CN110647680A - User browsing behavior analysis method and device - Google Patents
User browsing behavior analysis method and device Download PDFInfo
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- CN110647680A CN110647680A CN201910840472.0A CN201910840472A CN110647680A CN 110647680 A CN110647680 A CN 110647680A CN 201910840472 A CN201910840472 A CN 201910840472A CN 110647680 A CN110647680 A CN 110647680A
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Abstract
The embodiment of the application provides a method and a device for analyzing user browsing behaviors, wherein the method comprises the following steps: determining browsing behaviors of a user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content; determining the reading preference of a user for the preset target segment according to the browsing behavior; according to the method and the device, the browsing behaviors of the user on different target segments in the target content can be accurately analyzed, the reading preference of the user on each target segment is further determined, and the user portrait of the reading preference degree of the user on each target segment is established.
Description
Technical Field
The application relates to the field of behavior analysis, in particular to a user browsing behavior analysis method and device.
Background
In the existing technical scheme for analyzing the browsing behavior of the user, the analysis of the browsing content is mainly based on a tag added to the whole article during preprocessing, and is combined with statistics of access data of the article (such as reading time, reading final position, access frequency and the like), but the existing method can only analyze the tag based on the whole article, and even if the segmented content is tagged, the access data describes the whole article, and the data analysis cannot be performed on the segmented tag, for example: the method comprises the steps of obtaining a first article, namely a three story rule, a first article, namely an alley story, a second article, namely a joke story, and a third encouragement story, wherein tags of the articles can be stories or stories, alleys, jokes and encourages, through statistics of reading data of users of the articles, only data which are interesting or uninteresting to the four tags of the articles by readers can be obtained, if the readers only see the alley stories and the joke story, the encouragement story is not interesting, the data are simply skipped, but the reading data statistics only can analyze the whole article, the users cannot analyze uninteresting to the encouragement story, and further the analysis of the behaviors of the users during content reading is inaccurate.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a user browsing behavior analysis method and device, which can accurately analyze the browsing behavior of a user on different target segments in target content, further determine the reading preference of the user on each target segment, and construct a user portrait for obtaining the reading preference degree of the user on each target segment.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a method for analyzing a browsing behavior of a user, including:
determining browsing behaviors of a user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content;
and determining the reading preference of the user for the preset target segment according to the browsing behavior.
Further, the determining, according to the reading time of a preset target segment in the target content in a preset browser target reading area when the user browses the target content, the browsing behavior of the user on the preset target segment includes:
judging whether the target fragment is located in at least one preset browser target reading area or not according to the coordinate position of the target fragment in the browser in unit reading time and the coordinate position of the preset browser target reading area, if so, obtaining a corresponding target weight value according to the browser target reading area in which the target fragment is located, and otherwise, judging that the target fragment is in an off-screen state;
and determining the corresponding browsing behaviors according to the numerical comparison result of the sum of the weighted values obtained in each unit reading time in the set reading time period and the preset weight threshold value of each browsing behavior.
Further, the determining, according to the coordinate position of the target segment in the browser within the unit reading time and the coordinate position of the preset browser target reading area, whether the target segment is located in at least one preset browser target reading area, and if so, obtaining a corresponding target weight value according to the browser target reading area where the target segment is located, including:
respectively judging whether the coordinate position of the target segment in the browser is coincident with the coordinate position of each preset browser target reading area;
if so, obtaining the sum of the weight values according to the weight values respectively corresponding to the preset browser target reading areas superposed with the coordinate positions of the target segments, and setting the sum of the weight values as the target weight value.
Further, after the determining that the target segment is in the off-screen state, the method includes:
judging whether the off-screen time length of the target fragment in the one-off-screen state is greater than a preset off-screen time length threshold value or not;
if so, judging whether the perusal browsing behaviors exist before the off-screen state and after the off-screen state according to the comparison result of the sum of the weighted values obtained in each unit reading time before the off-screen state and after the off-screen state and the preset perusal threshold value of the perusal browsing behaviors, and if so, judging that the browsing behaviors of the user on the target segment are rereading behaviors.
Further, the determining, according to the reading time of a preset target segment in the target content in a preset browser target reading area when the user browses the target content, the browsing behavior of the user on the preset target segment, further includes:
determining the target segments of which two adjacent browsing behaviors are perusal browsing behaviors according to the reading time of each preset target segment in a set reading time period in the target reading area of the same browser and the numerical comparison result of the reading time and the preset time threshold of each browsing behavior;
and setting the browsing behavior of the target segment between the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors as the skip browsing behavior.
Further, before the step of obtaining a sum of the weight values according to the weight values respectively corresponding to the preset browser target reading areas coinciding with the coordinate positions of the target segments, the method includes:
presetting at least one browser target reading area in a display area of the browser, and respectively setting corresponding weight values according to the coordinate position in the display area of the browser of each browser target reading area.
Further, the determining, according to the browsing behavior, a reading preference of the user for the preset target segment includes:
determining a reading preference weight value of the target segment according to the chapter position of the target segment in the target content;
and determining the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value and the conversion relation between each browsing behavior and each reading preference.
In a second aspect, the present application provides an apparatus for analyzing browsing behavior of a user, including:
the browsing behavior determining module is used for determining the browsing behavior of a user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content;
and the reading preference determining module is used for determining the reading preference of the user for the preset target segment according to the browsing behavior.
