CN112765346B - Information processing method and device - Google Patents
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- CN112765346B CN112765346B CN202011297816.7A CN202011297816A CN112765346B CN 112765346 B CN112765346 B CN 112765346B CN 202011297816 A CN202011297816 A CN 202011297816A CN 112765346 B CN112765346 B CN 112765346B
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Abstract
The application discloses an information processing method and device. By the method and the device, when the posts are sorted, the target heat value of the posts can be acquired by means of the target heat value of the posts, the sentiment classification of the target posts and the benchmark heat value of the target posts can be comprehensively referred, so that the influence of the number of the reply contents of the posts on the heat value of the posts can be weakened, the situation that the heat value of the posts with high number of the reply contents is higher and higher can be avoided, and the situation that the posts with controversial topics, excited speeches, speeches attacking others and negative energy contents are higher and higher can be avoided, so that the posts with positive direction and civilization harmony can be preferentially displayed on the forum, the civilization and harmony atmosphere of the forum can be improved, the positive energy of the forum can be enhanced, and the harmonious development of the forum can be facilitated. Secondly, the user can be prevented from seeing more negative energy content, and further the user experience can be prevented from being reduced.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to an information processing method and apparatus.
Background
Currently, forums gradually become platforms for convenient communication between people, and each user can publish or reply posts on forums, so as to realize online discussion of the same topic by multiple users.
The forum is provided with a plurality of posts, a plurality of posts can be displayed on the forum for a user to select, and the posts can be displayed in a sorted mode when the plurality of posts are displayed on the forum.
In the forum, the degree of hotness of the post is generally used to reflect the degree of the post being focused by the user, and the higher the degree of hotness of the post is, the more focused the post is, so in order to attract more users, the hotness of each post can be obtained. And then, the posts are displayed in an ordered way according to the heat degree of the posts from high to low. The higher the popularity of the post, the closer (further forward) the post is shown on the forum.
The earlier the position of the post in the forum is, the higher the probability that the post is clicked by the user is, the higher the probability that the user replies to the post is, and the like. However, according to the above method for obtaining the popularity of posts, the effect that the popularity of posts with high popularity is higher and higher is easily caused, which is likely to be unfavorable for the harmonious development of forums.
For example, if a poster specifically selects some topics of controversy in a post, the deliberate use of an excited story causes attacks by other net friends; or the reply content of a certain post contains a plurality of contents specially giving off negative energy, disputes can be caused, the number of the reply contents of the post is increased, and then the heat value of the post is improved, but the 'hot post' can reduce the civilized and harmonious atmosphere of the forum and is not beneficial to the harmonious development of the forum. The user experience is also reduced as the user sees more negative energy content.
Disclosure of Invention
In order to purify the network environment of forums, enable the forums to develop harmoniously and improve user experience, the application shows an information processing method and device.
In a first aspect, the present application shows an information processing method, comprising:
acquiring a reference heat value of a target post;
acquiring post content of a target post and reply content of the target post;
determining an emotion classification of the target post according to the post content and the reply content;
adjusting the reference heat value according to the emotion classification to obtain a target heat value of the target post;
determining a display order of the target posts in a plurality of posts according to the target heat value;
displaying the target posts based on the display order.
In an alternative implementation, the post content of the target post comprises a post title and a post body of the target post;
said determining an emotion classification of said targeted post as a function of said post content and said reply content comprising:
acquiring a first emotion classification of the post title, a second emotion classification of the post text and a third emotion classification of the reply content;
obtaining an emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification.
In an alternative implementation, the obtaining the sentiment classification of the target post according to the first sentiment classification, the second sentiment classification and the third sentiment classification includes:
obtaining the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification according to the following formula:
in the formula, δ score is the emotion classification of the target post, ε t is a first preset coefficient, ε c is a second preset coefficient, ε r is a third preset coefficient, st is the first emotion classification, sc is the second emotion classification, and sr i A third sentiment classification for the ith reply content of the target post; n is the number of reply contents of the target post.
In an alternative implementation manner, the obtaining the benchmark heat value of the target post includes:
acquiring at least first grade information of a poster who posts the target post, the total number of times the target post is browsed, a first quantity of reply contents of the target post, second grade information of a replier of each reply content of the target post and a second quantity of forward comments obtained by the target post;
obtaining a benchmark heat value of the target posts according to at least the first level information, the total number of times, the first number, the second level information, and the second number.
