CN104765609A - Software related resource recommendation method, obtaining method and corresponding device - Google Patents
Software related resource recommendation method, obtaining method and corresponding device Download PDFInfo
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Abstract
The invention discloses a software related resource recommendation method, an obtaining method and a corresponding device, wherein the software related resource recommendation method comprises the following steps: establishing a software resource database, wherein the software resource database is stored with main software and related resources of main software; obtaining software data information of the main software on the client side; searching the related resources matched with the software data information in the software resource database; recommending the searched related resources to the client side according to the recommendation strategy. According to the scheme disclosed by the invention, the resource information related to the software data information is recommended or shown to the user side based on the software data of the client side.
Description
Technical field
The disclosure relates generally to computer technology, is specifically related to software administration technology, particularly relates to a kind of software context resource recommendation method, acquisition methods, recommendation apparatus and acquisition device.
Background technology
In the prior art, generally speaking, user uses the flow process of software for downloading-installing-use-unload.Specifically, in prior art, when user needs certain software, the method by search obtains the download link of this software from server (server of such as website), and by downloading the operation (such as clicking operation) of link.After completing download, installed by the executable file clicked in software installation kit.In addition, when needs are upgraded to software, also by installing similar method to download with software and the AKU of mounting software.Finally, if user no longer needs to use this software, it can be unloaded from client.
Current software on the market only provides the help in download, installation and unloading for user, and in software application link, except helpful to software upgrading, for other process in software application, does not provide additional function or help.
Summary of the invention
In view of above-mentioned defect of the prior art or deficiency, expect to provide a kind of software context resource recommendation method, acquisition methods, recommendation apparatus and acquisition device, can client-based software data information to recommended by client or present the resource information be associated with this software data information.
First aspect, the embodiment of the present application provides a kind of software context resource recommendation method, comprising: set up soft-asset data storehouse, and wherein soft-asset data storehouse associatedly stores the correlated resources of major software and major software; Obtain the software data information of the major software in client; The correlated resources of search and software data information matches in soft-asset data storehouse; And recommend the correlated resources that searches to client according to Generalization bounds, wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
Second aspect, the embodiment of the present application additionally provides a kind of software context resource acquiring method, comprising: the software data information obtaining the major software in client; Described software data information is sent to external server; Receive that described external server sends with the correlated resources of described software data information matches; And present described correlated resources to described client; Wherein, described correlated resources comprises following at least one item: the software relevant to major software, document and material.
The third aspect, the embodiment of the present application additionally provides a kind of software context resource recommendation device, and comprising: set up module, be configured for and set up soft-asset data storehouse, wherein soft-asset data storehouse associatedly stores the correlated resources of major software and major software; Acquisition module, is configured for the software data information of the major software obtained in client; Search module, is configured for the correlated resources of search and software data information matches in soft-asset data storehouse; And recommending module, be configured for and recommend according to Generalization bounds the correlated resources that searches to client, wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
Fourth aspect, the embodiment of the present application additionally provides a kind of software context resource acquisition device, comprising: acquisition module, is configured for the software data information of the major software obtained in client; Sending module, is configured for and software data information is sent to software resource server; Receiver module, be configured for receive that software resource server sends with correlated resources that is software data information matches; And present module, be configured for and present correlated resources on the client; Wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
Software context resource recommendation method, acquisition methods, recommendation apparatus and acquisition device that the embodiment of the present application provides, can based on the software data information in client, software, document and material that the recommendation to user's differentiation is correlated with.In addition, the analysis also by using hobby to user software, initiatively recommends software, resource or document to user targetedly, facilitates user to download use.
In addition, in certain embodiments, can based on client to Generalization bounds such as the fancy grades of correlated resources, determine whether to recommend correlated resources or whether correlated resources is got client to client, and recommend correlated resources to client or whether correlated resources got the frequency of client.
Accompanying drawing explanation
By reading the detailed description done non-limiting example done with reference to the following drawings, the other features, objects and advantages of the application will become more obvious:
Fig. 1 shows the exemplary system architecture 100 can applying the embodiment of the present application;
Fig. 2 shows the schematic process flow diagram of the software context resource recommendation method of the embodiment of the present application;
Fig. 3 shows the schematic process flow diagram searching for the correlated resources relevant to software data information in soft-asset data storehouse of the embodiment of the present application;
Fig. 4 shows the schematic process flow diagram of the software context resource recommendation method of another embodiment of the application;
Fig. 5 shows the schematic process flow diagram of the software context resource acquiring method of the embodiment of the present application;
Fig. 6 shows the indicative flowchart of a kind of application scenarios of the software context resource recommendation method of the embodiment of the present application;
Fig. 7 shows the schematic diagram of the another kind of application scenarios of the software context resource recommendation method of the embodiment of the present application;
Fig. 8 shows the schematic structural drawing of the software context resource recommendation device of the embodiment of the present application;
Fig. 9 shows the schematic structural drawing of the software context resource acquisition device of the embodiment of the present application;
Figure 10 shows the structural representation of the computer system 1000 of terminal device or the server be suitable for for realizing the embodiment of the present application.
Embodiment
Below in conjunction with drawings and Examples, the application is described in further detail.Be understandable that, specific embodiment described herein is only for explaining related invention, but not the restriction to this invention.It also should be noted that, for convenience of description, illustrate only in accompanying drawing and invent relevant part.
It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.Below with reference to the accompanying drawings and describe the application in detail in conjunction with the embodiments.
Fig. 1 shows the exemplary system architecture 100 can applying the embodiment of the present application.
