CN116186205A

CN116186205A - Content recommendation method and device, electronic equipment and storage medium

Info

Publication number: CN116186205A
Application number: CN202111422179.6A
Authority: CN
Inventors: 王旭; 郑伟; 朱静茹
Original assignee: Beijing Qury Technology Co ltd; Shandong Kurui Technology Co ltd
Current assignee: Beijing Qury Technology Co ltd; Shandong Kurui Technology Co ltd
Priority date: 2021-11-26
Filing date: 2021-11-26
Publication date: 2023-05-30

Abstract

The embodiment of the disclosure provides a content recommendation method, a device, equipment and a storage medium, wherein the content recommendation method comprises the following steps: acquiring interaction content of at least one round of interaction with a user; predicting a user intent based on the interactive content; and determining corresponding recommended content according to the predicted user intention, and outputting the recommended content. By adopting the scheme provided by the embodiment of the disclosure, the electronic equipment can judge the user intention based on the interactive content of at least one round, so as to identify the invisible requirement of the user through the user intention, and recommend the corresponding content to the user based on the implicit requirement of the user, thereby improving the diversity and accuracy of content recommendation and improving the user experience.

Description

Content recommendation method and device, electronic equipment and storage medium

Technical Field

The disclosure relates to the technical field of searching, and in particular relates to a content recommendation method, device, equipment and storage medium.

Background

With the development of intelligent technology, users are increasingly accustomed to acquiring information by means of intelligent interaction with intelligent devices. Taking interaction between the voice assistant and the intelligent device as an example, when a user needs to acquire specific information, the voice problem is input in a voice mode, and then the intelligent device processes the voice problem input by the user to obtain corresponding answers or recommended contents. In the prior art, the intelligent device only answers the questions presented by the user in a one-to-one interaction mode, and the problem that reasonable answers or reasonable recommended content questions cannot be provided for some questions possibly occurs, so that the user experience is poor.

Disclosure of Invention

In order to solve the technical problems described above or at least partially solve the technical problems described above, the present disclosure provides a content page display method, a device, an electronic apparatus, and a storage medium.

In a first aspect, an embodiment of the present disclosure provides a content recommendation method, including:

acquiring interaction content of at least one round of interaction with a user;

predicting a user intent based on the interactive content;

and determining corresponding recommended content according to the predicted user intention, and outputting the recommended content.

Optionally, the predicting the user intention based on the interactive content includes:

performing natural semantic analysis on the interactive content to obtain word segmentation results corresponding to the interactive content;

predicting the user intention based on the word segmentation result.

Optionally, in the case that the interactive content is voice interactive content or picture interactive content, the performing natural semantic analysis on the interactive content includes:

converting the voice interaction content or the picture interaction content into text interaction content;

performing natural semantic analysis on the text interaction content obtained by conversion; or alternatively, the process may be performed,

processing the voice interaction content or the image interaction content to generate character expression content representing the voice interaction content or the image interaction content;

and carrying out natural semantic analysis on the text expression content.

Optionally, the predicting the user intention based on the word segmentation result includes:

judging whether the word segmentation in the word segmentation result has a corresponding intention label or not;

if the word segmentation in the word segmentation result has a corresponding intention label, determining the user intention based on the intention label;

if the word segmentation in the word segmentation result does not have the corresponding intention label, inputting the word segmentation result into a preset intention prediction model, and predicting the user intention.

Optionally, the predicting the user intention based on the interactive content includes: predicting a plurality of user intents based on the interactive content;

the method further comprises the steps of: obtaining intention scores corresponding to the intention of each user;

the outputting the recommended content includes:

ranking each of the recommended content according to the intent score;

and outputting the recommended content in front according to the sequence of the recommended content.

Optionally, the method further comprises: acquiring user portrait information of the user;

the determining the corresponding recommended content according to the predicted user intention comprises the following steps: and determining the corresponding recommended content according to the predicted user intention and the user portrait information.

Optionally, before outputting the recommended content, the method further includes:

determining a target output device based on the type of the recommended content;

the outputting the recommended content includes: and sending the recommended content to the target output device so that the target output device outputs the recommended content.

In a second aspect, an embodiment of the present disclosure provides a content recommendation apparatus, including:

the interactive content acquisition unit is used for acquiring interactive content of at least one round of interaction with a user;

a user intention prediction unit for predicting a user intention based on the interactive content;

and the content recommending unit is used for determining corresponding recommended content according to the predicted user intention and outputting the recommended content.