In an alternative implementation, the obtaining a base heat value of the target post based on at least the first level information, the total number of times, the first number, the second level information, and the second number includes:
obtaining a benchmark heat value of the target post according to at least the first level information, the total times, the first quantity, the second level information and the second quantity according to the following formula:
in the formula, score is the reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient;
pl is the first level information, pv is the total number of times, pr is the first number, pa is the second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
In a second aspect, the present application shows an information processing apparatus comprising:
the first acquisition module is used for acquiring a reference heat value of the target post;
the second acquisition module is used for acquiring the post content of the target post and the reply content of the target post;
a first determination module for determining an emotion classification of the target post based on the post content and the reply content;
the adjusting module is used for adjusting the reference heat value according to the emotion classification to obtain a target heat value of the target post;
a second determination module, configured to determine a display order of the targeted posts among the plurality of posts according to the targeted heat value;
a display module to display the target posts based on the display order.
In an alternative implementation, the post content of the target post comprises a post title and a post body of the target post;
the first determining module includes:
the first acquiring unit is used for acquiring a first emotion classification of the post title, acquiring a second emotion classification of the post text and acquiring a third emotion classification of the reply content;
a second obtaining unit, configured to obtain an emotion classification of the target post according to the first emotion classification, the second emotion classification, and the third emotion classification.
In an optional implementation manner, the second obtaining unit is specifically configured to: obtaining the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification according to the following formula:
in the formula, δ score is the emotion classification of the target post, ε t is a first preset coefficient, ε c is a second preset coefficient, ε r is a third preset coefficient, st is the first emotion classification, sc is the second emotion classification, and sr i A third sentiment classification for an ith reply content of the target post; n is the number of reply contents of the target post.
In an optional implementation manner, the first obtaining module includes:
a third obtaining unit, configured to obtain at least first level information of a poster who published the target post, a total number of times the target post is browsed, a first number of reply contents of the target post, second level information of a reply person of each reply content of the target post, and a second number of positive comments obtained by the target post;
a fourth obtaining unit, configured to obtain a benchmark heat value of the target posts according to at least the first level information, the total number of times, the first number, the second level information, and the second number.
In an optional implementation manner, the fourth obtaining unit is specifically configured to: obtaining a benchmark heat value of the target post according to at least the first level information, the total times, the first quantity, the second level information and the second quantity according to the following formula:
in the formula, score is the reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient;
pl is the first level information, pv is the total number of times, pr is the first number, pa is the second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
In a third aspect, the present application shows an electronic device comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the information processing method according to the first aspect.
In a fourth aspect, the present application shows a non-transitory computer-readable storage medium having instructions which, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method according to the first aspect.
In a fifth aspect, the present application shows a computer program product, in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method according to the first aspect.
The technical scheme provided by the application can comprise the following beneficial effects:
in the application, a reference heat value of a target post is obtained; acquiring the post content of the target post and the reply content of the target post; obtaining the emotion classification of the target post according to the post content of the target post and the reply content of the target post; acquiring a target heat value of the target post according to the emotion classification of the target post and the reference heat value of the target post; acquiring the display sequence of the target posts in the posts according to the target heat value; and displaying the target posts based on the display sequence.
By the method and the device, when the posts are sorted, the target heat value of the posts can be acquired by means of the target heat value of the posts, the sentiment classification of the target posts and the benchmark heat value of the target posts can be comprehensively referred, so that the influence of the number of the reply contents of the posts on the heat value of the posts can be weakened, the situation that the heat value of the posts with high number of the reply contents is higher and higher can be avoided, and the situation that the posts with controversial topics, excited speeches, speeches attacking others and negative energy contents are higher and higher can be avoided, so that the posts with positive direction and civilization harmony can be preferentially displayed on the forum, the civilization and harmony atmosphere of the forum can be improved, the positive energy of the forum can be enhanced, and the harmonious development of the forum can be facilitated. Secondly, the user can be prevented from seeing more negative energy content, and further the user experience can be prevented from being reduced.
