CN112015948A - Video recommendation method and device, electronic equipment and storage medium - Google Patents
Video recommendation method and device, electronic equipment and storage medium Download PDFInfo
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/74—Browsing; Visualisation therefor
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/73—Querying
- G06F16/735—Filtering based on additional data, e.g. user or group profiles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/7867—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/04842—Selection of displayed objects or displayed text elements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
- G06F3/048—Interaction techniques based on graphical user interfaces [GUI]
- G06F3/0484—Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
- G06F3/04847—Interaction techniques to control parameter settings, e.g. interaction with sliders or dials
Abstract
The embodiment of the invention relates to a video recommendation method, a video recommendation device, electronic equipment and a storage medium, wherein the method comprises the following steps: dividing behavior data acquired by the mobile equipment within a set time period and obtained when a user operates the mobile equipment with one hand to obtain at least one data group, wherein different data groups belong to different time slices; determining corresponding behavior characteristics of the user in each time segment according to the behavior data in each data group; when video recommendation of a user is determined, determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice; and sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to the sequencing result. Therefore, the transverse arrangement sequence of the recommended videos on the video playing interface can be dynamically determined according to the single-hand operation behaviors of the user in different time segments, the operation experience of the user is improved, and the click playing amount of the recommended videos is further improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a video recommendation method and device, electronic equipment and a storage medium.
Background
Currently, when a user operates a mobile phone, the user usually uses the lower half of a single-hand-held mobile phone and uses a thumb to perform touch control on a touch display screen of the mobile phone, for example, clicking a video icon on a video application interface to trigger video playing.
However, in the above usage scenario, because the length of the thumb of the user is limited, the area that can be touched by the user on the touch display screen is also limited, which causes the user to click on the video application interface with the thumb, and the video icon farther from the side where the user holds the video application interface will be more laborious, thereby affecting the operation experience of the user and further affecting the click playing amount of the video.
Disclosure of Invention
In view of this, in order to solve the technical problem in the prior art that operation is inconvenient when a user operates a mobile device with one hand in a video recommendation scene, embodiments of the present invention provide a video recommendation method and apparatus, an electronic device, and a storage medium.
In a first aspect, an embodiment of the present invention provides a video recommendation method, including:
dividing behavior data acquired by a mobile device within a set time period and obtained when a user operates the mobile device with one hand to obtain at least one data group, wherein different data groups belong to different time slices;
determining behavior characteristics corresponding to the user in each time slice according to behavior data in each data group, wherein the behavior characteristics are used for representing human body parts used when the user operates the mobile equipment with one hand in the corresponding time slice, and the human body parts comprise a left human body hand or a right human body hand;
when video recommendation of the user is determined, determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice;
and sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to a sequencing result.
In a possible embodiment, the dividing behavior data collected by the mobile device within a set time period and obtained when the mobile device is operated by a single hand of a user to obtain at least one data group includes:
dividing the set time period according to a set time interval to obtain a plurality of time segments;
determining corresponding time segments according to the acquisition time of each piece of behavior data, dividing the behavior data corresponding to the same time segment into the same data group, and dividing the behavior data corresponding to different time segments into different data groups.
In a possible embodiment, the determining, according to the behavior data in each of the data sets, the behavior characteristics corresponding to the user in each of the time slices includes:
for each behavior data in each data set, determining a human body part used when the user operates the mobile equipment with one hand according to the behavior data;
determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs;
and determining the corresponding behavior characteristics of the user in the time slice to which the data set belongs based on the first times and the second times.
In one possible embodiment, the behavior data includes: starting position coordinates and ending position coordinates of one-hand sliding operation on the display screen of the mobile equipment;
the determining the human body part used when the user operates the mobile device with one hand according to the behavior data comprises:
calculating the initial position coordinate and the end position coordinate according to a set angle calculation mode to obtain a first angle;
if the first angle meets a first set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the left hand of the human body;
and if the first angle meets a second set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the right hand of the human body.
In a possible embodiment, the determining, from the determined behavior characteristics corresponding to the user in each time segment, a target behavior characteristic matching the current time includes:
determining a target time segment to which the current time belongs according to the starting time and the ending time of each time segment;
and determining the corresponding behavior characteristics of the determined user in the target time segment as the target behavior characteristics.
In a possible implementation manner, the sorting the videos to be recommended according to the target behavior feature includes:
if the target behavior characteristics indicate that the human body part used when the user operates the mobile equipment with one hand in the target time segment is the left human body hand, sequencing the recommended videos according to the sequence of the video playing heat from high to low;
and if the target behavior characteristics indicate that the part of the human body used when the user operates the mobile equipment with one hand in the target time segment is the right hand of the human body, sequencing the recommended videos according to the sequence of the video playing heat from low to high.
