to the keyword extracted;
Divide submodule, for being subdivided into by each keyword in each category set after the cluster analysis of described cluster submodule.
14. devices according to claim 13, is characterized in that, described cluster analysis comprises following at least one: K-mean algorithm, two-step approach TwoStep cluster.
15. devices according to claim 9, is characterized in that, described determination module comprises:
Statistics submodule, in the category set after described classification comprise keyword quantity add up;
Determine submodule, for according in category set comprise the quantity order from more to less of keyword, determine the priority height of the subject categories corresponding with described category set.
16. devices according to claim 9, is characterized in that, described device also comprises:
Weighted value determination module, determines the weighted value of described subject application for the clicking rate according to subject application, positive rating.
17. 1 kinds of subject application recommendation apparatus, is characterized in that, comprising:
Processor;
For storing the storer of the executable instruction of described processor;
Wherein, described processor is used for obtaining the user data corresponding with described user ID according to user ID; Described user data is analyzed, extracts the keyword in described user data; According to subject categories, the keyword extracted is sorted out, obtain the category set after sorting out; Category set after described classification is analyzed, to determine the priority of described subject categories; Each subject application meeting described subject categories is included in described subject categories; Obtain the target topic application in the highest subject categories of priority, described target topic is applied as the subject application with highest weight weight values comprised in the highest subject categories of described priority; Push described target topic and be applied to terminal device corresponding to described user ID.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510850302.2A CN105488154A (en) | 2015-11-28 | 2015-11-28 | Theme application recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510850302.2A CN105488154A (en) | 2015-11-28 | 2015-11-28 | Theme application recommendation method and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105488154A true CN105488154A (en) | 2016-04-13 |
Family
ID=55675128
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510850302.2A Pending CN105488154A (en) | 2015-11-28 | 2015-11-28 | Theme application recommendation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105488154A (en) |
Cited By (23)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106060762A (en) * | 2016-05-24 | 2016-10-26 | 中国联合网络通信集团有限公司 | Information pushing method, information pushing device and information pushing system |
| CN106569860A (en) * | 2016-11-04 | 2017-04-19 | 广东欧珀移动通信有限公司 | Application management method and terminal |
| CN106653057A (en) * | 2016-09-30 | 2017-05-10 | 北京智能管家科技有限公司 | Data processing method and apparatus |
| CN107622074A (en) * | 2016-07-15 | 2018-01-23 | 北京搜狗科技发展有限公司 | A kind of data processing method, device and computing device |
| WO2018018639A1 (en) * | 2016-07-29 | 2018-02-01 | 深圳市沃特沃德股份有限公司 | Pet application information pushing method and device |
| CN107665442A (en) * | 2017-05-10 | 2018-02-06 | 平安科技（深圳）有限公司 | Obtain the method and device of targeted customer |
| CN107704512A (en) * | 2017-08-31 | 2018-02-16 | 平安科技（深圳）有限公司 | Financial product based on social data recommends method, electronic installation and medium |
| CN107742240A (en) * | 2017-09-30 | 2018-02-27 | 北京金山安全软件有限公司 | Theme application pushing method, device and system |
| CN107767273A (en) * | 2017-09-05 | 2018-03-06 | 平安科技（深圳）有限公司 | Asset Allocation method, electronic installation and medium based on social data |
| CN107979687A (en) * | 2017-10-31 | 2018-05-01 | 维沃移动通信有限公司 | A kind of wallpaper switching method, mobile terminal |
| CN108021619A (en) * | 2017-11-13 | 2018-05-11 | 星潮闪耀移动网络科技（中国）有限公司 | A kind of event description object recommendation method and device |
| CN109033263A (en) * | 2018-07-09 | 2018-12-18 | 努比亚技术有限公司 | A kind of application recommended method and terminal |
| CN110083774A (en) * | 2019-05-10 | 2019-08-02 | 腾讯科技（深圳）有限公司 | Using determination method, apparatus, computer equipment and the storage medium of recommendation list |