Drawings
FIG. 1 is a flow chart of the steps of an information processing method of the present application;
fig. 2 is a block diagram of a structure of an information processing apparatus of the present application;
FIG. 3 is a block diagram of an electronic device shown in the present application;
fig. 4 is a block diagram of an electronic device shown in the present application.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, the present application is described in further detail with reference to the accompanying drawings and the detailed description.
Referring to fig. 1, a flowchart illustrating steps of an information processing method according to the present application is shown, where the method is applied to an electronic device, and the method may specifically include the following steps:
in step S101, a base heat value of the target post is acquired.
In one embodiment of the present application, in this step, the number of reply contents of the target post may be obtained and used as the reference heat value of the target post. The more the number of the reply contents of the target post is, the more people participate in the interaction in the target post, the higher the benchmark heat value of the target post is, and the less the number of the reply contents of the target post is, the less people participate in the interaction in the target post, and the lower the benchmark heat value of the target post is.
In another embodiment of the present application, the step may be implemented by the following process, including:
1011. at least acquiring first grade information of a poster who issues the target post, the total browsing times of the target post, a first quantity of reply contents of the target post, second grade information of a replier of each reply content of the target post and a second quantity of positive comments obtained by the target post.
Of course, other information about the target post may also be obtained according to actual requirements, which may be specific according to actual requirements and is not limited herein.
1012. And acquiring a reference heat value of the target posts at least according to the first level information, the total times, the first quantity, the second level information and the second quantity.
In one example, the base heat value of the target post may be obtained according to at least the first level information, the total number of times, the first number, the second level information, and the second number according to the following formula:
wherein, in the formula, the first and the second groups,score is a reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient; pl is first level information, pv is total number of times, pr is first number, pa is second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
The sum of the fourth preset coefficient epsilon 1, the fifth preset coefficient epsilon 2, the sixth preset coefficient epsilon 3 and the seventh preset coefficient epsilon 4 may be equal to a specific numerical value, and the specific numerical value includes 1, 1.5 or 2, and the like, which is not limited in the present application.
The fourth predetermined coefficient e 1 may be greater than or equal to 0 and less than or equal to a specific value, the fifth predetermined coefficient e 2 may be greater than or equal to 0 and less than or equal to a specific value, the sixth predetermined coefficient e 3 may be greater than or equal to 0 and less than or equal to a specific value, etc., and the seventh predetermined coefficient e 4 may be greater than or equal to 0 and less than or equal to a specific value, etc.
In step S102, the post content of the target post and the reply content of the target post are acquired.
In step S103, an emotion classification of the target post is determined according to the post content of the target post and the reply content of the target post.
In the present application, the post content may include a post title of the target post and a post body.
The target post may have text, expression and the like in the post title, and the text and the expression may embody the emotional classification of the post title.
The post body of the target post can have text, expression, video, audio or image content, and the text, expression, video, audio or image content can embody the emotion classification of the post body.
The post may have at least one reply content, the reply content is reply content for replying to the target post in the target post after other users except the poster enter the target post and see the post content of the target post, and the user replying to the target post is a replying person of the target post.
The reply content of the target post may have content such as text, expression, video, audio or image, and the content such as text, expression, video, audio or image may embody the emotional classification of the reply content.
The sentiment classification of the post title, the sentiment classification of the post text and the sentiment classification of the reply content are combined to embody the sentiment classification of the target post.
The emotion classification in the present application may include three classifications, positive, normal, and negative. Alternatively, more emotion classifications may be divided according to actual needs, for example, 5 emotion classifications are divided according to "1 to 5", or 10 emotion classifications are divided according to "1 to 10", and the like, and the larger the numerical value is, the more positive the emotion classification is, and the smaller the numerical value is, the more negative the emotion classification is, and the like.
In one embodiment, the post content of the target post includes a post title and a post body of the target post, and the step may be implemented by a process including:
1031, obtaining a first sentiment classification of the post title, obtaining a second sentiment classification of the post text, and obtaining a third sentiment classification of the reply content.
In one embodiment of the application, an emotion classification retrieval model may be used to retrieve a first emotion classification for a post title, a second emotion classification for a post body, and a third emotion classification for reply content.
In one approach, the emotion classification retrieval model may use a model that already exists in the market, such as CoreML or Resnet 50.
In another approach, the emotion classification acquisition model may be trained in advance.