In a third aspect, an embodiment of the present disclosure provides an electronic device, including: a processor for executing a computer program stored in a memory, which when executed by the processor implements the method according to the first aspect.

In a fourth aspect, embodiments of the present disclosure provide a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of the first aspect.

Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:

by adopting the scheme provided by the embodiment of the disclosure, the electronic equipment can judge the user intention based on the interactive content of at least one round, so as to identify the invisible requirement of the user through the user intention, and recommend the corresponding content to the user based on the implicit requirement of the user, thereby improving the diversity and accuracy of content recommendation and improving the user experience.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.

In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.

FIG. 1 is a flow chart of a content page presentation method provided by some embodiments of the present disclosure;

FIG. 2 is an interface schematic of an electronic device provided in one embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a content recommendation device according to some embodiments of the present disclosure

Fig. 4 is a schematic structural diagram of an electronic device provided in some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.

The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below.

Fig. 1 is a flow chart of a content recommendation method provided by some embodiments of the present disclosure, which may be performed by an electronic device. By way of example, the electronic device may be an electronic device having a display output means, such as a smart phone, tablet, smart television, wearable device, or the like.

As shown in fig. 1, the content recommendation method provided in the embodiment of the present disclosure includes steps S101 to S103.

Step S101: and acquiring the interaction content of at least one round of interaction with the user.

In the embodiment of the disclosure, when intelligent interaction with a user is performed, the electronic device may acquire interaction content of at least one round of interaction with the user. The interactive content may include question content input by a user into the electronic device, and may also include target content generated or retrieved by the electronic device based on the question content.

In the embodiment of the present disclosure, according to the actual situation, the interactive content of at least one turn acquired by the electronic device may be various types of content, for example, may be text content, voice content, picture content, link content, or expression content, and the embodiment of the present disclosure is not particularly limited.

Step S102: the user intent is predicted based on the interactive content.

According to the embodiment of the disclosure, after the electronic device acquires the interactive content of at least one round, the electronic device predicts the user intention based on the interactive content of the at least one round.

It should be noted that the user intent in the embodiments of the present disclosure is not the target content that the electronic device generates or retrieves based on the problem content of the user, but rather the implicit needs of the user that are contained in the interactive content, the user intent may not be directly embodied in the literal meaning of the interactive content.

In some embodiments of the present disclosure, the electronic device performing the aforementioned step S102 to predict the user intention based on the interactive content may include steps S1021-S1022.

Step S1021: and carrying out natural semantic analysis on the interactive content to obtain word segmentation results corresponding to the interactive content.

In the embodiment of the disclosure, after the interactive content is obtained, the electronic device performs natural semantic analysis based on the interactive content. Specifically, the electronic device performs word segmentation processing or other processing on the interactive content to obtain a word segmentation result corresponding to the interactive content. It should be noted that the word segmentation result obtained by performing natural semantic analysis on the interactive contents should be a word segmentation result including keywords in the interactive contents.

In the specific disclosure, the process of performing natural semantic analysis on the interactive contents to obtain corresponding word segmentation results is different for different types of interactive contents.

If the interactive content is text interactive content, the electronic equipment can directly perform natural semantic analysis on the interactive content to obtain a corresponding word segmentation result.

And if the interactive content is voice interactive content or picture interactive content, the natural language analysis of the interactive content comprises the following steps: and converting the interactive content into text interactive content, and then carrying out natural language analysis on the converted text interactive content to obtain a corresponding word segmentation result.

Specifically, if the interactive content is voice interactive content, the electronic device firstly performs voice-to-text conversion on the voice interactive content to obtain converted text interactive content. If the interactive content is the picture interactive content, the electronic equipment firstly carries out OCR processing on the picture interactive content and extracts texts in the picture interactive content to obtain text interactive content.

Of course, in some embodiments of the present disclosure, when the interactive content is a voice interactive content or an image interactive content and there is no corresponding text content, the electronic device may further process the voice interactive content or the image interactive content to generate a text expression content that characterizes the voice interactive content or the image interactive content, and then perform natural semantic analysis on the text expression content to obtain a corresponding word segmentation result.

Step S1022: the user intent is predicted based on the word segmentation result.

After obtaining the word segmentation result, the electronic device may predict the user intent based on the word segmentation result.