As shown in Figure 1, system architecture 100 can comprise terminal device 101,102, network 103 and server 104.Network 103 in order to provide the medium of communication link between terminal device 101,102 and server 104.Network 103 can comprise various connection type, such as wired, wireless communication link or fiber optic cables etc.
User 110 can use terminal device 101,102 mutual by network 103 and server 104, to receive or to send message etc.Terminal device 101,102 can be provided with various client application, such as JICQ, mailbox client, social platform software, software administration application etc.
Terminal device 101,102 can be various electronic equipment, includes but not limited to PC, smart mobile phone, intelligent watch, panel computer, personal digital assistant etc.
Server 104 can be to provide the server of various service.The process such as server can store the data received, analysis, and result is fed back to terminal device.In the embodiment of the application, server 104 is such as software resource server, for recommending the various resources relevant to software to terminal device 101,102.
Should be appreciated that, the number of the terminal device in Fig. 1, network and server is only schematic.According to realizing needs, the terminal device of arbitrary number, network and server can be had.
As previously mentioned, in prior art, can not when the software that user installation is new to other softwares, resource or document that it recommends the software new with this to be associated; Can not recommend and this other softwares, resource or document of being associated of mounting software to it according to software mounted on subscriber computer.User is made to need initiatively to spend the plenty of time to search and new software or other softwares, resource or the document that are associated of mounting software like this.
The embodiment of the software context resource recommendation method of the application, acquisition methods, recommendation apparatus and acquisition device is intended to solve above one or more problems.According to the embodiment of the application, in software application process, by other softwares, document and the material that may use and this software contacts, and can recommend when user needs or be pushed to user.
First, will provide in the following description, the specific explanations of each concept that use.
Major software, refer to current for or the software of service, the resource that such as will associate with it for this software recommend, therefore major software is also the software of the acquisition object as software data information.It should be noted that, in the application, the concept of major software is relative.Such as, when recommending correlated resources for software A, when the software data information based on software A searches for its related resource in soft-asset data storehouse, software A can regard as major software, and the software B of associated can be used as the software class resource of major software A.When recommending correlated resources for software B, when the software data information based on software B searches for its related resource in soft-asset data storehouse, software B can regard as major software, and the software A of associated can be used as the software class resource of major software B.
Preposition software, refers to that major software completes necessary software when installing first.Specifically, if software A is in the process of installing or use, require that software B has installed or run, then title software B is the preposition software of software A.Such as, certain Games Software relies on the installation of Java environment, then Java is the preposition software of this game.
Assistant software, refers to the software that can strengthen major software function.Specifically, if software B can make user better use software A, then title software B is the assistant software of software A.The relation that major software and its assistant software do not rely on by force.Such as, it is more smooth that sudden peal of thunder game accelerator can make player play certain online game, then sudden peal of thunder game accelerator is the assistant software of this online game.
Special material, refers to the material only can opened with this major software or the software with certain general character.These materials can make user better use this software, such as enrich function, strengthen effect etc.Such as, PPT template is the special material of Powerpoint software, and QQ expression is the special material of QQ application, and PS brush is the special material of Photoshop software, etc.
Study course document, refers to the document that user can be instructed better to use certain software.Study course document such as can include but not limited to, walkthrough, various elementary, high-level software study course etc.
Fig. 2 shows the schematic process flow diagram of the software context resource recommendation method 200 of the embodiment of the present application.
First, in step 210, soft-asset data storehouse is set up.Wherein soft-asset data storehouse associatedly stores the correlated resources of major software and major software.By major software and its correlated resources are carried out association store in a database, when searching the correlated resources of major software, based on the information of this major software, all correlated resources relevant to this major software can be found easily.
Here, the correlated resources of major software can refer to any resource be associated with this major software.Such as, can comprise the software class resource relevant to major software and/or non-software class resource, wherein non-software class resource can comprise document and/or material.The type of correlated resources does not also limit, it can be such as executable file (.exe file, belong to software class resource), document (such as .doc document .txt document etc., belong to non-software class resource), picture (.jpeg picture file .bmp picture file belong to non-software class resource) etc.
In certain embodiments, when setting up soft-asset data storehouse, (software race ID) can be identified to the software race that major software is identical with the software class Resourse Distribute of major software; And the software identification (software I D) of this major software of non-software class Resourse Distribute to major software.Have the software relevant or associated software each other of same software race ID.
In one embodiment, the major software stored in soft-asset data storehouse can comprise at least one item in software I D, dbase, software size, software version, update time and system information.Major software also comprises software race ID and optional preposition software I D.Preposition software I D points to the software I D of the preposition software of this major software.The correlated resources of the major software stored in soft-asset data storehouse can comprise at least one item in resource ID, resource name, resource size, resource version, update time and system information.For non-software class resource, also comprise related software ID, the software of the software pointed by this related software ID associated by this non-software class resource.In other words, the software I D of the related software ID also i.e. major software of this resource.In certain embodiments, by the operation (such as clicking) of soft-asset data storehouse respective memory locations, link to the actual storage locations of major software and correlated resources body thereof, thus obtain major software body or correlated resources body (executable file, picture, document etc. of such as software).So, storage space shared by soft-asset data storehouse can be made less.
In existing software administration, other softwares, document and material that software and software may be used process as independent file, do not set up corresponding logical relation, more do not associate in storage.By setting up soft-asset data storehouse in the embodiment of the application, can help user very fast find the related software of needs, document and material.
Then, in a step 220, the software data information of the major software in client is obtained.Here, software data information can refer to the information of user to the arbitrary act performed by this major software.Such as, user to the installation of this major software, upgrade, open or unload, software data information can also comprise the use information of such as user to control a certain in this major software, certain instrument or certain material.