In a second aspect, an embodiment of the present invention provides a video recommendation apparatus, including:
the data dividing module is used for dividing behavior data which are acquired by the mobile equipment within a set time period and are obtained when a user operates the mobile equipment with one hand to obtain at least one data group, and different data groups belong to different time slices;
a first determining module, configured to determine, according to behavior data in each of the data sets, behavior features corresponding to the user in each of the time segments, where the behavior features are used to represent a human body part used when the user operates a mobile device with one hand in the corresponding time segment, and the human body part includes a left hand or a right hand of a human body;
the second determining module is used for determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice when the video recommendation of the user is determined;
and the video recommendation module is used for sequencing the recommended videos according to the target behavior characteristics and recommending the videos to the user according to the sequencing result.
In a possible embodiment, the data dividing module divides behavior data collected by a mobile device within a set time period and obtained when a user operates the mobile device with one hand, to obtain at least one data group, including:
dividing the set time period according to a set time interval to obtain a plurality of time segments;
determining corresponding time segments according to the acquisition time of each piece of behavior data, dividing the behavior data corresponding to the same time segment into the same data group, and dividing the behavior data corresponding to different time segments into different data groups.
In a possible implementation manner, the determining, by the first determining module, behavior characteristics of the user corresponding to each time segment according to the behavior data in each data group includes:
for each behavior data in each data set, determining a human body part used when the user operates the mobile equipment with one hand according to the behavior data;
determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs;
and determining the corresponding behavior characteristics of the user in the time slice to which the data set belongs based on the first times and the second times.
In one possible embodiment, the behavior data includes: starting position coordinates and ending position coordinates of one-hand sliding operation on the display screen of the mobile equipment;
the first determining module determines a human body part used when the user operates the mobile device with one hand according to the behavior data, and the determining module comprises:
calculating the initial position coordinate and the end position coordinate according to a set angle calculation mode to obtain a first angle;
if the first angle meets a first set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the left hand of the human body;
and if the first angle meets a second set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the right hand of the human body.
In a possible embodiment, the second determining module determines a target behavior feature matching the current time from the determined behavior features corresponding to the user in each time slice, including:
determining a target time segment to which the current time belongs according to the starting time and the ending time of each time segment;
and determining the corresponding behavior characteristics of the determined user in the target time segment as the target behavior characteristics.
In a possible implementation manner, the video recommending module ranks videos to be recommended according to the target behavior feature, including:
if the target behavior characteristics indicate that the human body part used when the user operates the mobile equipment with one hand in the target time slice is the left hand of the human body, sequencing the recommended videos according to the recommended priority from high to low;
and if the target behavior characteristics indicate that the part of the human body used when the user operates the mobile equipment with one hand in the target time segment is the right hand of the human body, sequencing the recommended videos according to the sequence of the recommended priority from low to high.
In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor and a memory, the processor being configured to execute a video recommendation program stored in the memory to implement the video recommendation method of any one of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a storage medium, where one or more programs are stored, and the one or more programs are executable by one or more processors to implement the video recommendation method according to any one of the first aspects.
According to the technical scheme provided by the embodiment of the invention, behavior data which are collected by the mobile equipment within a set time period and used when the user operates the mobile equipment with one hand are divided to obtain at least one data group, different data groups belong to different time segments, corresponding behavior characteristics of the user within each time segment are determined according to the behavior data in each data group, the behavior characteristics are used for representing human body parts which are used when the user operates the mobile equipment with one hand within the corresponding time segment, and the human body parts comprise a left hand or a right hand of the human body, so that the behavior habit of the user in one-hand operation within different time segments is obtained.
Further, when video recommendation of the user is determined, the target behavior characteristics matched with the current time are determined from the corresponding behavior characteristics of the determined user in each time slice, the recommended videos are sorted according to the target behavior characteristics, and the video recommendation is performed on the user according to the sorting result, so that the transverse arrangement sequence of the recommended videos on the video playing interface is dynamically determined according to the single-hand operation behavior habit of the user in the time slice to which the current time belongs, the user can easily click the interested recommended videos, the operation experience of the user is improved, and the click playing amount of the recommended videos is further improved.
Drawings
Fig. 1 is a schematic view of an application scenario of a video recommendation method according to an embodiment of the present invention;
fig. 2 is a flowchart of an embodiment of a video recommendation method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a sliding track of a single-handed sliding operation when a user slides on a touch display screen of a mobile device using a left thumb;
FIG. 4 is a schematic diagram of a sliding track of a one-handed sliding operation when a user slides on a touch display screen of a mobile device using a thumb of a right hand;
fig. 5 is a block diagram of an embodiment of a video recommendation apparatus according to the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
For the convenience of understanding of the embodiments of the present invention, an application scenario of the video recommendation method provided by the embodiments of the present invention is first explained with reference to the drawings.