Specifically, a plurality of different emotion classifications can be divided, where the different emotion classifications represent different emotion polarities, for example, the emotion classification includes 3, such as positive, normal, and negative, etc.
And then acquiring a plurality of sample data, marking each sample data by the sample data which comprises data such as pictures, texts, audios, videos and the like to obtain a marked emotion classification of each sample data, and training the model by using the plurality of sample data and the marked emotion classifications of each sample data until network parameters in the model are converged to obtain an emotion classification acquisition model.
The model includes CNN (Convolutional Neural Networks), RNN (Recurrent Neural Networks), LSTM (Long Short-Term Memory), and the like.
In this way, a first sentiment classification of the post title of the target post, a second sentiment classification of the post body of the target post, and a third sentiment classification of the reply content of the target post may be obtained based on the sentiment classification retrieval model.
For example, the post title of the target post may be input into the sentiment classification retrieval model, which may process the post title of the target post and output a first sentiment classification of the post title of the target post. A first sentiment classification of the post title of the target post output by the sentiment classification retrieval model may then be retrieved.
And inputting the post text of the target post into the emotion classification acquisition model, wherein the emotion classification acquisition model can process the post text of the target post and output a second emotion classification of the post text of the target post. A second sentiment classification of the post text of the target post output by the sentiment classification retrieval model may then be retrieved.
And for any reply content of the target post, inputting the reply content of the target post into an emotion classification acquisition model, processing the reply content of the target post by the emotion classification acquisition model, and outputting a third emotion classification of the reply content of the target post. A third sentiment classification of the reply content to the target post output by the sentiment classification retrieval model may then be retrieved. The same is performed for each of the other reply contents of the target post, thus obtaining a third sentiment classification of each of the reply contents of the target post.
1032. And acquiring the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification.
In one embodiment of the present application, the first sentiment classification, the second sentiment classification and the third sentiment classification may be weighted and summed to obtain the sentiment classification of the target post.
For example, the emotion classification of the target post may be obtained according to the following formula according to the first emotion classification, the second emotion classification and the third emotion classification:
in the formula, δ score is the emotion classification of the target post, ε t is a first preset coefficient, ε c is a second preset coefficient, ε r is a third preset coefficient, st is the first emotion classification, sc is the second emotion classification, and sr is i A third sentiment classification for the ith reply content of the target post; n is the number of reply contents of the target post.
In an example, the sum of the first preset coefficient ∈ t, the second preset coefficient ∈ c, and the third preset coefficient ∈ r may be equal to a specific value, where the specific value includes 1, 1.5, or 2, and the like, which is not limited in this application.
The first predetermined coefficient epsilont may be greater than or equal to 0 and less than or equal to a specific value, the second predetermined coefficient epsilonc may be greater than or equal to 0 and less than or equal to a specific value, the third predetermined coefficient epsilonr may be greater than or equal to 0 and less than or equal to a specific value, and so on.
In step S104, the reference heat value is adjusted according to the emotion classification to obtain the target heat value of the target post.
Different emotion classifications have respective corresponding emotion scores, the more the emotion classification of the target post is biased to positive direction, the higher the corresponding emotion score is, the more the emotion classification of the target post is biased to negative direction, the lower the corresponding emotion score is, and thus, the sum value between the emotion score corresponding to the emotion classification of the target post and the reference heat value of the target post can be calculated to obtain the target heat value of the target post.
In step S105, the display order of the target posts in the plurality of posts is determined according to the target heat value.
In an embodiment of the present application, the electronic device may obtain the target heat value of each of the plurality of posts (including the target post) according to the flow of steps S101 to S104. The posts are then sorted in order of the target popularity value of each post from high to low, so that the display order of each post in the respective posts (where the display order of the target posts in the posts can be obtained) can be obtained.
In step S106, the target posts are presented based on the presentation order.
In one embodiment of the present application, the electronic device may present the targeted posts on the screen based on the presentation order.
For example, the electronic device may display a post list on a screen according to business requirements, where the post list includes a plurality of posts (including target posts), and the electronic device may respectively obtain a display order of each post in the post list according to the flow of steps S101 to S105, and then display each post in the post list (including target posts) in an order.
In another embodiment of the application, the electronic device sends the target post and the display sequence of the target posts in the posts to other devices, so that the other devices display the target posts based on the display sequence.