Then, in step 230, in soft-asset data storehouse, the correlated resources with software data information matches is searched for.In certain embodiments, the software class resource due to each major software all has the software race identical with this major software and identifies, then by this software race mark, search out whole software class resources of this major software.In addition, in certain embodiments, because the non-software class resource of each major software has the software identification identical with the software identification of major software, the non-software class resource of this major software is searched for by this software identification.
Then, in step 240, correlated resources is recommended according to Generalization bounds to client.Search out in soft-asset data storehouse with the correlated resources of software data information matches after, recommend to client based on certain strategy.So, the normal running recommending too frequently to cause affecting user customer and use can such as be avoided.
In some embodiments, Generalization bounds such as can be determined based on following at least one item: client is to the fancy grade of correlated resources, and whether the number of users of correlated resources, the high-quality degree of correlated resources, the update date of correlated resources, correlated resources be recommended etc. determines.
Such as, the fancy grade of client to correlated resources can be determined according to the operation behavior of the user of client feedback to correlated resources, and then determine the frequency of recommending correlated resources to client.In certain embodiments, user such as can comprise at least one in the click behavior of correlated resources that user's subtend client recommends, installation behavior or usage behavior to the operation behavior of correlated resources.
In certain embodiments, can whether recommended according to the update date of the high-quality degree of the number of users of correlated resources, correlated resources, correlated resources, correlated resources in one or the multinomial recommended frequency to correlated resources sort.Such as, if the number of users of a certain particular association resource is more, then recommend the frequency of this correlated resources higher to client.
Fig. 3 shows the schematic process flow diagram searching for the correlated resources (that is to say in Fig. 2 step 230) relevant to software data information in soft-asset data storehouse of the embodiment of the present application.
In this embodiment, software data information can comprise software installation information.
In step 231, judge whether software installation information indicates this major software for install first.
In step 232, when software installation information instruction is installed first, can in soft-asset data storehouse, the primary resources in the correlated resources of search major software.
Primary resources such as can comprise preposition software and getting started tutorial document.Here, preposition software is that major software completes and installs necessary software first.Such as, Games Software G must install under Java environment, and so, Java is then a preposition software of this Games Software G.
In step 233, when software installation information instruction non-install first time, search major software correlated resources in premium resource.
Here, non-software installation information of installing first such as can comprise the software installation information that represents software upgrading or represent the software installation information etc. that software again installs after client unloading.
Premium resource such as can comprise at least one item in the assistant software of major software, high-order study course document and special material.Here, assistant software is the software that can strengthen major software function.In certain embodiments, assistant software can improve travelling speed, the human-computer interaction interface improving major software or the network joint efficiency accelerating major software etc. of major software.Special material can refer to the material only can opened with this major software or the software with certain general character.Such as, can think that PPT (Powerpoint, PowerPoint) template is the special material of PPT software, PS (Photoshop) brush is the special material of PS software, and QQ expression is the special material of QQ software.
In certain embodiments, software data information can also comprise software application information.Here, software application information can comprise following at least one item: the major software frequency of utilization of client, and such as, within the unit interval, client opens the number of times of Photoshop software; Client is to the frequency of utilization of the particular tool in major software, and such as, within the unit interval, client uses the number of times of Brush Tool in Photoshop software; And the network search words relevant to major software that user uses, such as, the search word relevant to Photoshop software of user's input.
In certain embodiments, search premium resource can comprise: the preference determining user based on software application information, and selects the premium resource meeting preference in the correlated resources of major software.
Such as, in software application information, point out client to use the frequency of Brush Tool in Photoshop software higher than a preset value, based on this software application information, can determine that user has the preference using Brush Tool in Photoshop software.So, Brush Tool can be searched in soft-asset data storehouse.
Fig. 4 shows the schematic process flow diagram of the software context resource recommendation method 400 of another embodiment of the application.
The software context resource recommendation method of the present embodiment, except comprising step 410 ~ 440 identical with the embodiment shown in Fig. 2, can also comprise following step.
In step 450, in response to the appearance of new correlated resources, update software resource database.Such as, when the renewal version of software occurs, at least one item in the dbase corresponding with this renewal version, software size, software version, update time and system information is added in soft-asset data storehouse.Or, when new correlated resources occurs, at least one item in the resource name of this correlated resources, resource size, resource version, update time and system information can be added in soft-asset data storehouse.
In step 460, the software data information based on the major software in client determines the client will recommending new correlated resources to it.
Such as, in the software application information of a particular clients, point out this client to use the frequency of Brush Tool in Photoshop software higher than a preset value.So, when in new Brush Tool resource updates to soft-asset data storehouse, can determine that this client is the client to its Brush Tool resource of recommending this new.Otherwise, in the software application information of another particular clients, point out this client to use the frequency of Brush Tool in Photoshop software lower than a preset value.So, when in new Brush Tool resource updates to soft-asset data storehouse, can determine that this client is not the client to its Brush Tool resource of recommending this new.
So, when new correlated resources occurs, by screening the client of being recommended by this new correlated resources based on the software data information of each client.
In step 470, new correlated resources is recommended according to Generalization bounds to determined client.In this step, the Generalization bounds identical with step 240 and step 440 such as can be adopted to recommend new correlated resources to client.
Fig. 5 shows the schematic process flow diagram of the software context resource acquiring method of the embodiment of the present application.
As shown in Figure 5, in step 510, the software data information of the major software in client is obtained.