Referring to fig. 1, a schematic diagram of an application scenario of the video recommendation method according to the embodiment of the present invention is shown.
As shown in fig. 1, a user 101 operates a mobile device 102 using a single hand, such as the left hand, to control the mobile device 102 to provide network services. Further, in a video recommendation scenario, a video application (not shown in fig. 1) installed on the mobile device 102 may also recommend other videos (hereinafter referred to as recommended videos) to the user during the playing of the videos. Optionally, the recommended video is determined by a server corresponding to the video application, and there is some association with the video currently being played by the video application. For example, the recommended video and the video currently being played belong to the same episode, and for example, the recommended video and the video currently being played belong to the same type or have the same video tag, and the like. The invention does not relate to how the server determines the recommended videos.
In one embodiment, the video application may make the video recommendation to the user by displaying a video icon of the recommended video on the video playing interface.
In one example, a video application may present video icons of a plurality of recommended videos laterally on a video playback interface. For example, as shown in fig. 1, video icons of recommended video 1 to recommended video 4 are displayed in a transverse direction on the video playing interface.
Further, in the existing method, when a plurality of recommended videos are displayed horizontally on a video playing interface, the arrangement rule of the recommended videos is fixed. For example, in any scene, at any time, the recommended videos are sorted in the order of playing heat from high to low according to videos, or in the order of playing episode numbers from small to large, which results in different operation experiences when the user clicks the same recommended video in two different scenes, i.e., when the user operates the mobile device 102 with the left hand and operates the mobile device 102 with the right hand. For example, the user tends to watch the recommended video with the highest video playing popularity, so that in a scene where the user operates the mobile device 102 with the left hand, the user can easily click the video icon that the user wants to watch the video, while in a scene where the user operates the mobile device 102 with the right hand, the user is more labored when the user clicks the video icon that the user wants to watch the video, thereby causing inconvenience in operation and affecting the operation experience of the user, and further, the user may change the watching intention due to inconvenience in operation, thereby affecting the click playing amount of the video.
Based on this, the embodiment of the present invention provides a video recommendation method, by which a horizontal arrangement order of recommended videos on a video playing interface can be dynamically determined according to different one-handed operation behaviors of a user in different time periods, so as to improve operation experience of the user and further improve click play amount of the recommended videos.
The following is a further explanation of the embodiments with reference to the drawings, which are not to be construed as limiting the embodiments of the present invention.
Referring to fig. 2, a flowchart of an embodiment of a video recommendation method according to an embodiment of the present invention is provided. In one example, the method is applied to an electronic device, where the electronic device may be a hardware device supporting network connection to provide various network services, including but not limited to a smart phone, a tablet computer, a laptop portable computer, a desktop computer, a server, and the like, and when the electronic device is a server, the electronic device may be a server corresponding to a video application in the application scenario shown in fig. 1. As shown in fig. 2, the method comprises the steps of:
First, some conceptual terms involved in this step 201 are explained:
(1) setting a time period:
typically, it is likely that the same user will have the same behavior during the same time period of each day. For example, users share lunch at 12 o 'clock to 12 o' clock 30 of each day, and during this time, they typically use the right hand to hold the cutlery and the left hand to operate the mobile device (e.g., smart phone); as another example, the user is riding a bus from 8 o 'clock to 9 o' clock each day, and during this time, the user typically operates the mobile device with the right hand. It follows that the parts of the human body used by the same user when operating the mobile device with one hand during the same time period on a daily basis, including the left human hand (hereinafter referred to as the left hand) and the right human hand (hereinafter referred to as the right hand), are likely to be the same. Based on this, the set time period may be set to 0 o 'clock to 24 o' clock on a certain day, or may be a time period within a certain day, such as 6 o 'clock to 24 o' clock.
(2) Time slice:
the time slice refers to one time period in the set time periods.
In the embodiment of the invention, the set time period can be divided according to the set time interval to obtain a plurality of time segments. For example, assuming that the set time period is from 6 to 24 points, and assuming that the set time interval is 1 hour, 18 time slices can be obtained by dividing the set time period according to the set time interval, and the 18 time slices respectively correspond to 6 to 7 points, 7 to 8 points, 8 to 9 points, and so on.
(2) Single-hand operation:
in the embodiment of the present invention, the one-handed operation refers to a sliding operation, such as a sliding operation performed on a touch display screen of a mobile device using a thumb.