Further, the browsing behavior determination module includes:
the target weight value determining unit is used for judging whether the target fragment is positioned in at least one preset browser target reading area or not according to the coordinate position of the target fragment in the browser in unit reading time and the coordinate position of the preset browser target reading area, if so, obtaining a corresponding target weight value according to the browser target reading area in which the target fragment is positioned, and otherwise, judging that the target fragment is in an off-screen state;
and the weighted value comparison unit is used for determining the corresponding browsing behaviors according to the numerical comparison result of the sum of weighted values obtained in each unit reading time in the set reading time period and the preset weighted threshold value of each browsing behavior.
Further, the target weight value determination unit includes:
the coordinate position judging subunit is used for respectively judging whether the coordinate position of the target segment in the browser coincides with the coordinate position of each preset browser target reading area;
and the multi-weight value summing subunit is used for obtaining a sum of weight values according to the weight values respectively corresponding to the preset browser target reading areas coinciding with the coordinate positions of the target segments when the coordinate positions of the target segments in the browser are judged to coincide with the coordinate positions of the preset browser target reading areas, and setting the sum of the weight values as the target weight value.
Further, still include:
the off-screen time judging unit is used for judging whether the off-screen time length of the target fragment in the one-time off-screen state is greater than a preset off-screen time length threshold value or not;
and the rereading behavior judging unit is used for judging whether the perusal behavior exists before the off-screen state and after the off-screen state according to the comparison result of the sum of weighted values obtained by each unit reading time before the off-screen state and after the off-screen state and the preset perusal threshold value of the perusal behavior when the off-screen time of the target fragment in the one-time off-screen state is judged to be larger than the preset off-screen time threshold value, and judging that the browsing behavior of the target fragment by the user is the rereading behavior if the rereading behavior exists before the off-screen state and after the off-screen state.
Further, the browsing behavior determination module further includes:
the reading time comparison unit is used for determining the target segments of two adjacent browsing behaviors as the fine reading browsing behaviors according to the reading time of each preset target segment in the target reading area of the same browser in a set reading time period and the numerical comparison result of the reading time and the preset time threshold of each browsing behavior;
and the skip behavior determining unit is used for setting the browsing behavior of the target segment between the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors as the skip browsing behavior.
Further, still include:
the reading area weight value determining unit is used for presetting at least one browser target reading area in a display area of the browser and respectively setting corresponding weight values according to the coordinate position in the display area of the browser of each browser target reading area.
Further, the reading preference determining module comprises:
a reading preference weight value determining unit, configured to determine a reading preference weight value of the target segment according to a chapter position of the target segment in the target content;
and the reading preference determining unit is used for determining the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value and the conversion relation between each browsing behavior and each reading preference.
In a third aspect, the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the user browsing behavior analysis method when executing the program.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, performs the steps of the user browsing behavior analysis method.
According to the technical scheme, the method and the device for analyzing the browsing behavior of the user are characterized in that a target reading area of a browser is preset in a display area of the browser, the browsing behavior of the user for the target segment is determined according to the retention time (namely the reading time of the target segment to be read) of a preset target segment in the target content when the user browses the target content, and the reading preference of the user for the target segment is further determined.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a user browsing behavior analysis method in an embodiment of the present application;
fig. 2 is a second flowchart illustrating a user browsing behavior analysis method according to an embodiment of the present application;
fig. 3 is a third schematic flowchart of a user browsing behavior analysis method in the embodiment of the present application;
FIG. 4 is a fourth flowchart illustrating a user browsing behavior analysis method according to an embodiment of the present application;
FIG. 5 is a fifth flowchart illustrating a user browsing behavior analysis method according to an embodiment of the present application;
fig. 6 is a sixth schematic flowchart of a user browsing behavior analysis method in the embodiment of the present application;
fig. 7 is one of the structural diagrams of a user browsing behavior analysis apparatus in the embodiment of the present application;
fig. 8 is a second block diagram of a user browsing behavior analysis apparatus according to an embodiment of the present application;
fig. 9 is a third block diagram of a user browsing behavior analysis apparatus in an embodiment of the present application;
fig. 10 is a fourth structural diagram of a user browsing behavior analysis apparatus in the embodiment of the present application;
fig. 11 is a fifth configuration diagram of a user browsing behavior analysis apparatus in the embodiment of the present application;
FIG. 12 is a diagram illustrating an embodiment of a preset target reading area of a browser in a display area of the browser;
FIG. 13 is a second schematic diagram illustrating a preset target reading area of a browser in a display area of the browser according to the embodiment of the present application;
fig. 14 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. 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 application.
Considering the existing technical solution for analyzing the browsing behavior of the user, the analysis of the browsing content is mainly based on the tags added to the whole article during the preprocessing, and combines with statistics of the access data of the article (such as reading time, reading final position, access frequency, etc.), but the existing method can only analyze the tags based on the whole article, and even if the tags are performed on the segmented content, the access data describes the whole article, and the data analysis cannot be performed on the segmented tags, thereby causing the problem of inaccurate behavior analysis when the user reads the content, the application provides a user browsing behavior analysis method and device, by presetting a browser target reading area in a browser display area, and according to the staying time of the preset target segment in the target content (i.e. the reading time of the target segment) in the browser target reading area when the user browses the target content, the browsing behavior of the user for the target segment is determined, the reading preference of the user for the target segment is further determined, and the reading preference of the user for each target segment in the target content can be analyzed, so that the analysis of the browsing behavior of the user is more detailed, the analysis granularity is small, the obtained analysis result of the user behavior is more accurate and has more commercial utilization value, and the user portrait further constructed and obtained is more accurate.