Then, in step 520, software data information is sent to software resource server.In software resource server, store major software and the correlated resources relevant to this major software.
Then, in step 530, receive that software resource server sends with correlated resources that is software data information matches.
Then, in step 540, correlated resources is presented on the client.
Wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
In certain embodiments, the software data information obtaining the major software in client can comprise in response to user installation major software, and obtain the software installation information of major software, software installation information indicates whether to install first.In other words, when user installs a major software on the client, in software installation information, contain the information determining whether this major software is installed first in this client.
In further embodiments, the software data information obtaining the major software in client can also comprise and uses major software in response to user, or search major software or correlated resources, obtain the software application information of major software.Software application information comprises following at least one item: user is to the frequency of utilization of major software; User is to the frequency of utilization of the particular tool in major software; And the network search words relevant to major software that user uses.
In certain embodiments, present correlated resources on the client can be included on software administration interface and associatedly present correlated resources with major software.Need illustrate time, major software and the particular location of its correlated resources on software administration interface can pre-set according to actual conditions.Such as, left side major software being presented on software administration interface can be set to, and the correlated resources relevant to this major software be presented to the right side of this major software.
In further embodiments, present on the client correlated resources can be included in software administration interface independently window in present correlated resources.Such as, correlated resources can be presented in the bullet window interface of client, or correlated resources be presented in the suspended window interface of client.
Preferably, software context resource acquiring method can also comprise detection user to the operation behavior of correlated resources; And to the determination of software resource server feedback operation behavior for Generalization bounds.
In certain embodiments, user such as can comprise at least one in the click behavior of correlated resources that user's subtend client recommends, installation behavior or usage behavior to the operation behavior of correlated resources.
It should be noted that, as shown in the system architecture in Fig. 1, the software context resource recommendation method that the embodiment of the present application provides and software context resource acquiring method can be performed by terminal device 101,102, also can be performed by server 104, software context resource recommendation device and software context resource acquisition device can be arranged in terminal device 101,102, also can be arranged in server 104.
In certain embodiments, the step obtaining the software data information of the major software in client can perform in server 104, also can perform in terminal device 101,102.Soft-asset data storehouse can be stored in server 104, also can be stored in terminal device 101,102.Such as, in soft-asset data storehouse, search is with the correlated resources of software data information matches and when recommending to described client the correlated resources searched according to Generalization bounds, if terminal device does not have processing power, can be undertaken searching for by server 104 and recommend to terminal device 101,102 based on Generalization bounds; If terminal device 101,102 has processing power, also can be directly searched by terminal device 101,102 and present correlated resources to user.
Fig. 6 shows the indicative flowchart of a kind of application scenarios of the software context resource recommendation method of the embodiment of the present application.In this application scenarios, software data information comprises software installation information and software application information.
As shown in Figure 6, when user is in client installation or when using software (610), in soft-asset data storehouse, correlated resources is searched for (620), judge whether active user is naive user (630) based on software data information, if, then from soft-asset data storehouse, search for primary resources (640), and recommend (680) based on certain Generalization bounds (650) to user.
On the other hand, if judge that active user is not naive user based on software data information, then from soft-asset data storehouse, search for premium resource (660), and the preference (670) of user is judged according to software data information, then based on certain Generalization bounds (650), the premium resource meeting user preference is recommended user (680).
Fig. 7 shows the indicative flowchart of the another kind of application scenarios of the software context resource recommendation method of the embodiment of the present application.In this application scenarios, software data information comprises software application information.
As shown in Figure 7, when user uses network search words (710) relevant to major software, in soft-asset data storehouse, correlated resources is searched for (720), and the preference (730) of user is judged according to software data information, then based on certain Generalization bounds (740), the premium resource meeting user preference is recommended user (750).
Fig. 8 shows the schematic structural drawing of the software context resource recommendation device of the embodiment of the present application.
As shown in Figure 8, software context resource recommendation device 800 comprises and sets up module 810, acquisition module 820, search module 830 and recommending module 840.
Wherein, set up module 810 and be configured for and set up soft-asset data storehouse, wherein soft-asset data storehouse associatedly stores the correlated resources of major software and major software.
Acquisition module 820 is configured for the software data information of the major software obtained in client.
Search module 830 is configured for the correlated resources of search and software data information matches in soft-asset data storehouse.
Recommending module 840 is configured for recommends according to Generalization bounds the correlated resources that searches to client.
Wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
In certain embodiments, set up module 810 and can comprise software race mark allocation units 811 and software identification allocation units 812.
Wherein, software race mark allocation units 811 are configured for the major software software race mark identical with the software class Resourse Distribute of major software.Software identification allocation units 812 are configured for the software identification of the non-software class Resourse Distribute major software to major software.
In certain embodiments, the major software stored in soft-asset data storehouse can comprise at least one item in dbase, software size, software version, update time and system information.The correlated resources of the major software stored in soft-asset data storehouse can comprise at least one item in resource name, resource size, resource version, update time and system information.
In certain embodiments, software data information can comprise software installation information.
In these embodiments, search module 830 can comprise the first search unit 831 and the second search unit 832.
Wherein, the first search unit 831 is configured for when software installation information instruction is installed first, the primary resources in the correlated resources of search major software.Primary resources such as can comprise preposition software and getting started tutorial document, and wherein, preposition software is that major software completes and installs necessary software first.
Second search unit 832 be configured for when software installation information instruction non-install first time, search major software correlated resources in premium resource.Premium resource such as can comprise at least one item in assistant software, high-order study course document and special material, and wherein assistant software is have the software strengthening major software function.
In certain embodiments, software data information can also comprise software application information.