In the application, a reference heat value of a target post is obtained; acquiring the post content of the target post and the reply content of the target post; obtaining the emotion classification of the target post according to the post content of the target post and the reply content of the target post; acquiring a target heat value of the target post according to the emotion classification of the target post and the reference heat value of the target post; acquiring the display sequence of the target posts in the posts according to the target heat value; and displaying the target posts based on the display sequence.
By the method and the device, when the posts are sorted, the target heat value of the posts can be acquired by means of the target heat value of the posts, the sentiment classification of the target posts and the benchmark heat value of the target posts can be comprehensively referred, so that the influence of the number of the reply contents of the posts on the heat value of the posts can be weakened, the situation that the heat value of the posts with high number of the reply contents is higher and higher can be avoided, and the situation that the posts with controversial topics, excited speeches, speeches attacking others and negative energy contents are higher and higher can be avoided, so that the posts with positive direction and civilization harmony can be preferentially displayed on the forum, the civilization and harmony atmosphere of the forum can be improved, the positive energy of the forum can be enhanced, and the harmonious development of the forum can be facilitated. Secondly, the user can be prevented from seeing more negative energy content, and further the user experience can be prevented from being reduced.
It is noted that, for simplicity of explanation, the method embodiments are described as a series of acts or combination of acts, but those skilled in the art will appreciate that the present application is not limited by the order of acts, as some steps may, in accordance with the present application, occur in other orders and concurrently. Further, those skilled in the art will also appreciate that the embodiments described in the specification are exemplary and that no action is necessarily required in this application.
Referring to fig. 2, a block diagram of an information processing apparatus according to the present application is shown, and the apparatus may specifically include the following modules:
a first obtaining module 11, configured to obtain a reference heat value of a target post;
the second obtaining module 12 is configured to obtain post content of a target post and reply content of the target post;
a first determining module 13, configured to determine an emotion classification of the target post according to the post content and the reply content;
an adjusting module 14, configured to adjust the reference heat value according to the emotion classification, to obtain a target heat value of the target post;
a second determining module 15, configured to determine, according to the target heat value, a display order of the target posts in a plurality of posts;
a presentation module 16, configured to present the target posts based on the presentation order.
In an alternative implementation, the post content of the target post comprises a post title and a post body of the target post;
the first determining module includes:
the first acquiring unit is used for acquiring a first emotion classification of the post title, acquiring a second emotion classification of the post text and acquiring a third emotion classification of the reply content;
a second obtaining unit, configured to obtain an emotion classification of the target post according to the first emotion classification, the second emotion classification, and the third emotion classification.
In an optional implementation manner, the second obtaining unit is specifically configured to: obtaining the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification according to the following formula:
wherein, in the above formula, δ score is the sentiment classification of the target post, ε t is a first preset coefficient, ε c is a second preset coefficient, ε r is a third preset coefficient, st is the first sentiment classification, sc is the second sentiment classification, and sr i A third sentiment classification for the ith reply content of the target post; n is the number of reply contents of the target post.
In an optional implementation manner, the first obtaining module includes:
a third obtaining unit, configured to obtain at least first level information of a poster who published the target post, a total number of times the target post is browsed, a first number of reply contents of the target post, second level information of a reply person of each reply content of the target post, and a second number of positive comments obtained by the target post;
a fourth obtaining unit, configured to obtain a benchmark heat value of the target post according to at least the first level information, the total number of times, the first number, the second level information, and the second number.
In an optional implementation manner, the fourth obtaining unit is specifically configured to: obtaining a benchmark heat value of the target post according to at least the first level information, the total times, the first quantity, the second level information and the second quantity according to the following formula:
in the formula, score is the reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient;
pl is the first level information, pv is the total number of times, pr is the first number, pa is the second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
In the application, a reference heat value of a target post is obtained; acquiring the post content of the target post and the reply content of the target post; obtaining the emotion classification of the target post according to the post content of the target post and the reply content of the target post; acquiring a target heat value of the target post according to the emotion classification of the target post and the reference heat value of the target post; acquiring the display sequence of the target posts in the posts according to the target heat value; and displaying the target posts based on the display sequence.