In order to accurately analyze the browsing behavior of the user on different target segments in the target content and further determine the reading preference of the user on each target segment, the application provides an embodiment of a user browsing behavior analysis method, which specifically includes the following contents, with reference to fig. 1:
step S101: and determining the browsing behavior of the user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content.
It is understood that when a user reads target content using an existing browser in a computer or a mobile phone, the user has a common reading habit (e.g., reading from left to right, top to bottom), and generally looks at the top 1/3-1/2 area of the browser screen, and scrolls the content to read line by line. The normal reading speed is typically 200-300 words per minute, and when the user encounters the content of interest, the reading speed is slowed down, which in turn results in the content remaining at the region for an extended period of time to enter a perusal state, when the user encounters no interest, the user quickly skips the content in the region, and when the user encounters a high preference, the user scrolls the content to the region again to enter a rereading state.
Alternatively, the target content may be a complete article loaded and displayed by a browser or all text loaded on a webpage, and the target segment is a segment (e.g., a segment of text describing an apple and/or a picture of an apple) included in the target content.
Alternatively, according to the common reading habit of the user, at least one browser target reading area may be set in advance according to the actual size of the display screen of the browser, and specifically, the system can store the coordinate position of each browser target reading area, that is, for example, a browser display screen with a size of 480 times 320, and 4 different browser target reading areas A, B, C and D are set, where the coordinate position of the browser target reading area a is: the coordinate axis x is 0, the coordinate axis y is 0, the width is 320, and the height is 80, and the coordinate position of the browser target reading area B is: the coordinate axis x is 0, the coordinate axis y is 80, the width is 320, and the height is 160, and the coordinate position of the browser target reading area C is: the coordinate axis x is 0, the coordinate axis y is 240, the width is 320, and the height is 160, and the coordinate position of the browser target reading area D is: the coordinate axis x is 0, the coordinate axis y is 400, the width is 320, and the height is 80, and the browser target reading area B is an area that the user can most easily watch when reading, as is known from the common reading habit of the user.
Optionally, when the reading time of the target segment in the preset browser target reading area is collected, the reading time of the target segment in the preset browser target reading area may be continuously recorded through an existing data monitoring technology, or whether the target segment is in the preset browser target reading area may be detected once every other fixed time period through the existing data monitoring technology, and a weight value corresponding to the browser target reading area is simultaneously taken, so that the sum of the acquired weight values in the set time period represents the reading time of the target segment in the preset browser target reading area.
Optionally, when the reading time of the target segment in the preset browser target reading area is calculated, the real-time coordinate position of the target segment in the browser display page may be obtained through the existing page data monitoring technology, and compared with the coordinate position of the preset browser target reading area, so as to determine whether the current target segment is located in the preset browser target reading area and which preset browser target reading area is specifically located.
Specifically, for example, an article describing various fruits is stored in the server database, before page loading is performed on the article, a content tag "apple" corresponding to the 40 th to 55 th characters describing an apple in the article may be added to the server side in advance, that is, an attribute of "apple" in the HTML technology is added to the 40 th to 55 th characters, when HTML page loading is performed, the tag attribute is added to a div tag before the 40 th to 55 th characters, for example, "< div tag ═ apple" > 40 th to 55 th characters </div > ", when a user slides and browses the entire article, a real-time coordinate position of the tag having the tag attribute may be obtained through a JavaScript technology responsible for a page layout function, and the real-time coordinate position is compared with a pre-stored coordinate position of a preset browser target reading area, so as to determine whether a current target segment (the 40 th to 55 th characters described by the apple) is located in the preset browser target reading area The area and the specific position are preset browser target reading areas.
It can be understood that the specific setting position and the specific number of the preset browser target reading areas can be flexibly set according to the actual size of the browser display screen and human experience, and the application is not specifically limited herein and can highlight the area which is most easily watched by the user.
It can be understood that the browsing behaviors may be browsing behaviors, such as overview, rough reading, fine reading, skip reading, repeat reading, and the like, which are expressed according to the degree of interest of the user when the user reads the target segment in the target content, and each browsing behavior may correspond to a specific duration of reading time of a different target segment in a preset browser target reading area.
Step S102: and determining the reading preference of the user for the preset target segment according to the browsing behavior.
It can be understood that each browsing behavior (for example, overview, rough reading, fine reading, skip reading, repeat reading, etc.) corresponds to a specific duration of reading time of a different target segment in a preset browser target reading area, so that the reading preference of the user for each preset target segment can be determined by the application.
Optionally, different browsing behaviors may directly correspond to different reading preferences, or weight calculation may be performed according to the different browsing behaviors in combination with other factors affecting the reading preferences, and the final reading preferences are obtained after comprehensive analysis.
In one embodiment, the target segment with browsing behavior of "overview, rough reading and skip reading" may be defined as the reading preference of "not interested", and the target segment with browsing behavior of "perusal and rereading" may be defined as the reading preference of "interested".