Software application information such as can comprise following at least one item: the major software frequency of utilization of client; Client is to the frequency of utilization of the particular tool in major software; And the network search words relevant to major software that user uses.
In these embodiments, the second search unit 832 is also configured for the preference determining user based on software application information; And select the premium resource meeting preference in the correlated resources of major software.
In certain embodiments, recommending module 840 is configurable determines Generalization bounds at least one item in whether recommended to the fancy grade of correlated resources, resource number of users, resource high-quality degree, resource updates date and resource based on client.
Preferably, recommending module 840 can comprise hobby determining unit 841, and the operation behavior of user to correlated resources be configured for based on client feedback determines the fancy grade of client to correlated resources.
Preferably, software context resource recommendation device 800 can also comprise database update module 850, client determination module 860.
Wherein, database update module 850 is configured for the appearance in response to new correlated resources, update software resource database.
The client determination module 860 software data information be configured for based on the major software in client determines to recommend to it client of new correlated resources.
Recommending module 840 is also configured for recommends new correlated resources according to Generalization bounds to determined client.
Fig. 9 shows the schematic structural drawing of the software context resource acquisition device of the embodiment of the present application.
As shown in Figure 9, software context resource acquisition device 900 comprises acquisition module 910, sending module 920, receiver module 930 and presents module 940.
Wherein, acquisition module 910 is configured for the software data information of the major software obtained in client.
Sending module 920 is configured for and software data information is sent to software resource server.
Receiver module 930 be configured for receive that software resource server sends with correlated resources that is software data information matches.
Present module 940 to be configured for and to present correlated resources on the client.
Wherein, correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
In certain embodiments, acquisition module 910 can mount message acquiring unit 911 and at least one item used in information acquisition unit 912.
Wherein, mount message acquiring unit 911 is configured in response to user installation major software, and obtain the software installation information of major software, software installation information indicates whether to install first.
Use information acquisition unit 912 to be configured for and use major software or search major software or correlated resources in response to user, obtain the software application information of major software.
Here, software application information can comprise following at least one item: user is to the frequency of utilization of major software; User is to the frequency of utilization of the particular tool in major software; And the network search words relevant to major software that user uses.
In certain embodiments, present module 940 and can comprise any one in the first display unit 941 and the second display unit 942.
Wherein, the first display unit 941 is configured for and associatedly presents correlated resources with major software on software administration interface.
Second display unit 942 be configured for software administration interface independently window in present correlated resources.
Preferably, the second display unit 942 can also comprise and plays window and present subelement and suspended window and present any one in subelement.
Wherein, play window to present subelement and be configured for and correlated resources be presented in the bullet window interface of client.
Suspended window presents subelement and is configured for and is presented to by correlated resources in the suspended window interface of client.
Preferably, software context resource acquisition device 900 can also comprise operation behavior detection module 950 and feedback module 960.
Wherein, operation behavior detection module 950 is configured for and detects user to the operation behavior of correlated resources.
Feedback module 960 is configured for the determination of software resource server feedback operation behavior for Generalization bounds.
Figure 10 shows the structural representation of the computer system 1000 of terminal device or the server be suitable for for realizing the embodiment of the present application.
As shown in Figure 10, computer system 1000 comprises CPU (central processing unit) (CPU) 1001, and it or can be loaded into the program random access storage device (RAM) 1003 from storage area 1008 and perform various suitable action and process according to the program be stored in ROM (read-only memory) (ROM) 1002.In RAM 1003, also store system 1000 and operate required various program and data.CPU 1001, ROM 1002 and RAM 1003 are connected with each other by bus 1004.I/O (I/O) interface 1005 is also connected to bus 1004.
I/O interface 1005 is connected to: the importation 1006 comprising keyboard, mouse etc. with lower component; Comprise the output 1007 of such as cathode-ray tube (CRT) (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.; Comprise the storage area 1008 of hard disk etc.; And comprise the communications portion 1009 of network interface unit of such as LAN card, modulator-demodular unit etc.Communications portion 1009 is via the network executive communication process of such as the Internet.Driver 1010 is also connected to I/O interface 1005 as required.Detachable media 1011, such as disk, CD, magneto-optic disk, semiconductor memory etc., be arranged on driver 1010 as required, so that the computer program read from it is mounted into storage area 1008 as required.
Especially, according to embodiment of the present disclosure, the process that reference flow sheet describes above may be implemented as computer software programs.Such as, embodiment of the present disclosure comprises a kind of computer program, and it comprises the computer program visibly comprised on a machine-readable medium, and described computer program comprises the program code for the method shown in flowchart.In such embodiments, this computer program can be downloaded and installed from network by communications portion 1009, and/or is mounted from detachable media 1011.
Process flow diagram in accompanying drawing and block diagram, illustrate according to the architectural framework in the cards of the system of various embodiments of the invention, method and computer program product, function and operation.In this, each square frame in process flow diagram or block diagram can represent a part for module, program segment or a code, and a part for described module, program segment or code comprises one or more executable instruction for realizing the logic function specified.Also it should be noted that at some as in the realization of replacing, the function marked in square frame also can be different from occurring in sequence of marking in accompanying drawing.Such as, in fact the square frame that two adjoining lands represent can perform substantially concurrently, and they also can perform by contrary order sometimes, and this determines according to involved function.Also it should be noted that, the combination of the square frame in each square frame in block diagram and/or process flow diagram and block diagram and/or process flow diagram, can realize by the special hardware based system of the function put rules into practice or operation, or can realize with the combination of specialized hardware and computer instruction.