(3) Behavior data:
corresponding to the concept of one-handed operation described above, the behavior data may include a start position coordinate and an end position coordinate of the one-handed sliding operation on the touch display screen of the mobile device.
For example, as shown in fig. 3, the sliding track diagram is a schematic diagram of a sliding track of a single-hand sliding operation when the user slides on the touch display screen of the mobile device with the thumb of the left hand. In fig. 3, a coordinate system is established with the vertex at the upper left corner of the mobile device touch display screen as the origin of coordinates, the horizontal right direction as the positive X-axis direction, and the vertical downward direction as the positive Y-axis direction, and in this coordinate system, the start position coordinates of the sliding track are P1(X1, Y1) and the end position coordinates are P2(X2, Y2).
For another example, as shown in fig. 4, the sliding track diagram is a schematic diagram of a sliding track of a single-hand sliding operation when the user slides on the touch display screen of the mobile device using the thumb of the right hand. In fig. 4, a coordinate system is established with the vertex at the upper left corner of the touch display screen of the mobile device as the origin of coordinates, the horizontal right direction as the positive direction of the X axis, and the vertical downward direction as the positive direction of the Y axis, and in the coordinate system, the start position coordinates of the sliding track are P1(X1, Y1) and the end position coordinates are P2(X2, Y2).
In an embodiment, the behavioral data may also include user identification, acquisition time, and the like.
The following explains a specific implementation of this step 201:
(1) the mobile equipment collects the explanation of the behavior data when the user operates the mobile equipment with one hand in a set time period:
in one embodiment, the mobile device may collect behavior data of the user when the user operates the mobile device with one hand within a set time period based on an externally input collection instruction. It is to be understood that, in this embodiment, the above-described acquisition instruction may carry a set period of time.
In an exemplary scenario, after downloading the video application for the first time, the user may input the capture instruction to the mobile device through a functional interface provided by the video application, so as to instruct the mobile device to capture behavior data of the user when the user operates the mobile device with one hand within a set time period.
In another embodiment, the mobile device may periodically collect behavior data when the mobile device is operated by a single hand of the user for a set period of time. For example, the mobile device may collect behavior data of a user operating the mobile device with one hand on the first day of each month, that is, the set time period is the first day of each month.
Further, in an embodiment, the mobile device may store behavior data collected within a set time period when the user operates the mobile device with one hand, so that the mobile device may subsequently execute the video recommendation method provided by the present invention.
When the mobile device periodically collects behavior data of a user operating the mobile device with one hand in a set time period, the mobile device updates the behavior data stored at the local terminal every time a collection period elapses, that is, the mobile device only stores the latest collected behavior data. The video recommendation method and the video recommendation system can realize video recommendation to the user based on the latest behavior habit of the user, and better meet the operation experience of the user.
In another embodiment, the mobile device may send behavior data collected within a set time period when the user operates the mobile device with one hand to a corresponding server, so that the server may subsequently execute the video recommendation method provided by the present invention.
When the mobile device periodically collects behavior data of a user operating the mobile device with one hand in a set time period, the server deletes the behavior data of the user received last time every time the server receives the behavior data of the same user, namely, the server only stores the latest collected behavior data of the mobile device. The video recommendation method and the video recommendation system can realize video recommendation to the user based on the latest behavior habit of the user, and better meet the operation experience of the user.
(2) Dividing behavior data collected by the mobile equipment in a set time period and obtained when a user operates the mobile equipment with one hand to obtain an explanation of at least one data group:
first, when the server executes the video recommendation method provided by the present invention, the server side may store behavior data of multiple users sent by multiple mobile devices, and based on this, in this step 201, the server may determine behavior data belonging to the same user based on the user identifier, and then divide the behavior data of the same user.
In an embodiment, for each piece of pedestrian data, a corresponding time segment is determined according to the acquisition time of the behavior data, the behavior data corresponding to the same time segment is divided into the same data group, and the behavior data corresponding to different time segments are divided into different data groups, so that different data groups belong to different time segments.
The behavior characteristics are used for representing human body parts used when the user operates the mobile equipment with one hand in the corresponding time slice.
In an embodiment, taking one of the data sets as an example, determining the corresponding behavior feature of the user in the time slice to which the data set belongs according to the behavior data in the data set includes the following steps:
a1, determining the human body part used when the user operates the mobile equipment with one hand according to the behavior data aiming at each behavior data in the data set.
In step a1, the start position coordinates and the end position coordinates may be calculated according to a set angle calculation method to obtain a first angle, and then the human body part used when the user operates the mobile device with one hand may be determined according to the magnitude of the first angle according to an empirical value.