In another embodiment, different reading preference weights are set for each target segment in advance, for example, a lower weight 0.8 is set for the target segment describing the full-text catalogue content, a higher weight 1.2 is set for the target segment describing the full-text prolog content, and a calculation initial value overview is set for the predefined browsing behaviors "overview, rough reading, fine reading, skip reading, and repeat reading", respectively: 0.6, 0.8 for rough reading, 1.0 for fine reading, 0.5 for skip reading and 1.2 for repeat reading, when the browsing behavior corresponding to the target segment describing the full-text catalogue content is overview, the final reading preference value is 0.6 times 0.8 and is equal to 0.48, when the browsing behavior corresponding to the target segment describing the full-text prolog content is fine reading, the final reading preference value is 1.0 times 1.2 and is equal to 1.2, meanwhile, the target segment with the final reading preference value lower than 1 can be set as the reading preference of 'uninteresting', the target segment with the final reading preference value not lower than 1 is set as the reading preference of 'interested', so that the reading preference of the user corresponding to the target segment describing the full-text catalogue content can be known as 'uninterested', and the reading preference of the user corresponding to the target segment describing the full-text prolog content is 'interested'.
As can be seen from the above description, the method for analyzing browsing behavior of a user provided in the embodiment of the present application can determine the browsing behavior of the user for the target segment by presetting the target reading area of the browser in the display area of the browser and according to the retention time (i.e. the reading time of the target segment being read) of the preset target segment in the target content when the user browses the target content, and further determine the reading preference of the user for the target segment.
In order to determine corresponding different browsing behaviors according to different durations of reading time of the preset target segment in the preset browser target reading area, in an embodiment of the user browsing behavior analysis method of the present application, referring to fig. 2, the following may be further specifically included:
step S201: judging whether the target fragment is located in at least one preset browser target reading area or not according to the coordinate position of the target fragment in the browser in unit reading time and the coordinate position of the preset browser target reading area, if so, obtaining a corresponding target weight value according to the browser target reading area in which the target fragment is located, and otherwise, judging that the target fragment is in an off-screen state.
It is understood that a higher weighting value may be set for a preset browser target reading area close to the user watching area and conforming to the user' S common reading habit, and a lower weighting value may be set for a preset browser target reading area far from the user watching area, for example, a weighting value a is set to 3 for the browser target reading area a, a weighting value B is set to 5 for the browser target reading area B, a weighting value C is set to 2 for the browser target reading area C, and a weighting value D is set to 1 for the browser target reading area D, as known from the relevant explanation of step S101, it may be detected by the existing data monitoring technology that whether a target segment is in the preset browser target reading area every unit reading time (for example, 2 seconds), and simultaneously the corresponding weighting value corresponding to the browser target reading area is taken as the target weighting value, for example, if a target segment is located in the preset browser target reading area B, the weight value B of the browser target reading area B is obtained as 5, which is the corresponding target weight value, so as to represent that the target segment is located in the browser target reading area B within the 2 seconds.
It can be understood that, if the target reading area of the browser in which the target segment is located is not detected within a unit reading time (e.g. 2 seconds), it indicates that the target segment is outside all preset target reading areas of the browser at this time, and the target segment may be set to the off-screen state at this time.
Step S202: and determining the corresponding browsing behaviors according to the numerical comparison result of the sum of the weighted values obtained in each unit reading time in the set reading time period and the preset weight threshold value of each browsing behavior.
It is understood that, the set reading time period may be a time period from the time when the user opens a web page to the time when the user closes the web page, or may be another self-defined time period (e.g. 10 minutes), and as can be known from the above step S201, it may be detected whether the target segment is within the preset browser target reading area every unit reading time (e.g. 2 seconds) within one set reading time period, and simultaneously the corresponding weight value of the corresponding browser target reading area is taken, for example, if a target segment is within the preset browser target reading area B at this time, the weight value B of the browser target reading area B is taken to be 5, so as to represent that the target segment is within the browser target reading area B within the 2 seconds, since a plurality of weight values of a target segment can be obtained within the set reading time period (e.g. 2 seconds takes one weight value, 1 minute can obtain at most 30 weighted values), therefore, after the set reading time period is over, all weighted values obtained in each unit reading time in the period can be summed, and according to the numerical comparison result of the weighted value sum and the preset weighted threshold value of each browsing behavior, the corresponding browsing behavior is determined, for example, the weighted value sum of a target segment is 80, the preset weighted threshold value of the preset perusal browsing behavior is greater than 60, it can be known that the browsing behavior of the target segment in the set reading time period is perusal, and other browsing behaviors can be obtained in the same manner.
In order to accurately obtain the weighted values when the target segment covers a plurality of preset browser target reading areas, in an embodiment of the user browsing behavior analysis method of the present application, referring to fig. 3, the following may be further included:
step S301: and respectively judging whether the coordinate position of the target segment in the browser is coincident with the coordinate position of the target reading area of each preset browser.
Step S302: if so, obtaining the sum of the weight values according to the weight values respectively corresponding to the preset browser target reading areas superposed with the coordinate positions of the target segments, and setting the sum of the weight values as the target weight value.