Unit involved by being described in the embodiment of the present application or module can be realized by the mode of software, also can be realized by the mode of hardware.Described unit or module also can be arranged within a processor, such as, can be described as: a kind of processor comprises sets up module, acquisition module, search module and recommending module.Wherein, the title of these unit or module does not form the restriction to this unit or module itself under certain conditions, such as, sets up module and can also be described to " for setting up the module in soft-asset data storehouse ".
As another aspect, present invention also provides a kind of computer-readable recording medium, this computer-readable recording medium can be the computer-readable recording medium comprised in device described in above-described embodiment; Also can be individualism, be unkitted the computer-readable recording medium in the equipment of allocating into.Computer-readable recording medium stores more than one or one program, and described program is used for performance description in the formula input method of the application by one or more than one processor.
More than describe and be only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art are to be understood that, invention scope involved in the application, be not limited to the technical scheme of the particular combination of above-mentioned technical characteristic, also should be encompassed in when not departing from described inventive concept, other technical scheme of being carried out combination in any by above-mentioned technical characteristic or its equivalent feature and being formed simultaneously.The technical characteristic that such as, disclosed in above-mentioned feature and the application (but being not limited to) has similar functions is replaced mutually and the technical scheme formed.
Claims (26)
1. a software context resource recommendation method, is characterized in that, described method comprises:
Set up soft-asset data storehouse, wherein said soft-asset data storehouse associatedly stores the correlated resources of major software and described major software;
Obtain the software data information of the major software in client;
The correlated resources of search and described software data information matches in described soft-asset data storehouse; And
Recommend the correlated resources searched to described client according to Generalization bounds,
Wherein, described correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
2. method according to claim 1, is characterized in that, described soft-asset data storehouse of setting up comprises:
To the software race mark that described major software is identical with the software class Resourse Distribute of described major software;
To described major software non-software class Resourse Distribute described in the software identification of major software.
3. method according to claim 2, is characterized in that:
The major software stored in described soft-asset data storehouse comprises at least one item in dbase, software size, software version, update time and system information;
The correlated resources of the major software stored in described soft-asset data storehouse comprises at least one item in resource name, resource size, resource version, update time and system information.
4. method according to claim 1, is characterized in that, described software data information comprises software installation information, wherein, searches for the correlated resources relevant to described software data information and comprise in described soft-asset data storehouse:
When described software installation information instruction is installed first, search for the primary resources in the correlated resources of described major software, described primary resources comprises preposition software and getting started tutorial document, and wherein, described preposition software is that described major software completes and installs necessary software first;
When the instruction of described software installation information is non-install first time, search for the premium resource in the correlated resources of described major software, described premium resource comprises at least one item in assistant software, high-order study course document and special material, and wherein said assistant software is have the software strengthening major software function.
5. method according to claim 4, is characterized in that, described software data information also comprises software application information, and described software application information comprises following at least one item: the major software frequency of utilization of client; Client is to the frequency of utilization of the particular tool in major software; And the network search words relevant to described major software that user uses;
And described search premium resource comprises:
The preference of user is determined based on described software application information; And
Select the premium resource meeting described preference in the correlated resources of described major software.
6. method according to claim 1, is characterized in that, described Generalization bounds is based on following at least one information:
Whether client is recommended to the fancy grade of correlated resources, resource number of users, resource high-quality degree, resource updates date and resource.
7. method according to claim 6, is characterized in that, described client is determined the operation behavior of correlated resources according to the user of client feedback the fancy grade of correlated resources.
8. the method according to claim 1-7 any one, is characterized in that, described method also comprises:
In response to the appearance of new correlated resources, upgrade described soft-asset data storehouse;
Software data information based on the major software in client determines the client will recommending described new correlated resources to it; And
Described new correlated resources is recommended to determined client according to described Generalization bounds.
9. a software context resource acquiring method, is characterized in that, described method comprises:
Obtain the software data information of the major software in client;
Described software data information is sent to software resource server;
Receive that described software resource server sends with the correlated resources of described software data information matches; And
Described client presents described correlated resources;
Wherein, described correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
10. method according to claim 9, is characterized in that, the software data information of the major software in described acquisition client comprises following at least one item:
In response to user installation major software, obtain the software installation information of described major software, described software installation information indicates whether to install first; And
Use major software in response to user or search for major software or correlated resources, obtain the software application information of described major software, described software application information comprises following at least one item: user is to the frequency of utilization of major software; User is to the frequency of utilization of the particular tool in major software; And the network search words relevant to described major software that user uses.
11. methods according to claim 9, is characterized in that, described client presents described correlated resources and comprises following any one:
Software administration interface associatedly presents described correlated resources with described major software; And
With described software administration interface independently window in present described correlated resources.
12. methods according to claim 11, is characterized in that, described with described software administration interface independently window in present described correlated resources and comprise following any one:
Described correlated resources is presented in the bullet window interface of described client; And
Described correlated resources is presented in the suspended window interface of described client.
13. methods according to claim 9, is characterized in that, described method also comprises:
Detect user to the operation behavior of described correlated resources; And
To the determination of operation behavior described in described software resource server feedback for Generalization bounds.
14. 1 kinds of software context resource recommendation devices, it is characterized in that, described device comprises:
Set up module, be configured for and set up soft-asset data storehouse, wherein said soft-asset data storehouse associatedly stores the correlated resources of major software and described major software;
Acquisition module, is configured for the software data information of the major software obtained in client;
Search module, is configured for the correlated resources of search and described software data information matches in described soft-asset data storehouse; And
Recommending module, is configured for and recommends according to Generalization bounds the correlated resources that searches to described client,
Wherein, described correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
15. devices according to claim 14, is characterized in that, set up module and comprise:
Software race mark allocation units, are configured for the described major software software race mark identical with the software class Resourse Distribute of described major software;
Software identification allocation units, are configured for the software identification of major software described in the non-software class Resourse Distribute to described major software.