The set angle calculation formula is shown as the following formula (I):
as shown in fig. 3 and 4, the first angle calculated according to the above formula (one) is ^ a in fig. 3 and 4.
In an embodiment, if the first angle satisfies a first setting condition as exemplified below, the part of the human body used when the user operates the mobile device with one hand is determined to be a left hand of the human body; if the first angle satisfies a second setting condition as exemplified below, it is determined that the part of the human body used when the user operates the mobile device with one hand is the right hand of the human body.
The first setting condition: less than or equal to;
the second setting condition: the angle beta-is less than or equal to 180 degrees-is less than or equal to angle beta +;
the above-mentioned ≈ beta and ≈ alpha are preset empirical values.
a2, determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs.
a3, determining the behavior characteristics of the user in the time slice to which the data group belongs based on the first times and the second times.
In one embodiment, the first number and the second number are compared, and if the first number is greater than the second number, it means that the user tends to operate the mobile device with the left hand in the time slice to which the data set belongs, and therefore, the behavior characteristic of the user in the time slice to which the data set belongs indicates that the part of the human body used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the left hand. On the contrary, if the second number is greater than the first number, it means that the user tends to operate the mobile device with the right hand in the time slice to which the data set belongs, and therefore, the behavior feature of the user in the time slice to which the data set belongs indicates that the part of the human body used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the right hand.
In another embodiment, the weight ratio P1 of the first time is calculated by the following formula (two), and if the calculated weight ratio P1 is greater than or equal to a preset weight ratio threshold, it means that the user tends to use the left hand to operate the mobile device in the time slice to which the data set belongs, so the behavior characteristic of the user in the time slice to which the data set belongs indicates that the human body part used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the left hand; on the contrary, if the calculated weight ratio P1 is smaller than the preset weight ratio threshold, it means that the user tends to operate the mobile device with the right hand in the time slice to which the data set belongs, and therefore, the behavior feature of the user in the time slice to which the data set belongs indicates that the human body part used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the right hand.
In the above formula (two), S1 represents the first order and S2 represents the second order.
In yet another embodiment, the weight ratio P2 of the second time is calculated by the following formula (three), if the calculated weight ratio P2 is greater than or equal to the preset weight ratio threshold, it means that the user tends to use the right hand to operate the mobile device in the time slice to which the data set belongs, and therefore, the behavior characteristics of the user in the time slice to which the data set belongs indicate that the human body part used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the right hand; on the contrary, if the calculated weight ratio P1 is smaller than the preset weight ratio threshold, it means that the user tends to use the left hand to operate the mobile device in the time slice to which the data set belongs, and therefore, the behavior characteristics of the user in the time slice to which the data set belongs indicate that the human body part used when the user operates the mobile device with one hand in the time slice to which the data set belongs is the left hand.
In addition, in an embodiment, after step 202 is executed, the corresponding behavior characteristics of the user in each time slice may be stored according to a storage format of key-value. For example, the behavior characteristics corresponding to the user in each time slice are stored as (T1, 1/0), (T2, 1/0), (T3, 1/0), … …, and (Tn, 1/0), where T1 to Tn represent n time slices, 1 represents that the human body part used when the user operates the mobile device with one hand in the corresponding time slice is the left hand, and 0 represents that the human body part used when the user operates the mobile device with one hand in the corresponding time slice is the right hand. By the storage method, the corresponding behavior characteristics of the user in a certain time segment can be conveniently determined subsequently.
In step 203, a time segment (hereinafter referred to as a target time segment) to which the current time belongs is determined according to the start time and the end time of each time segment, and then the corresponding behavior feature of the determined user in the target time segment is determined as a target behavior feature.
And 204, sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to the sequencing result.
It can be understood that if the target behavior feature indicates that the human body part used when the user operates the mobile device with one hand in the target time slice is the left hand of the human body, this means that the more the display position of the video icon of the recommended video on the interface is biased to the left side, the more convenient the user clicks the video icon; on the contrary, if the target behavior feature indicates that the human body part used when the user operates the mobile device with one hand in the target time segment is the right hand of the human body, this means that the more the display position of the video icon of the recommended video on the interface is biased to the right side, the more convenient the user clicks the video icon. Therefore, the ordering rules of the recommended videos are different under different target behavior characteristics.
In an embodiment, if the target behavior feature indicates that the part of the human body used when the user operates the mobile device with one hand in the target time slice is the left hand of the human body, the recommended videos are sorted in the order of the recommended priority from high to low. This can realize on the interface, according to from right to left order, the recommendation priority of the recommendation video that shows is from low to high ranking, namely, the nearer to the left side, the higher the recommendation priority, and the higher the recommendation priority is higher, shows that the user is more interested in watching of recommendation video, therefore, can realize that the user can click the recommendation video of interest easily when using left-handed operation mobile device, promotes user's operation experience.