It can be understood that, when the preset browser target reading area where the target segment is located is determined, since the coordinate position of the target segment may coincide with the coordinate positions of the preset browser target reading areas in one determination process, for example, the coordinate position of one target segment is coordinate axis x being 0, coordinate axis y being 20, width being 320, and height being 100, it can be known that the target segment is simultaneously located in the preset browser target reading area a and the preset browser target reading area B, at this time, in order to improve the accuracy of weight value calculation and simultaneously embody the characteristic of large size of the target segment, the weight values of all related preset browser target reading areas may be added to obtain the target weight value of this time, in other embodiments of the present application, the target weight value may also be obtained by combining the actual overlapping area of the target segment and the browser target reading area, for example, the target weight value of a single target segment may be calculated by: the overlapping area of the current target fragment and each browser target reading area is multiplied by the weight value corresponding to each browser target reading area, and then the obtained product is divided by the weight unit area to obtain the target weight value, wherein the weight unit area is the area corresponding to the preset weight value of 1, for example, the width 320 is multiplied by the height 100, so that the target weight value calculated by the method not only covers the situation of overlapping with a plurality of browser target reading areas, but also can be calculated according to the actual overlapping area during overlapping, and the target weight value can reflect the reading time of the target fragment in each browser target reading area more accurately, intuitively and reliably.
In order to determine whether the target segment is rereaded by the user according to the state of the target segment when the target segment is not in the preset browser target reading area (i.e. off-screen state), in an embodiment of the user browsing behavior analysis method of the present application, referring to fig. 4, the following may be further included:
step S401: and judging whether the screen-off time length of the target fragment in the one-time screen-off state is greater than a preset screen-off time length threshold value.
Step S402: if so, judging whether the perusal browsing behaviors exist before the off-screen state and after the off-screen state according to the comparison result of the sum of the weighted values obtained in each unit reading time before the off-screen state and after the off-screen state and the preset perusal threshold value of the perusal browsing behaviors, and if so, judging that the browsing behaviors of the user on the target segment are rereading behaviors.
It can be understood that, as shown in the step S201, if the target reading area of the browser where the target segment is located is not detected within a unit reading time (e.g. 2 seconds), it indicates that the target segment is located outside all preset target reading areas of the browser, at this time, the target segment may be set to the off-screen state, and if the weighted values can be obtained within the set reading time period before the target segment is in the off-screen state and after the target segment is in the off-screen state, and the sum of the weighted values obtained within each unit reading time before the off-screen state is greater than the preset perusal threshold of the perusal behavior (i.e. the target segment is the perusal behavior before the off-screen state) and/or the sum of the weighted values obtained within each unit reading time after the off-screen state is greater than the preset perusal threshold of the perusal behavior (i.e. the target segment is the perusal behavior after the off-screen, the target segment can be judged to be read again by the user after being off the screen, and the target segment is a repeated reading browsing behavior.
Optionally, the preset off-screen duration threshold may be preset according to an actual requirement, for example, 2 seconds, which may indicate that the target segment actually leaves the valid duration from the user visual range.
In order to determine whether the target segment is skipped by the user according to different durations of the reading time of the preset target segment in the preset browser target reading area, in an embodiment of the user browsing behavior analysis method according to the present application, referring to fig. 5, the following may be further included:
step S501: and determining the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors according to the reading time of each preset target segment in the target reading area of the same browser in the set reading time period and the numerical comparison result of the reading time and the preset time threshold of each browsing behavior.
Step S502: and setting the browsing behavior of the target segment between the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors as the skip browsing behavior.
It can be understood that, the determination of whether the target segment is the skip browsing behavior may not only be determined according to the result of comparing the sum of the weighted values obtained in each unit reading time in the set reading time period in the step S202 with the preset weighted threshold of each browsing behavior, but also may be implemented as follows: firstly, acquiring all target segments passing through a target reading area of the same browser in a set reading time period and reading time thereof, sequencing the target segments according to the passing sequence, judging whether the target segments are in a fine reading browsing behavior according to the reading time of each target segment, if so, setting the browsing behavior of the target segment between two adjacent target segments which are in the fine reading browsing behavior as skip reading.
In order to preset different target reading areas of the browser and set different weight values for the target reading areas of the browser in a specific area according to the specific type of the browser and the common reading habit of the user during browsing, in an embodiment of the user browsing behavior analysis method of the present application, referring to fig. 12 and 13, the following contents may be further included: presetting at least one browser target reading area in a display area of the browser, and respectively setting corresponding weight values according to the coordinate position in the display area of the browser of each browser target reading area.
Optionally, because the specific types of the browsers are different, the page displayed in the browser may simply slide up and down (see fig. 12), or may move in any direction under the control of a keyboard and a mouse (see fig. 13), so that the specific number and the specific coordinate position of the target reading area of the browser may be flexibly set according to the actual situation, so as to meet the actual business requirement and the general reading habit of the user, and set the corresponding weight value, for example, a higher weight value may be set for the preset browser target reading area that conforms to the general reading habit of the user and is close to the user watching area, and a lower weight value may be set for the preset browser target reading area that is far away from the user watching area.
In order to determine the reading preference of the user for the target segment according to the different browsing behaviors of the user for the target segment, in an embodiment of the user browsing behavior analysis method of the present application, referring to fig. 6, the following may be further included:
step S601: and determining the reading preference weight value of the target segment according to the chapter position of the target segment in the target content.