| CN110362376A (en) * | 2019-07-18 | 2019-10-22 | 北京小米移动软件有限公司 | A kind of method, apparatus and storage medium that electronic apparatus system theme style is set |
| CN110879868A (en) * | 2019-11-21 | 2020-03-13 | 中国工商银行股份有限公司 | Consultant scheme generation method, device, system, electronic equipment and medium |
| CN110889036A (en) * | 2019-10-31 | 2020-03-17 | 深圳市微立德科技有限公司 | Multi-dimensional information processing method and device and terminal equipment |
| CN111158832A (en) * | 2019-12-31 | 2020-05-15 | 中国银行股份有限公司 | Theme skin changing method and device for mobile banking application |
| CN111163228A (en) * | 2019-12-31 | 2020-05-15 | 中国银行股份有限公司 | Bank software function interface generation method and device |
| CN111259259B (en) * | 2020-03-11 | 2021-03-30 | 郑州工程技术学院 | University student news recommendation method, device, equipment and storage medium |
| CN112948528A (en) * | 2021-03-02 | 2021-06-11 | 北京秒针人工智能科技有限公司 | Data classification method and system based on keywords |
| WO2021116850A1 (en) * | 2019-12-11 | 2021-06-17 | International Business Machines Corporation | Grouping users of a mobile network |
| WO2021217470A1 (en) * | 2020-04-29 | 2021-11-04 | Citrix Systems, Inc. | Computer resource allocation based on categorizing computing processes |
| CN114979097A (en) * | 2021-06-03 | 2022-08-30 | 中移互联网有限公司 | MQTT-based message pushing method and device and electronic equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103886090A (en) * | 2014-03-31 | 2014-06-25 | 北京搜狗科技发展有限公司 | Content recommendation method and device based on user favorites |
| CN104283842A (en) * | 2013-07-02 | 2015-01-14 | 中兴通讯股份有限公司 | Theme management method and system |
| CN104361062A (en) * | 2014-11-03 | 2015-02-18 | 百度在线网络技术（北京）有限公司 | Associated information recommendation method and device |
-
2015
- 2015-11-28 CN CN201510850302.2A patent/CN105488154A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104283842A (en) * | 2013-07-02 | 2015-01-14 | 中兴通讯股份有限公司 | Theme management method and system |
| CN103886090A (en) * | 2014-03-31 | 2014-06-25 | 北京搜狗科技发展有限公司 | Content recommendation method and device based on user favorites |
| CN104361062A (en) * | 2014-11-03 | 2015-02-18 | 百度在线网络技术（北京）有限公司 | Associated information recommendation method and device |
Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106060762A (en) * | 2016-05-24 | 2016-10-26 | 中国联合网络通信集团有限公司 | Information pushing method, information pushing device and information pushing system |
| CN106060762B (en) * | 2016-05-24 | 2020-03-13 | 中国联合网络通信集团有限公司 | Information pushing method, information pushing device and information pushing system |
| CN107622074A (en) * | 2016-07-15 | 2018-01-23 | 北京搜狗科技发展有限公司 | A kind of data processing method, device and computing device |
| CN107622074B (en) * | 2016-07-15 | 2022-04-19 | 北京搜狗科技发展有限公司 | Data processing method and device and computing equipment |
| WO2018018639A1 (en) * | 2016-07-29 | 2018-02-01 | 深圳市沃特沃德股份有限公司 | Pet application information pushing method and device |
| CN106653057A (en) * | 2016-09-30 | 2017-05-10 | 北京智能管家科技有限公司 | Data processing method and apparatus |
| CN106569860A (en) * | 2016-11-04 | 2017-04-19 | 广东欧珀移动通信有限公司 | Application management method and terminal |
| WO2018205459A1 (en) * | 2017-05-10 | 2018-11-15 | 平安科技（深圳）有限公司 | Target user acquisition method and apparatus, electronic device and medium |
| CN107665442A (en) * | 2017-05-10 | 2018-02-06 | 平安科技（深圳）有限公司 | Obtain the method and device of targeted customer |
| CN107704512A (en) * | 2017-08-31 | 2018-02-16 | 平安科技（深圳）有限公司 | Financial product based on social data recommends method, electronic installation and medium |
| CN107704512B (en) * | 2017-08-31 | 2021-08-24 | 平安科技（深圳）有限公司 | Financial product recommendation method based on social data, electronic device and medium |
| CN107767273A (en) * | 2017-09-05 | 2018-03-06 | 平安科技（深圳）有限公司 | Asset Allocation method, electronic installation and medium based on social data |
| CN107767273B (en) * | 2017-09-05 | 2021-08-31 | 平安科技（深圳）有限公司 | Asset configuration method based on social data, electronic device and medium |
| CN107742240A (en) * | 2017-09-30 | 2018-02-27 | 北京金山安全软件有限公司 | Theme application pushing method, device and system |
| CN107979687A (en) * | 2017-10-31 | 2018-05-01 | 维沃移动通信有限公司 | A kind of wallpaper switching method, mobile terminal |
| CN108021619A (en) * | 2017-11-13 | 2018-05-11 | 星潮闪耀移动网络科技（中国）有限公司 | A kind of event description object recommendation method and device |
| CN108021619B (en) * | 2017-11-13 | 2020-05-05 | 星潮闪耀移动网络科技（中国）有限公司 | Event description object recommendation method and device |