And if the target behavior characteristics indicate that the part of the human body used when the user operates the mobile equipment with one hand in the target time slice is the right hand of the human body, sequencing the recommended videos according to the sequence of the recommended priority from low to high. This can realize on the interface, according to from left to right order, the recommendation priority of the recommendation video that shows is from low to high ranking, and is closer to the right side, and the recommendation priority is higher, therefore, can realize that the user can click the recommendation video of sense of interest easily when using the right hand operation mobile device, promotes user's operation experience.
In an example, the recommendation priority may be represented by a video playing popularity, and specifically, the higher the video playing popularity, the higher the recommendation priority.
In another example, the recommendation priority may be represented by a video relevance, where the video relevance refers to a relevance between the recommended video and a video currently being played, and specifically, the higher the video relevance, the higher the recommendation priority.
It should be noted that the above two examples are merely exemplary illustrations of the recommendation priority, and in practical applications, the recommendation priority may also be related to other parameters, and the present invention is not limited thereto.
So far, the description about the flow shown in fig. 2 is completed.
According to the technical scheme provided by the embodiment of the invention, behavior data which are collected by the mobile equipment within a set time period and used when the user operates the mobile equipment with one hand are divided to obtain at least one data group, different data groups belong to different time segments, corresponding behavior characteristics of the user within each time segment are determined according to the behavior data in each data group, the behavior characteristics are used for representing human body parts which are used when the user operates the mobile equipment with one hand within the corresponding time segment, and the human body parts comprise a left hand or a right hand of the human body, so that the behavior habit of the user in one-hand operation within different time segments is obtained.
Further, when video recommendation of the user is determined, the target behavior characteristics matched with the current time are determined from the corresponding behavior characteristics of the determined user in each time slice, the recommended videos are sorted according to the target behavior characteristics, and the video recommendation is performed on the user according to the sorting result, so that the transverse arrangement sequence of the recommended videos on the video playing interface is dynamically determined according to the single-hand operation behavior habit of the user in the time slice to which the current time belongs, the user can easily click the interested recommended videos, the operation experience of the user is improved, and the click playing amount of the recommended videos is further improved.
Corresponding to the embodiment of the video recommendation method, the invention also provides an embodiment of a video recommendation device.
As shown in fig. 5, a block diagram of an embodiment of a video recommendation apparatus according to an embodiment of the present invention is provided, where the apparatus includes: a data partitioning module 51, a first determining module 52, a second determining module 53, and a video recommending module 54.
The data dividing module 51 is configured to divide behavior data acquired by the mobile device within a set time period and used when a user operates the mobile device with one hand, so as to obtain at least one data group, where different data groups belong to different time slices;
a first determining module 52, configured to determine, according to the behavior data in each data set, a behavior feature corresponding to each time slice of the user, where the behavior feature is used to represent a human body part used when the user operates the mobile device with one hand in the corresponding time slice, and the human body part includes a left human body hand or a right human body hand;
a second determining module 53, configured to, when it is determined to perform video recommendation on the user, determine, from the determined behavior features corresponding to the user in each time segment, a target behavior feature that matches the current time;
and the video recommending module 54 is configured to sort the recommended videos according to the target behavior characteristics, and recommend the videos to the user according to a sorting result.
In a possible embodiment, the data dividing module 51 divides behavior data collected by the mobile device in a set time period and obtained when the mobile device is operated by a single hand of a user, so as to obtain at least one data group, including:
dividing the set time period according to a set time interval to obtain a plurality of time segments;
determining corresponding time segments according to the acquisition time of each piece of behavior data, dividing the behavior data corresponding to the same time segment into the same data group, and dividing the behavior data corresponding to different time segments into different data groups.
In a possible embodiment, the determining module 52 determines the corresponding behavior feature of the user in each time segment according to the behavior data in each data set, including:
for each behavior data in each data set, determining a human body part used when the user operates the mobile equipment with one hand according to the behavior data;
determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs;
and determining the corresponding behavior characteristics of the user in the time slice to which the data set belongs based on the first times and the second times.
In one possible embodiment, the behavior data includes: starting position coordinates and ending position coordinates of one-hand sliding operation on the display screen of the mobile equipment;
the first determining module 52 determines the human body part used when the user operates the mobile device with one hand according to the behavior data, including:
calculating the initial position coordinate and the end position coordinate according to a set angle calculation mode to obtain a first angle;
if the first angle meets a first set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the left hand of the human body;
and if the first angle meets a second set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the right hand of the human body.
