CN104537104A - Software ranking method and system - Google Patents
Software ranking method and system Download PDFInfo
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- CN104537104A CN104537104A CN201510016067.9A CN201510016067A CN104537104A CN 104537104 A CN104537104 A CN 104537104A CN 201510016067 A CN201510016067 A CN 201510016067A CN 104537104 A CN104537104 A CN 104537104A
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- 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
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Abstract
The invention discloses a software ranking method and system. The software ranking method includes the steps that downloading data and exposure data, reported by a client side, of software are obtained; the downloading rate of the software is calculated according to the downloading data and exposure data; the software is ranked according to the number of downloading rates from large to small; several articles of top-ranked software are put into an artificial list, the left software articles are put into a machine list, the artificial list is put before the machine list, and software abandoned from the artificial list is not put into the machine list anymore. Through the software ranking method and system, the software ranking list can be updated in real time automatically, and therefore a good software ranking list is obtained.
Description
Technical field
The present invention relates to computer network software field, specifically, relate to a kind of software sort method and system.
Background technology
Along with developing rapidly of types of applications software, all kinds of softwares of people in the face of constantly updating, often feel dazzled and have no way of selecting.Especially when same class application software numerous and constantly update, cannot differentiate especially.
Although there are some software sorted lists at present, utilize the sequence of various information (as: recommend, mark or evaluate) to help people and selected to download software, these software sorted lists existing are by artificial treatment mostly.As everyone knows, Current software One's name is legion and renewal speed are fast, existing sort method, because artificial energy is limited, take time and effort, be difficult in time and exactly the Ordering Software in software matrix upgraded, make existing software sorted lists freshness poor, low with reference to rate.
Therefore, in order to the high and problem of list limited quality of the cost of labor solving the list of current manual's Ordering Software, a kind of more intelligent and real-time software sort method and system is needed badly.
Summary of the invention
In order to the high and problem of list limited quality of the cost of labor solving the list of current manual's Ordering Software, embodiments of the present invention provide a kind of software sort method and system.
On the one hand, embodiment of the present invention provides a kind of software sort method, and described method comprises:
Obtain downloading data and the exposure data of the software that client reports;
According to described downloading data and exposure data, calculate the download rate of described software;
From big to small described software is sorted according to the numerical value of described download rate; And
List some softwares before described sequence in manual list, list remaining software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
Accordingly, embodiment of the present invention additionally provides a kind of software ordering system, and described system comprises:
Acquisition module, for obtaining downloading data and the exposure data of the software that client reports;
Computing module, for according to described downloading data and exposure data, calculates the download rate of described software;
Order module, for sorting to described software from big to small according to the numerical value of described download rate;
List block, for listing some softwares before described sequence in manual list, list remaining software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
Implement various embodiment of the present invention and there is following beneficial effect: in real time and automatically software sorted lists is upgraded, thus the software sorted lists of high-quality more can be obtained.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the software sort method according to embodiment of the present invention;
Fig. 2 is the Organization Chart of the software ordering system according to embodiment of the present invention;
Fig. 3 shows the block diagram of the acquisition module 100 shown in Fig. 2;
Fig. 4 shows the block diagram of the list block 400 shown in Fig. 2.
Embodiment
Be described in detail to various aspects of the present invention below in conjunction with the drawings and specific embodiments.Wherein, well-known module, unit and connection each other, link, communication or operation do not illustrate or do not elaborate.Further, described feature, framework or function can combine by any way in one or more embodiments.It will be appreciated by those skilled in the art that following various embodiments are only for illustrating, but not for limiting the scope of the invention.Can also easy understand, the module in each embodiment described herein and shown in the drawings or unit or processing mode can be undertaken combining and designing by various different configuration.
Fig. 1 is the process flow diagram of the software sort method according to embodiment of the present invention; See Fig. 1, described method comprises:
S1, obtains downloading data and the exposure data of the software that client reports; Wherein, described downloading data comprises the number of times of the clicked download of described software; Described exposure data comprises described software and exposes the number of times represented, and in addition, can arrange the time of timing acquisition, such as: 1 hour etc. to above-mentioned steps.