16. devices according to claim 15, is characterized in that:
The major software stored in described soft-asset data storehouse comprises at least one item in dbase, software size, software version, update time and system information;
The correlated resources of the major software stored in described soft-asset data storehouse comprises at least one item in resource name, resource size, resource version, update time and system information.
17. devices according to claim 14, is characterized in that, described software data information comprises software installation information, and wherein, described search module comprises:
First search unit, be configured for when described software installation information instruction is installed first, search for the primary resources in the correlated resources of described major software, described primary resources comprises preposition software and getting started tutorial document, wherein, described preposition software is that described major software completes and installs necessary software first;
Second search unit, be configured for when the instruction of described software installation information is non-install first time, search for the premium resource in the correlated resources of described major software, described premium resource comprises at least one item in assistant software, high-order study course document and special material, and wherein said assistant software is have the software strengthening major software function.
18. devices according to claim 17, is characterized in that, described software data information also comprises software application information, and described software application information comprises following at least one item: the major software frequency of utilization of client; Client is to the frequency of utilization of the particular tool in major software; And the network search words relevant to described major software that user uses;
Described second search unit is also configured for:
The preference of user is determined based on described software application information; And
Select the premium resource meeting described preference in the correlated resources of described major software.
19. devices according to claim 14, it is characterized in that, described recommending module be configured for whether recommended to the fancy grade of correlated resources, resource number of users, resource high-quality degree, resource updates date and resource based on client at least one item determine described Generalization bounds.
20. devices according to claim 19, is characterized in that, described recommending module comprises:
Hobby determining unit, the operation behavior of user to correlated resources be configured for based on client feedback determines the fancy grade of client to correlated resources.
21. devices according to claim 14-20 any one, it is characterized in that, described device also comprises:
Database update module, is configured for the appearance in response to new correlated resources, upgrades described soft-asset data storehouse; And
Client determination module, the software data information be configured for based on the major software in client determines to recommend to it client of described new correlated resources; And
Described recommending module is also configured for recommends described new correlated resources according to described Generalization bounds to determined client.
22. 1 kinds of software context resource acquisition devices, it is characterized in that, described device comprises:
Acquisition module, is configured for the software data information of the major software obtained in client;
Sending module, is configured for and described software data information is sent to software resource server;
Receiver module, be configured for receive that described software resource server sends with correlated resources that is described software data information matches; And
Present module, be configured for and present described correlated resources in described client;
Wherein, described correlated resources comprises software class resource and/or the non-software class resource of major software, and wherein non-software class resource comprises document and/or material.
23. devices according to claim 22, is characterized in that, described acquisition module comprises following at least one item:
Mount message acquiring unit, is configured in response to user installation major software, obtains the software installation information of described major software, and described software installation information indicates whether to install first; And
Use information acquisition unit, be configured for and use major software or search major software or correlated resources in response to user, obtain the software application information of described major software, described software application information comprises following at least one item: user is to the frequency of utilization of major software; User is to the frequency of utilization of the particular tool in major software; And the network search words relevant to described major software that user uses.
24. devices according to claim 22, is characterized in that, described in present module and comprise following any one:
First display unit, is configured for and associatedly presents described correlated resources with described major software on software administration interface; And
Second display unit, be configured for described software administration interface independently window in present described correlated resources.
25. devices according to claim 24, is characterized in that, described second display unit comprises following any one:
Play window and present subelement, be configured for and described correlated resources be presented in the bullet window interface of described client; And
Suspended window presents subelement, is configured for and is presented in the suspended window interface of described client by described correlated resources.
26. devices according to claim 23, is characterized in that, described device also comprises:
Operation behavior detection module, is configured for and detects user to the operation behavior of described correlated resources; And