In a possible implementation manner, the second determining module 53 determines, from the determined behavior features corresponding to the user in each time segment, a target behavior feature matching the current time, including:
determining a target time segment to which the current time belongs according to the starting time and the ending time of each time segment;
and determining the corresponding behavior characteristics of the determined user in the target time segment as the target behavior characteristics.
In a possible implementation manner, the video recommending module 54 ranks videos to be recommended according to the target behavior feature, including:
if the target behavior characteristics indicate that the human body part used when the user operates the mobile equipment with one hand in the target time slice is the left hand of the human body, sequencing the recommended videos according to the recommended priority from high to low;
and if the target behavior characteristics indicate that the part of the human body used when the user operates the mobile equipment with one hand in the target time segment is the right hand of the human body, sequencing the recommended videos according to the sequence of the recommended priority from low to high.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, where the electronic device 600 shown in fig. 6 includes: at least one processor 601, memory 602, at least one network interface 604, and other user interfaces 603. The various components in the electronic device 600 are coupled together by a bus system 605. It is understood that the bus system 605 is used to enable communications among the components. The bus system 605 includes a power bus, a control bus, and a status signal bus in addition to a data bus. For clarity of illustration, however, the various buses are labeled as bus system 605 in fig. 6.
The user interface 603 may include, among other things, a display, a keyboard, or a pointing device (e.g., a mouse, trackball, touch pad, or touch screen, among others.
It will be appreciated that the memory 602 in embodiments of the invention may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. The non-volatile memory may be a Read-only memory (ROM), a programmable Read-only memory (PROM), an erasable programmable Read-only memory (erasabprom, EPROM), an electrically erasable programmable Read-only memory (EEPROM), or a flash memory. The volatile memory may be a Random Access Memory (RAM) which functions as an external cache. By way of example, but not limitation, many forms of RAM are available, such as static random access memory (staticaram, SRAM), dynamic random access memory (dynamic RAM, DRAM), synchronous dynamic random access memory (syncronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced synchronous SDRAM (ESDRAM), synchronous link SDRAM (synchlink DRAM, SLDRAM), and direct memory bus RAM (DRRAM). The memory 602 described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, memory 602 stores the following elements, executable units or data structures, or a subset thereof, or an expanded set thereof: an operating system 6021 and an application 6022.
The operating system 6021 includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application program 6022 includes various application programs such as a media player (MediaPlayer), a Browser (Browser), and the like, and is used to implement various application services. A program implementing the method of an embodiment of the invention may be included in the application program 6022.
In the embodiment of the present invention, by calling a program or an instruction stored in the memory 602, specifically, a program or an instruction stored in the application program 6022, the processor 601 is configured to execute the method steps provided by the method embodiments, for example, including:
dividing behavior data acquired by a mobile device within a set time period and obtained when a user operates the mobile device with one hand to obtain at least one data group, wherein different data groups belong to different time slices;
determining behavior characteristics corresponding to the user in each time slice according to behavior data in each data group, wherein the behavior characteristics are used for representing human body parts used when the user operates the mobile equipment with one hand in the corresponding time slice, and the human body parts comprise a left human body hand or a right human body hand;
when video recommendation of the user is determined, determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice;
and sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to a sequencing result.
The method disclosed by the above-mentioned embodiment of the present invention can be applied to the processor 601, or implemented by the processor 601. The processor 601 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 601. The processor 601 may be a general-purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, or discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software elements in the decoding processor. The software cells may be located in ram, flash, rom, prom, eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 602, and the processor 601 reads the information in the memory 602 and completes the steps of the method in combination with the hardware thereof.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units designed to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques described herein may be implemented by means of units performing the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
The electronic device provided in this embodiment may be the electronic device shown in fig. 6, and may perform all the steps of the video recommendation method shown in fig. 2, so as to achieve the technical effect of the video recommendation method shown in fig. 2, please refer to the description related to fig. 2 for brevity, which is not described herein again.
The embodiment of the invention also provides a storage medium (computer readable storage medium). The storage medium herein stores one or more programs. Among others, the storage medium may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as read-only memory, flash memory, a hard disk, or a solid state disk; the memory may also comprise a combination of memories of the kind described above.
When one or more programs in the storage medium can be executed by one or more processors, the automatic printing method executed on the electronic equipment side is realized.