By the method and the device, when the posts are sorted, the target heat value of the posts can be acquired by means of the target heat value of the posts, the sentiment classification of the target posts and the benchmark heat value of the target posts can be comprehensively referred, so that the influence of the number of the reply contents of the posts on the heat value of the posts can be weakened, the situation that the heat value of the posts with high number of the reply contents is higher and higher can be avoided, and the situation that the posts with controversial topics, excited speeches, speeches attacking others and negative energy contents are higher and higher can be avoided, so that the posts with positive direction and civilization harmony can be preferentially displayed on the forum, the civilization and harmony atmosphere of the forum can be improved, the positive energy of the forum can be enhanced, and the harmonious development of the forum can be facilitated. Secondly, the user can be prevented from seeing more negative energy content, and further the user experience can be prevented from being reduced.
For the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and reference may be made to the partial description of the method embodiment for relevant points.
Fig. 3 is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 3, electronic device 800 may include one or more of the following components: a processing component 802, a memory 804, a power component 806, a multimedia component 808, an audio component 810, an input/output (I/O) interface 812, a sensor component 814, and a communication component 816.
The processing component 802 generally controls overall operation of the electronic device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing components 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phonebook data, messages, images, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
The power supply component 806 provides power to the various components of the electronic device 800. The power components 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.
The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the electronic device 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open/closed state of the device 800, the relative positioning of components, such as a display and keypad of the electronic device 800, the sensor assembly 814 can also detect a change in position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, orientation or acceleration/deceleration of the electronic device 800, and a change in temperature of the electronic device 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 may access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G, or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives broadcast signals or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the electronic device 800 may be implemented by 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), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the electronic device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
Fig. 4 is a block diagram of an electronic device 1900 shown in the present application. For example, the electronic device 1900 may be provided as a server.
Referring to fig. 4, electronic device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The electronic device 1900 may also include a power component 1926 configured to perform power management of the electronic device 1900, a wired or wireless network interface 1950 configured to connect the electronic device 1900 to a network, and an input/output (I/O) interface 1958. The electronic device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, mac OS XTM, unixTM, linuxTM, freeBSDTM, or the like.
The embodiments in the present specification are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal 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 terminal to cause a series of operational steps to be performed on the computer or other programmable terminal to produce a computer implemented process such that the instructions which execute on the computer or other programmable terminal provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications of these embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or terminal apparatus that comprises the element.
The information processing method and apparatus provided by the present application are introduced in detail, and a specific example is applied in the present application to explain the principle and the implementation of the present application, and the description of the above embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. An information processing method, characterized in that the method comprises:
acquiring a reference heat value of a target post;
acquiring post content of a target post and reply content of the target post;
determining an emotion classification of the target post according to the post content and the reply content, wherein the emotion classification of the target post is determined according to the emotion classification of the post content and the emotion classification of each reply content;
adjusting the reference heat value according to the emotion classification to obtain a target heat value of the target post;
wherein the adjusting the reference heat value according to the emotion classification to obtain the target heat value of the target post comprises:
obtaining the emotion score of a target post based on the emotion classification, wherein the more positive the emotion classification is, the higher the corresponding emotion score is, the more negative the emotion classification is, and the lower the corresponding emotion score is;
taking the sum value between the sentiment score and the reference heat value of the target post as the target heat value of the target post;
determining a display order of the targeted posts in a plurality of posts according to the targeted heat value;
displaying the target posts based on the display order;
the base heat value of the retrieval target post comprises:
acquiring at least first grade information of a poster who posts the target post, the total number of times the target post is browsed, a first quantity of reply contents of the target post, second grade information of a replier of each reply content of the target post and a second quantity of forward comments obtained by the target post;
obtaining a benchmark heat value of the target posts according to at least the first level information, the total number of times, the first number, the second level information, and the second number.
2. The method of claim 1, wherein the post content of the target post comprises a post title and a post body of the target post;
the determining an emotion classification of the targeted post from the post content and the reply content comprises:
acquiring a first emotion classification of the post title, a second emotion classification of the post text and a third emotion classification of the reply content;
obtaining an emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification.