Feedback module, is configured for the determination of operation behavior described in described software resource server feedback for Generalization bounds.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106682196A (en) * | 2016-12-29 | 2017-05-17 | 北京奇虎科技有限公司 | Related software recommending method and device |
| CN107592254A (en) * | 2017-08-23 | 2018-01-16 | 广东欧珀移动通信有限公司 | A kind of method, apparatus, storage medium and the mobile terminal of information push |
| CN107977224A (en) * | 2017-11-29 | 2018-05-01 | 广东欧珀移动通信有限公司 | Application program collocation method, device, server and storage medium |
| CN108268259A (en) * | 2016-12-30 | 2018-07-10 | 谷歌有限责任公司 | It is dynamically generating customized to apply getting started tutorial |
| CN111160800A (en) * | 2019-12-31 | 2020-05-15 | 清华大学 | Emergency resource combination method and device and related equipment |
| CN111429200A (en) * | 2020-02-24 | 2020-07-17 | 浙江口碑网络技术有限公司 | Content association method and device, storage medium and computer equipment |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101645065A (en) * | 2008-08-05 | 2010-02-10 | 北京搜狗科技发展有限公司 | Method and device for determining auxiliary lexicon needing to be loaded and input method system |
| CN102722379A (en) * | 2011-03-30 | 2012-10-10 | 腾讯科技（深圳）有限公司 | Software recommendation method and system |
| CN102799825A (en) * | 2012-07-18 | 2012-11-28 | 腾讯科技（深圳）有限公司 | Method, device, terminal and server for pushing safety application programs |
| CN102857559A (en) * | 2012-08-15 | 2013-01-02 | 腾讯科技（深圳）有限公司 | Method and system for recommending software, and client end |
| CN103019750A (en) * | 2011-09-20 | 2013-04-03 | 奇智软件（北京）有限公司 | Update overloading method of drive program |
| CN103136342A (en) * | 2013-02-04 | 2013-06-05 | 百度在线网络技术（北京）有限公司 | Searching method, system and searching server of application programs (APP) |
| CN103455522A (en) * | 2012-06-04 | 2013-12-18 | 北京搜狗科技发展有限公司 | Recommendation method and system of application extension tools |
| CN103500114A (en) * | 2013-10-12 | 2014-01-08 | 北京奇虎科技有限公司 | Method and device for installing application program |
| CN103677866A (en) * | 2012-09-05 | 2014-03-26 | 北京搜狗科技发展有限公司 | Application program extension tool pushing method and system |
| CN103747347A (en) * | 2013-12-30 | 2014-04-23 | 乐视网信息技术（北京）股份有限公司 | Video recommendation method |
| CN104111844A (en) * | 2013-04-19 | 2014-10-22 | 腾讯科技（深圳）有限公司 | Method and system for installing application programs into mobile terminals |
| US20140344254A1 (en) * | 2011-12-14 | 2014-11-20 | Beijing Qihood Technology Company Limited | Software recommending method and recommending system |
| CN104216960A (en) * | 2014-08-21 | 2014-12-17 | 北京奇艺世纪科技有限公司 | Method and device for recommending video |
| CN104298679A (en) * | 2013-07-18 | 2015-01-21 | 腾讯科技（深圳）有限公司 | Application service recommendation method and device |
-
2015
- 2015-04-03 CN CN201510159383.1A patent/CN104765609B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101645065A (en) * | 2008-08-05 | 2010-02-10 | 北京搜狗科技发展有限公司 | Method and device for determining auxiliary lexicon needing to be loaded and input method system |
| CN102722379A (en) * | 2011-03-30 | 2012-10-10 | 腾讯科技（深圳）有限公司 | Software recommendation method and system |
| CN103019750A (en) * | 2011-09-20 | 2013-04-03 | 奇智软件（北京）有限公司 | Update overloading method of drive program |
| US20140344254A1 (en) * | 2011-12-14 | 2014-11-20 | Beijing Qihood Technology Company Limited | Software recommending method and recommending system |
| CN103455522A (en) * | 2012-06-04 | 2013-12-18 | 北京搜狗科技发展有限公司 | Recommendation method and system of application extension tools |
| CN102799825A (en) * | 2012-07-18 | 2012-11-28 | 腾讯科技（深圳）有限公司 | Method, device, terminal and server for pushing safety application programs |
| CN102857559A (en) * | 2012-08-15 | 2013-01-02 | 腾讯科技（深圳）有限公司 | Method and system for recommending software, and client end |
| CN103677866A (en) * | 2012-09-05 | 2014-03-26 | 北京搜狗科技发展有限公司 | Application program extension tool pushing method and system |
| CN103136342A (en) * | 2013-02-04 | 2013-06-05 | 百度在线网络技术（北京）有限公司 | Searching method, system and searching server of application programs (APP) |
| CN104111844A (en) * | 2013-04-19 | 2014-10-22 | 腾讯科技（深圳）有限公司 | Method and system for installing application programs into mobile terminals |
| CN104298679A (en) * | 2013-07-18 | 2015-01-21 | 腾讯科技（深圳）有限公司 | Application service recommendation method and device |
| CN103500114A (en) * | 2013-10-12 | 2014-01-08 | 北京奇虎科技有限公司 | Method and device for installing application program |
| CN103747347A (en) * | 2013-12-30 | 2014-04-23 | 乐视网信息技术（北京）股份有限公司 | Video recommendation method |
| CN104216960A (en) * | 2014-08-21 | 2014-12-17 | 北京奇艺世纪科技有限公司 | Method and device for recommending video |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106682196A (en) * | 2016-12-29 | 2017-05-17 | 北京奇虎科技有限公司 | Related software recommending method and device |
| CN108268259A (en) * | 2016-12-30 | 2018-07-10 | 谷歌有限责任公司 | It is dynamically generating customized to apply getting started tutorial |
| US11029979B2 (en) | 2016-12-30 | 2021-06-08 | Google Llc | Dynamically generating custom application onboarding tutorials |
| CN107592254A (en) * | 2017-08-23 | 2018-01-16 | 广东欧珀移动通信有限公司 | A kind of method, apparatus, storage medium and the mobile terminal of information push |
| CN107977224A (en) * | 2017-11-29 | 2018-05-01 | 广东欧珀移动通信有限公司 | Application program collocation method, device, server and storage medium |
| CN107977224B (en) * | 2017-11-29 | 2021-05-07 | Oppo广东移动通信有限公司 | Application program configuration method, device, server and storage medium |
| CN111160800A (en) * | 2019-12-31 | 2020-05-15 | 清华大学 | Emergency resource combination method and device and related equipment |
| CN111160800B (en) * | 2019-12-31 | 2022-06-17 | 清华大学 | Emergency resource combination method and device and related equipment |
| CN111429200A (en) * | 2020-02-24 | 2020-07-17 | 浙江口碑网络技术有限公司 | Content association method and device, storage medium and computer equipment |
| CN111429200B (en) * | 2020-02-24 | 2023-04-28 | 浙江口碑网络技术有限公司 | Content association method and device, storage medium and computer equipment |
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