The processor is used for executing the video recommendation program stored in the memory to realize the following steps of the video recommendation method executed on the electronic equipment side:
dividing behavior data acquired by a mobile device within a set time period and obtained when a user operates the mobile device with one hand to obtain at least one data group, wherein different data groups belong to different time slices;
determining behavior characteristics corresponding to the user in each time slice according to behavior data in each data group, wherein the behavior characteristics are used for representing human body parts used when the user operates the mobile equipment with one hand in the corresponding time slice, and the human body parts comprise a left human body hand or a right human body hand;
when video recommendation of the user is determined, determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice;
and sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to a sequencing result.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. A method for video recommendation, comprising:
dividing behavior data acquired by a mobile device within a set time period and obtained when a user operates the mobile device with one hand to obtain at least one data group, wherein different data groups belong to different time slices;
determining corresponding behavior characteristics of the user in each time slice according to behavior data in each data group, wherein the behavior characteristics are used for representing human body parts used when the user operates the mobile equipment with one hand in the corresponding time slice, and the human body parts comprise a left hand or a right hand of the human body;
when video recommendation of the user is determined, determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice;
and sequencing the recommended videos according to the target behavior characteristics, and recommending the videos to the user according to the sequencing result.
2. The method of claim 1, wherein the dividing behavior data collected by the mobile device within a set time period and obtained when the mobile device is operated by a single hand of a user to obtain at least one data group comprises:
dividing the set time period according to a set time interval to obtain a plurality of time segments;
determining corresponding time segments according to the acquisition time of each piece of behavior data, dividing the behavior data corresponding to the same time segment into the same data group, and dividing the behavior data corresponding to different time segments into different data groups.
3. The method of claim 1, wherein determining the corresponding behavior characteristics of the user in each of the time slices according to the behavior data in each of the data sets comprises:
for each behavior data in each data set, determining a human body part used when the user operates the mobile equipment with one hand according to the behavior data;
determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs;
and determining the corresponding behavior characteristics of the user in the time slice to which the data set belongs based on the first times and the second times.
4. The method of claim 3, wherein the behavior data comprises: starting position coordinates and ending position coordinates of one-hand sliding operation on the display screen of the mobile equipment;
the determining the human body part used when the user operates the mobile device with one hand according to the behavior data comprises:
calculating the initial position coordinate and the termination position coordinate according to a set angle calculation mode to obtain a first angle;
if the first angle meets a first set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the left hand of the human body;
and if the first angle meets a second set condition, determining that the part of the human body used when the user operates the mobile equipment with one hand is the right hand of the human body.
5. The method of claim 1, wherein determining the target behavior feature matching the current time from the determined behavior features corresponding to the user in each time slice comprises:
determining a target time segment to which the current time belongs according to the starting time and the ending time of each time segment;
and determining the corresponding behavior feature of the determined user in the target time segment as the target behavior feature.
6. The method according to claim 5, wherein the sorting videos to be recommended according to the target behavior characteristics comprises:
if the target behavior characteristics indicate that the human body part used when the user operates the mobile equipment with one hand in the target time slice is the left hand of the human body, sequencing the recommended videos according to the recommended priority from high to low;
and if the target behavior characteristics indicate that the part of the human body used when the user operates the mobile equipment with one hand in the target time slice is the right hand of the human body, sequencing the recommended videos according to the sequence of the recommended priority from low to high.
7. A video recommendation apparatus, comprising:
the data dividing module is used for dividing behavior data which are acquired by the mobile equipment within a set time period and are acquired by a user when the user operates the mobile equipment with one hand to obtain at least one data group, wherein different data groups belong to different time slices;
a first determining module, configured to determine, according to behavior data in each of the data sets, behavior features corresponding to the user in each of the time segments, where the behavior features are used to represent a human body part used when the user operates a mobile device with one hand in the corresponding time segment, and the human body part includes a left hand or a right hand of a human body;
the second determining module is used for determining target behavior characteristics matched with the current time from the determined behavior characteristics corresponding to the user in each time slice when the video recommendation of the user is determined;
and the video recommending module is used for sequencing the recommended videos according to the target behavior characteristics and recommending the videos to the user according to the sequencing result.
8. The apparatus of claim 7, wherein the first determining module determines the corresponding behavior feature of the user in each time slice according to the behavior data in each data set, and comprises:
for each behavior data in each data set, determining a human body part used when the user operates the mobile equipment with one hand according to the behavior data;
determining a first number of times that the user operates the mobile device with the left hand of the human body and a second number of times that the user operates the mobile device with the right hand of the human body in the time slice to which the data set belongs;
and determining the corresponding behavior characteristics of the user in the time slice to which the data set belongs based on the first times and the second times.
9. An electronic device, comprising: a processor and a memory, the processor being configured to execute a video recommendation program stored in the memory to implement the video recommendation method of any one of claims 1-6.
10. A storage medium storing one or more programs, the one or more programs being executable by one or more processors to implement the video recommendation method of any one of claims 1-6.
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