S2, according to described downloading data and exposure data, calculates the download rate of described software; Described download rate is obtained by following formulae discovery:
Number of times/the software of the clicked download of download rate=software exposes the number of times represented.
S3, sorts to described software from big to small according to the numerical value of described download rate; And
S4, by names some before described sequence (such as: front 20 or sequence front 20%) software list manual list in, list remaining software in machine list.Wherein, manual list is the list that operation personnel safeguards, operation personnel can list some good softwares in daily operation, these softwares be operation personnel from some channels, as competing product list, forum etc., the software that the download demand of acquisition may be higher; Machine list is the high-quality resource that machine is responsible for filling; Represent in process, before manual list comes machine list, and the software eliminated from described manual list is no longer listed in described machine list, namely the software be eliminated after described sequence in described manual list, if be sorted in described machine list, then the described software be eliminated is deleted from described machine list.Can according to described sequence, only some names (such as: first 100) software before in described remaining software is listed in described machine list.
By adopting the software sort method of embodiment of the present invention, in real time and automatically software sorted lists is upgraded, thus the software sorted lists of high-quality more can be obtained.
Fig. 2 is the Organization Chart of the software ordering system 1 according to embodiment of the present invention; See Fig. 2, described system 1 comprises:
Acquisition module 100, for obtaining downloading data and the exposure data of the software that client reports;
Computing module 200, for according to described downloading data and exposure data, calculates the download rate of described software; Described download rate is obtained by following formulae discovery:
Number of times/the software of the clicked download of download rate=software exposes the number of times represented.
Order module 300, for sorting to described software from big to small according to the numerical value of described download rate;
List block 400, for listing some softwares before described sequence in manual list, list remaining software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
Fig. 3 shows the block diagram of the acquisition module 100 shown in Fig. 2; See Fig. 3, described acquisition module 100 comprises:
Downloading data acquiring unit 110, for obtaining described downloading data, described downloading data comprises the number of times of the clicked download of described software;
Exposure data acquiring unit 120, for obtaining described exposure data, described exposure data comprises described software and exposes the number of times represented.
Fig. 4 shows the block diagram of the list block 400 shown in Fig. 2; See Fig. 4, described list block 400 comprises:
Manual list unit 410, for by names some before described sequence (such as: front 20 or sequence are front 20%), software lists manual list in;
Machine list cell 420, for listing remaining described software in machine list, represent in process, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list, namely the software be eliminated after described sequence in described manual list, if be sorted in described machine list, then deletes the described software be eliminated from described machine list.Wherein, can according to described sequence, only some names (such as: first 100) software before in described remaining software is listed in described machine list.
Wherein, manual list is the list that operation personnel safeguards, operation personnel can list some good softwares in daily operation, these softwares be operation personnel from some channels, as competing product list, forum etc., the software that the download demand of acquisition may be higher; Machine list is the high-quality resource that machine is responsible for filling.
Through the above description of the embodiments, those skilled in the art can be well understood to the present invention and can realize by the mode of software combined with hardware platform, can certainly all be implemented by hardware.Based on such understanding, what technical scheme of the present invention contributed to background technology can embody with the form of software product in whole or in part, this computer software product can be stored in storage medium, as ROM/RAM, magnetic disc, CD etc., comprising some instructions in order to make a computer equipment (can be personal computer, server, smart mobile phone or the network equipment etc.) perform the method described in some part of each embodiment of the present invention or embodiment.
The term used in instructions of the present invention and wording, just to illustrating, are not meaned and are formed restriction.It will be appreciated by those skilled in the art that under the prerequisite of the ultimate principle not departing from disclosed embodiment, can various change be carried out to each details in above-mentioned embodiment.Therefore, scope of the present invention is only determined by claim, and in the claims, except as otherwise noted, all terms should be understood by the most wide in range rational meaning.