Step S602: and determining the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value and the conversion relation between each browsing behavior and each reading preference.
Optionally, different reading preference weights may be set for each target segment in advance according to the chapter position of the target segment in the target content, for example, a lower weight 0.8 is set for the target segment describing the full-text catalogue content, a higher weight 1.2 is set for the target segment describing the full-text prolog content, and a calculation initial value overview is set for predefined browsing behaviors "overview, rough reading, fine reading, skip reading, and repeat reading", respectively: 0.6, 0.8 for rough reading, 1.0 for fine reading, 0.5 for skip reading and 1.2 for repeat reading, when the browsing behavior corresponding to the target segment describing the full-text catalogue content is overview, the final reading preference value is 0.6 times 0.8 and is equal to 0.48, when the browsing behavior corresponding to the target segment describing the full-text prolog content is fine reading, the final reading preference value is 1.0 times 1.2 and is equal to 1.2, meanwhile, the target segment with the final reading preference value lower than 1 can be set as the reading preference of 'uninteresting', the target segment with the final reading preference value not lower than 1 is set as the reading preference of 'interested', so that the reading preference of the user corresponding to the target segment describing the full-text catalogue content can be known as 'uninterested', and the reading preference of the user corresponding to the target segment describing the full-text prolog content is 'interested'.
In order to accurately analyze the browsing behavior of the user on different target segments in the target content and further determine the reading preference of the user on each target segment, the present application provides an embodiment of a user browsing behavior analysis apparatus for implementing all or part of the content of the user browsing behavior analysis method, and referring to fig. 7, the user browsing behavior analysis apparatus specifically includes the following contents:
the browsing behavior determining module 10 is configured to determine a browsing behavior of a user on a preset target segment according to reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content.
And a reading preference determining module 20, configured to determine, according to the browsing behavior, a reading preference of the user for the preset target segment.
As can be seen from the above description, the user browsing behavior analysis apparatus provided in the embodiment of the present application can determine the browsing behavior of the user for the target segment by presetting the browser target reading area in the browser display area and according to the retention time of the preset target segment in the target content in the browser target reading area (i.e. the reading time of the target segment being read) when the user browses the target content, and thus further determine the reading preference of the user for the target segment.
In order to determine different browsing behaviors according to different durations of reading time of a preset target segment in a preset browser target reading area, in an embodiment of the apparatus for analyzing browsing behavior of a user according to the present application, referring to fig. 8, the browsing behavior determining module 10 includes:
the target weight value determining unit 11 is configured to determine whether the target segment is located in at least one preset browser target reading area according to a coordinate position of the target segment in the browser within a unit reading time and a coordinate position of the preset browser target reading area, obtain a corresponding target weight value according to the browser target reading area where the target segment is located if the target segment is located, and determine that the target segment is in an off-screen state if the target segment is located.
And the weighted value comparing unit 12 is configured to determine a corresponding browsing behavior according to a numerical comparison result between a sum of weighted values obtained in each unit reading time in a set reading time period and a preset weighted threshold of each browsing behavior.
In order to accurately obtain the weighted values when the target segment covers a plurality of preset browser target reading areas, in an embodiment of the apparatus for analyzing user browsing behavior of the present application, referring to fig. 9, the target weighted value determining unit 11 includes:
and a coordinate position determining subunit 111, configured to determine whether the coordinate position of the target segment in the browser coincides with the coordinate position of each preset browser target reading area.
A multi-weight value summing subunit 112, configured to, when it is determined that the coordinate position of the target segment in the browser coincides with the coordinate position of the preset browser target reading area, obtain a sum of weight values according to the weight values respectively corresponding to the preset browser target reading areas that coincide with the coordinate position of the target segment, and set the sum of weight values as the target weight value.
In order to determine whether the target segment is rereaded by the user according to the state of the target segment when the target segment is not in the preset browser target reading area (i.e. off-screen state), in an embodiment of the user browsing behavior analysis apparatus of the present application, the following contents are further specifically included:
and the off-screen time judging unit 31 is configured to judge whether the off-screen time of the target segment in the one-off-screen state is greater than a preset off-screen time threshold.
And the rereading behavior judging unit 32 is configured to, when it is judged that the off-screen duration of the target segment in the one-off-screen state is greater than the preset off-screen duration threshold, judge whether the perusal behavior exists before the off-screen state and after the off-screen state according to a comparison result between a sum of weighted values obtained in each unit reading time before the off-screen state and after the off-screen state and a value of the preset perusal threshold of the perusal behavior, and if so, judge that the browsing behavior of the target segment by the user is rereading behavior.
In order to determine whether the target segment is skipped by the user according to different durations of the reading time of the preset target segment in the preset browser target reading area, in an embodiment of the user browsing behavior analysis apparatus of the present application, referring to fig. 10, the browsing behavior determination module 20 further includes:
and the reading time comparison unit 13 is configured to determine, according to the reading time of each preset target segment in the set reading time period in the same browser target reading area and a numerical comparison result between the reading time and a preset time threshold of each browsing behavior, that two adjacent browsing behaviors are the target segments of the perusal browsing behavior.