| CN109033263A (en) * | 2018-07-09 | 2018-12-18 | 努比亚技术有限公司 | A kind of application recommended method and terminal |
| CN110083774A (en) * | 2019-05-10 | 2019-08-02 | 腾讯科技（深圳）有限公司 | Using determination method, apparatus, computer equipment and the storage medium of recommendation list |
| CN110083774B (en) * | 2019-05-10 | 2023-11-03 | 腾讯科技（深圳）有限公司 | Method and device for determining application recommendation list, computer equipment and storage medium |
| CN110362376A (en) * | 2019-07-18 | 2019-10-22 | 北京小米移动软件有限公司 | A kind of method, apparatus and storage medium that electronic apparatus system theme style is set |
| CN110889036A (en) * | 2019-10-31 | 2020-03-17 | 深圳市微立德科技有限公司 | Multi-dimensional information processing method and device and terminal equipment |
| CN110879868A (en) * | 2019-11-21 | 2020-03-13 | 中国工商银行股份有限公司 | Consultant scheme generation method, device, system, electronic equipment and medium |
| WO2021116850A1 (en) * | 2019-12-11 | 2021-06-17 | International Business Machines Corporation | Grouping users of a mobile network |
| US11361009B2 (en) | 2019-12-11 | 2022-06-14 | International Business Machines Corporation | Grouping users of a mobile network |
| GB2605735A (en) * | 2019-12-11 | 2022-10-12 | Ibm | Grouping users of a mobile network |
| CN111163228A (en) * | 2019-12-31 | 2020-05-15 | 中国银行股份有限公司 | Bank software function interface generation method and device |
| CN111158832A (en) * | 2019-12-31 | 2020-05-15 | 中国银行股份有限公司 | Theme skin changing method and device for mobile banking application |
| CN111259259B (en) * | 2020-03-11 | 2021-03-30 | 郑州工程技术学院 | University student news recommendation method, device, equipment and storage medium |
| WO2021217470A1 (en) * | 2020-04-29 | 2021-11-04 | Citrix Systems, Inc. | Computer resource allocation based on categorizing computing processes |
| CN112948528A (en) * | 2021-03-02 | 2021-06-11 | 北京秒针人工智能科技有限公司 | Data classification method and system based on keywords |
| CN114979097A (en) * | 2021-06-03 | 2022-08-30 | 中移互联网有限公司 | MQTT-based message pushing method and device and electronic equipment |
| CN114979097B (en) * | 2021-06-03 | 2023-07-21 | 中移互联网有限公司 | Message pushing method and device based on MQTT and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105488154A (en) | Theme application recommendation method and device | |
| CN105488112B (en) | Information-pushing method and device | |
| CN104615655B (en) | Information recommendation method and device | |
| CN110175223A (en) | A kind of method and device that problem of implementation generates | |
| CN108227950A (en) | A kind of input method and device | |
| CN110147467A (en) | A kind of generation method, device, mobile terminal and the storage medium of text description | |
| CN108073606B (en) | News recommendation method and device for news recommendation | |
| KR20120043434A (en) | Server, user terminal appaatus, service providing method and control method thereof | |
| CN107622074B (en) | Data processing method and device and computing equipment | |
| CN104133956A (en) | Method and device for processing pictures | |
| CN105373580A (en) | Method and device for displaying subjects | |
| CN105677392A (en) | Method and apparatus for recommending applications | |
| CN110222256B (en) | Information recommendation method and device and information recommendation device | |
| CN109714643A (en) | Recommended method, system and the server and storage medium of video data | |
| CN110598098A (en) | Information recommendation method and device and information recommendation device | |
| CN112784142A (en) | Information recommendation method and device | |
| US11546663B2 (en) | Video recommendation method and apparatus | |
| CN112464031A (en) | Interaction method, interaction device, electronic equipment and storage medium | |
| CN106777016A (en) | The method and device of information recommendation is carried out based on instant messaging | |
| CN106649781B (en) | Application recommendation method and device | |
| CN105095253A (en) | Webpage display method and webpage display device | |
| CN107665447B (en) | Information processing method and information processing apparatus | |
| CN110110204A (en) | A kind of information recommendation method, device and the device for information recommendation | |
| CN107045541A (en) | data display method and device | |
| CN110162691B (en) | Topic recommendation, operation method, device and machine equipment in online content service |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160413 |