Claims (10)
1. a software sort method, is characterized in that, described method comprises:
Obtain downloading data and the exposure data of the software that client reports;
According to described downloading data and exposure data, calculate the download rate of described software;
From big to small described software is sorted according to the numerical value of described download rate; And
List some softwares before described sequence in manual list, list remaining software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
2. the method for claim 1, is characterized in that, described downloading data comprises the number of times of the clicked download of described software; Described exposure data comprises described software and exposes the number of times represented.
3. method as claimed in claim 2, it is characterized in that, described download rate is obtained by following formulae discovery:
Number of times/the software of the clicked download of download rate=software exposes the number of times represented.
4. the method for claim 1, is characterized in that, the described software eliminated from described manual list is no longer listed described machine list in and comprised:
The software be eliminated after described sequence in described manual list, if be sorted in described machine list, then deletes the described software be eliminated from described machine list.
5. the method for claim 1, is characterized in that, describedly lists remaining software in machine list and comprises:
According to described sequence, some softwares before in described remaining software are listed in described machine list.
6. a software ordering system, is characterized in that, described system comprises:
Acquisition module, for obtaining downloading data and the exposure data of the software that client reports;
Computing module, for according to described downloading data and exposure data, calculates the download rate of described software;
Order module, for sorting to described software from big to small according to the numerical value of described download rate;
List block, for listing some softwares before described sequence in manual list, list remaining software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
7. system as claimed in claim 6, it is characterized in that, described acquisition module comprises:
Downloading data acquiring unit, for obtaining described downloading data, described downloading data comprises the number of times of the clicked download of described software;
Exposure data acquiring unit, for obtaining described exposure data, described exposure data comprises described software and exposes the number of times represented.
8. system as claimed in claim 6, it is characterized in that, described download rate is obtained by following formulae discovery:
Number of times/the software of the clicked download of download rate=software exposes the number of times represented.
9. system as claimed in claim 6, it is characterized in that, described list block comprises:
Manual list unit, for listing some softwares before described sequence in manual list;
Machine list cell, for listing remaining described software in machine list, before described manual list comes described machine list, and the software eliminated from described manual list is no longer listed in described machine list.
10. system as claimed in claim 9, is characterized in that, describedly lists remaining software in machine list and comprises:
According to described sequence, some softwares before in described remaining software are listed in described machine list.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201510016067.9A CN104537104A (en) | 2015-01-13 | 2015-01-13 | Software ranking method and system |
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| CN201510016067.9A CN104537104A (en) | 2015-01-13 | 2015-01-13 | Software ranking method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107885572A (en) * | 2017-12-11 | 2018-04-06 | 广东欧珀移动通信有限公司 | Classification card generation method, system, server and computer-readable recording medium |
| CN109408715A (en) * | 2018-10-15 | 2019-03-01 | 上海基分文化传播有限公司 | A kind of material screening technique and system |
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| CN103763361A (en) * | 2014-01-13 | 2014-04-30 | 北京奇虎科技有限公司 | Method and system for recommending applications based on user behavior and recommending server |
| CN103853604A (en) * | 2012-11-23 | 2014-06-11 | 联发科技股份有限公司 | Application management method and applicationrecommendation method |
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| US20030086110A1 (en) * | 2001-11-05 | 2003-05-08 | Parry Travis J. | Use of geographically-referenced imaging device usage information |
| WO2013097119A1 (en) * | 2011-12-28 | 2013-07-04 | 华为技术有限公司 | Method and device for realizing multilevel storage in file system |
| CN103853604A (en) * | 2012-11-23 | 2014-06-11 | 联发科技股份有限公司 | Application management method and applicationrecommendation method |
| CN103618774A (en) * | 2013-11-19 | 2014-03-05 | 北京奇虎科技有限公司 | Resource recommending method, device and system based on network behaviors |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107885572A (en) * | 2017-12-11 | 2018-04-06 | 广东欧珀移动通信有限公司 | Classification card generation method, system, server and computer-readable recording medium |
| CN109408715A (en) * | 2018-10-15 | 2019-03-01 | 上海基分文化传播有限公司 | A kind of material screening technique and system |
| CN109408715B (en) * | 2018-10-15 | 2021-03-19 | 上海趣蕴网络科技有限公司 | Material screening method and system |
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Application publication date: 20150422 |
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