A skip-reading behavior determination unit 14, configured to set, as skip-reading browsing behavior, browsing behavior of a target segment between the target segments of which the two adjacent browsing behaviors are fine-reading browsing behaviors.
In order to preset different target reading areas of the browser and set different weighted values for the target reading areas of the browser in a specific area according to the specific type of the browser and the common reading habit of the user during browsing, an embodiment of the apparatus for analyzing the browsing behavior of the user according to the present application further includes the following contents: a reading area weight value determining unit 33, configured to preset at least one browser target reading area in a display area of the browser, and set corresponding weight values according to coordinate positions in the display area of the browser in each browser target reading area.
In order to determine the reading preference of the user for the target segment according to the browsing behavior of the user for the target segment, in an embodiment of the apparatus for analyzing the browsing behavior of the user according to the present application, referring to fig. 11, the reading preference determining module 20 includes:
a reading preference weight value determining unit 21, configured to determine a reading preference weight value of the target segment according to a chapter position of the target segment in the target content.
The reading preference determining unit 22 is configured to determine the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value, and the conversion relationship between each browsing behavior and each reading preference.
An embodiment of the present application further provides a specific implementation manner of an electronic device, which is capable of implementing all steps in the user browsing behavior analysis method in the foregoing embodiment, and with reference to fig. 14, the electronic device specifically includes the following contents:
a processor (processor)601, a memory (memory)602, a communication Interface (Communications Interface)603, and a bus 604;
the processor 601, the memory 602 and the communication interface 603 complete mutual communication through the bus 604; the communication interface 603 is used for realizing information transmission among a user browsing behavior analysis device, an online service system, client equipment and other participating mechanisms;
the processor 601 is configured to call a computer program in the memory 602, and when the processor executes the computer program, the processor implements all the steps in the user browsing behavior analysis method in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
step S101: and determining the browsing behavior of the user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content.
Step S102: and determining the reading preference of the user for the preset target segment according to the browsing behavior.
As can be seen from the above description, the electronic device provided in the embodiment of the present application can determine the browsing behavior of the user for the target segment by presetting the browser target reading area in the browser display area and according to the staying time of the preset target segment in the target content in the browser target reading area (i.e. the reading time of the target segment being read) when the user browses the target content, and further determine the reading preference of the user for the target segment.
An embodiment of the present application further provides a computer-readable storage medium capable of implementing all the steps in the user browsing behavior analysis method in the foregoing embodiment, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, implements all the steps in the user browsing behavior analysis method in the foregoing embodiment, for example, when the processor executes the computer program, the processor implements the following steps:
step S101: and determining the browsing behavior of the user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content.
Step S102: and determining the reading preference of the user for the preset target segment according to the browsing behavior.
As can be seen from the above description, the computer-readable storage medium provided in the embodiment of the present application can determine the browsing behavior of the user for the target segment by presetting the browser target reading area in the browser display area and according to the retention time of the preset target segment in the target content in the browser target reading area (i.e. the reading time of the target segment being read) when the user browses the target content, and thus further determine the reading preference of the user for the target segment.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Although the present application provides method steps as described in an embodiment or flowchart, additional or fewer steps may be included based on conventional or non-inventive efforts. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The described embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.
Claims (16)
1. A user browsing behavior analysis method is characterized by comprising the following steps:
determining browsing behaviors of a user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content;
and determining the reading preference of the user for the preset target segment according to the browsing behavior.
2. The method for analyzing browsing behavior of a user according to claim 1, wherein the determining browsing behavior of the user on the preset target segment according to the reading time of the preset target segment in the target content in the preset browser target reading area when the user browses the target content comprises:
judging whether the target fragment is located in at least one preset browser target reading area or not according to the coordinate position of the target fragment in the browser in unit reading time and the coordinate position of the preset browser target reading area, if so, obtaining a corresponding target weight value according to the browser target reading area in which the target fragment is located, and otherwise, judging that the target fragment is in an off-screen state;
and determining the corresponding browsing behaviors according to the numerical comparison result of the sum of the weighted values obtained in each unit reading time in the set reading time period and the preset weight threshold value of each browsing behavior.
3. The method of claim 2, wherein the step of determining whether the target segment is located in at least one preset browser target reading area according to the coordinate position of the target segment in the browser within a unit reading time and the coordinate position of the preset browser target reading area, and if so, obtaining a corresponding target weight value according to the browser target reading area where the target segment is located comprises:
respectively judging whether the coordinate position of the target segment in the browser is coincident with the coordinate position of each preset browser target reading area;
if so, obtaining the sum of the weight values according to the weight values respectively corresponding to the preset browser target reading areas superposed with the coordinate positions of the target segments, and setting the sum of the weight values as the target weight value.
4. The user browsing behavior analysis method according to claim 2, wherein after the determining that the target segment is in the off-screen state, the method comprises:
judging whether the off-screen time length of the target fragment in the one-off-screen state is greater than a preset off-screen time length threshold value or not;
if so, judging whether the perusal browsing behaviors exist before the off-screen state and after the off-screen state according to the comparison result of the sum of the weighted values obtained in each unit reading time before the off-screen state and after the off-screen state and the preset perusal threshold value of the perusal browsing behaviors, and if so, judging that the browsing behaviors of the user on the target segment are rereading behaviors.