3. The method of claim 2, wherein obtaining the sentiment classification of the targeted post according to the first sentiment classification, the second sentiment classification, and the third sentiment classification comprises:
obtaining the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification according to the following formula:
wherein, in the above formula, δ score is the sentiment classification of the target post, ε t is a first preset coefficient, ε c is a second preset coefficient, ε r is a third preset coefficient, st is the first sentiment classification, sc is the second sentiment classification, and sr i A third sentiment classification for an ith reply content of the target post; n is the number of reply contents of the target post.
4. The method of claim 1, wherein said obtaining a benchmark heat value for the target post based on at least the first rating information, the total number of times, the first number, the second rating information, and the second number comprises:
obtaining a benchmark heat value of the target post according to at least the first level information, the total times, the first quantity, the second level information and the second quantity according to the following formula:
in the formula, score is the reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient;
pl is the first level information, pv is the total number of times, pr is the first number, pa is the second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
5. An information processing apparatus characterized in that the apparatus comprises:
the first acquisition module is used for acquiring a reference heat value of the target post;
the second acquisition module is used for acquiring the post content of the target post and the reply content of the target post;
a first determining module, configured to determine an emotion classification of the target post according to the post content and the reply content, wherein the emotion classification of the target post is determined according to the emotion classification of the post content and the emotion classification of each reply content;
the adjusting module is used for adjusting the reference heat value according to the emotion classification to obtain a target heat value of the target post;
wherein the adjusting the reference heat value according to the emotion classification to obtain the target heat value of the target post comprises:
obtaining the emotion score of a target post based on the emotion classification, wherein the more positive the emotion classification is, the higher the corresponding emotion score is, the more negative the emotion classification is, and the lower the corresponding emotion score is;
taking the sum value between the sentiment score and the reference heat value of the target post as the target heat value of the target post;
a second determination module, configured to determine a display order of the targeted posts among the plurality of posts according to the targeted heat value;
a presentation module for presenting the target posts based on the presentation order;
the first obtaining module comprises:
a third obtaining unit, configured to obtain at least first level information of a poster who published the target post, a total number of times the target post is browsed, a first number of reply contents of the target post, second level information of a reply person of each reply content of the target post, and a second number of positive comments obtained by the target post;
a fourth obtaining unit, configured to obtain a benchmark heat value of the target posts according to at least the first level information, the total number of times, the first number, the second level information, and the second number.
6. The apparatus of claim 5, wherein the post content of the target post comprises a post title and a post body of the target post;
the first determining module includes:
the first acquiring unit is used for acquiring a first emotion classification of the post title, acquiring a second emotion classification of the post text and acquiring a third emotion classification of the reply content;
a second obtaining unit, configured to obtain an emotion classification of the target post according to the first emotion classification, the second emotion classification, and the third emotion classification.
7. The apparatus according to claim 6, wherein the second obtaining unit is specifically configured to: obtaining the emotion classification of the target post according to the first emotion classification, the second emotion classification and the third emotion classification according to the following formula:
wherein in the above formula, δ score is the sentiment classification of the target post, and ε t is the firstA predetermined coefficient, ε c a second predetermined coefficient, ε r a third predetermined coefficient, st the first emotion classification, sc the second emotion classification, and sr i A third sentiment classification for an ith reply content of the target post; n is the number of reply contents of the target post.
8. The apparatus according to claim 5, wherein the fourth obtaining unit is specifically configured to: obtaining a benchmark heat value of the target post according to at least the first level information, the total times, the first quantity, the second level information and the second quantity according to the following formula:
in the formula, score is the reference heat value, epsilon 1 is a fourth preset coefficient, epsilon 2 is a fifth preset coefficient, epsilon 3 is a sixth preset coefficient, and epsilon 4 is a seventh preset coefficient;
pl is the first level information, pv is the total number of times, pr is the first number, pa is the second number, and rl i Second level information of a replenisher for the ith reply content of the target post.
9. An electronic device, characterized in that the electronic device comprises:
a processor;
a memory for storing processor-executable instructions;
wherein the processor is configured to perform the information processing method of any one of claims 1 to 4.
10. A non-transitory computer-readable storage medium in which instructions, when executed by a processor of an electronic device, enable the electronic device to perform the information processing method of any one of claims 1 to 4.
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| CN104077354A (en) * | 2014-05-29 | 2014-10-01 | 小米科技有限责任公司 | Forum post heat determining method and related device thereof |
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