5. The method for analyzing browsing behavior of a user according to claim 1, wherein the determining browsing behavior of the user on the preset target segment according to the reading time of the preset target segment in the target content in the preset browser target reading area when the user browses the target content further comprises:
determining the target segments of which two adjacent browsing behaviors are perusal browsing behaviors according to the reading time of each preset target segment in a set reading time period in the target reading area of the same browser and the numerical comparison result of the reading time and the preset time threshold of each browsing behavior;
and setting the browsing behavior of the target segment between the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors as the skip browsing behavior.
6. The method according to claim 3, wherein before obtaining a sum of the weight values according to the weight values respectively corresponding to the preset browser target reading areas coinciding with the coordinate positions of the target segments, the method comprises:
presetting at least one browser target reading area in a display area of the browser, and respectively setting corresponding weight values according to the coordinate position in the display area of the browser of each browser target reading area.
7. The method as claimed in claim 1, wherein the determining the reading preference of the user for the preset target segment according to the browsing behavior comprises:
determining a reading preference weight value of the target segment according to the chapter position of the target segment in the target content;
and determining the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value and the conversion relation between each browsing behavior and each reading preference.
8. An apparatus for analyzing a browsing behavior of a user, comprising:
the browsing behavior determining module is used for determining the browsing behavior of a user on a preset target segment according to the reading time of the preset target segment in the target content in a preset browser target reading area when the user browses the target content;
and the reading preference determining module is used for determining the reading preference of the user for the preset target segment according to the browsing behavior.
9. The apparatus of claim 8, wherein the browsing behavior determination module comprises:
the target weight value determining unit is used for judging whether the target fragment is positioned in at least one preset browser target reading area or not according to the coordinate position of the target fragment in the browser in unit reading time and the coordinate position of the preset browser target reading area, if so, obtaining a corresponding target weight value according to the browser target reading area in which the target fragment is positioned, and otherwise, judging that the target fragment is in an off-screen state;
and the weighted value comparison unit is used for determining the corresponding browsing behaviors according to the numerical comparison result of the sum of weighted values obtained in each unit reading time in the set reading time period and the preset weighted threshold value of each browsing behavior.
10. The apparatus according to claim 9, wherein the target weight value determining unit comprises:
the coordinate position judging subunit is used for respectively judging whether the coordinate position of the target segment in the browser coincides with the coordinate position of each preset browser target reading area;
and the multi-weight value summing subunit is used for obtaining a sum of weight values according to the weight values respectively corresponding to the preset browser target reading areas coinciding with the coordinate positions of the target segments when the coordinate positions of the target segments in the browser are judged to coincide with the coordinate positions of the preset browser target reading areas, and setting the sum of the weight values as the target weight value.
11. The apparatus for analyzing browsing behavior of a user according to claim 8, further comprising:
the off-screen time judging unit is used for judging whether the off-screen time length of the target fragment in the one-time off-screen state is greater than a preset off-screen time length threshold value or not;
and the rereading behavior judging unit is used for judging whether the perusal behavior exists before the off-screen state and after the off-screen state according to the comparison result of the sum of weighted values obtained by each unit reading time before the off-screen state and after the off-screen state and the preset perusal threshold value of the perusal behavior when the off-screen time of the target fragment in the one-time off-screen state is judged to be larger than the preset off-screen time threshold value, and judging that the browsing behavior of the target fragment by the user is the rereading behavior if the rereading behavior exists before the off-screen state and after the off-screen state.
12. The apparatus of claim 8, wherein the browsing behavior determination module further comprises:
the reading time comparison unit is used for determining the target segments of two adjacent browsing behaviors as the fine reading browsing behaviors according to the reading time of each preset target segment in the target reading area of the same browser in a set reading time period and the numerical comparison result of the reading time and the preset time threshold of each browsing behavior;
and the skip behavior determining unit is used for setting the browsing behavior of the target segment between the target segments of which the two adjacent browsing behaviors are the perusal browsing behaviors as the skip browsing behavior.
13. The apparatus for analyzing browsing behavior of a user according to claim 8, further comprising:
the reading area weight value determining unit is used for presetting at least one browser target reading area in a display area of the browser and respectively setting corresponding weight values according to the coordinate position in the display area of the browser of each browser target reading area.
14. The apparatus as claimed in claim 8, wherein the reading preference determining module comprises:
a reading preference weight value determining unit, configured to determine a reading preference weight value of the target segment according to a chapter position of the target segment in the target content;
and the reading preference determining unit is used for determining the reading preference of the user for the preset target segment according to the browsing behavior of the user for the target segment, the reading preference weight value and the conversion relation between each browsing behavior and each reading preference.
15. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the steps of the user browsing behavior analysis method according to any of claims 1 to 7 are implemented when the processor executes the program.
16. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the user browsing behavior analysis method of any one of claims 1 to 7.
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Effective date of registration: 20221008 Address after: 12 / F, 15 / F, 99 Yincheng Road, Pudong New Area pilot Free Trade Zone, Shanghai, 200120 Applicant after: Jianxin Financial Science and Technology Co.,Ltd. Address before: 25 Financial Street, Xicheng District, Beijing 100033 Applicant before: CHINA CONSTRUCTION BANK Corp. Applicant before: Jianxin Financial Science and Technology Co.,Ltd. |
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Application publication date: 20200103 |