In some embodiments of the present disclosure, the electronic device predicting the user intent based on the word segmentation result may include steps S1022A-S1022C.

Step S1022A, judging whether the word segmentation in the word segmentation result has a corresponding intention label or not; if yes, go to step S1022B; if not, go to step S1022C.

Step S1022B: determining a user intent based on the intent tag;

step S1022C: inputting the word segmentation result into a preset intention prediction model to predict the intention of the user.

In an embodiment of the disclosure, an electronic device or a server communicatively connected to the electronic device is configured with a word segmentation database. The word segmentation database stores words and corresponding intention labels.

After obtaining the word segmentation in the word segmentation result, the electronic device queries a word segmentation database based on the word segmentation to determine whether a corresponding intention label exists. If the word segmentation database has the corresponding intention label, the intention marked by the intention label is taken as the user intention.

If the electronic equipment does not find the labels corresponding to the word segmentation results in the word segmentation database, the electronic equipment inputs the word segmentation results into a preset intention prediction model, and the intention of the user is predicted through the intention prediction model. The intention prediction model is a model obtained by training a sample word segmentation result and a corresponding sample intention.

Step S103: and determining corresponding recommended content based on the predicted user intention, and outputting the recommended content.

In the embodiment of the disclosure, the association relationship between various contents to be recommended and corresponding user intention labels is stored in a server in communication connection with the electronic equipment. After obtaining the predicted user tag, the electronic device may send the predicted user intent to the server, so that the server searches for the foregoing association relationship based on the user intent, determines recommended content, and returns the recommended content to the electronic device. And the electronic equipment outputs the recommended content for the user to select after receiving the recommended content.

By adopting the content recommendation method provided by the embodiment of the disclosure, the electronic equipment can acquire the interactive content of at least one round of interaction with the user in the process of interacting with the user, predict the intention of the user based on the interactive content, and determine the recommended content recommended to the user based on the predicted intention of the user. By adopting the method provided by the embodiment of the disclosure, the electronic equipment can judge the user intention based on the interactive content of at least one round, so as to identify the invisible requirement of the user through the user intention, and recommend the corresponding content to the user based on the implicit requirement of the user, thereby improving the diversity and accuracy of content recommendation and improving the user experience.

It should be noted that, in the content recommendation method provided in the embodiment of the present disclosure, after the user performs a new interaction with the electronic device, the foregoing steps S101 to S103 may be performed again, so as to recommend content to the user again, until the user clicks the corresponding recommended content or the user closes the interaction interface with the electronic device.

In some embodiments of the present disclosure, the electronic device, when performing step S102 to predict user intentions based on the interactive contents, predicts a plurality of user intentions based on the interactive contents. In addition, the electronic device may also obtain an intention score corresponding to each user intention. The intent score is a score used to characterize the probability of intent likelihood, which may be between 0-1. In the embodiment of the disclosure, the intention score is a judgment score of the recommendation system on the intention of each user based on a recommendation algorithm of the recommendation system. In one implementation, if the user intent is based on an intent tag query, the intent score may be 1, and if the user intent is calculated based on an intent prediction model, the intent probability output by the intent prediction model may be set as the intent score.

In the embodiment of the disclosure, in the case that a plurality of user intentions are predicted, the electronic device may acquire a plurality of recommended contents based on the plurality of user intentions. Correspondingly, outputting recommended content in step S103 includes step S1031 and step S1032.

Step S1031: the recommended content is ranked according to the intent score.

Step S1032: and outputting the previous recommended content according to the sequence of the recommended content.

After obtaining the recommended content corresponding to each intention score, in order to recommend the recommended content corresponding to the user intention with the higher score to the user as much as possible, in some embodiments of the present disclosure, the electronic device ranks the corresponding recommended content according to the obtained intention score of each user intention, and then outputs a preset number of recommended contents according to the ranks of the recommended content.

In step S103 in the foregoing embodiment, the electronic apparatus determines the corresponding point based on the user intention. In other embodiments of the present disclosure, the electronic device may further obtain user portrait information of the user, and the corresponding electronic device may determine corresponding recommended content according to the predicted user intention and the user portrait information. By adopting the user intention and the user image information, recommended content can be provided for the user more accurately, and the content accuracy is improved.

In some embodiments of the present disclosure, before the electronic device performs the outputting of the recommended content in the aforementioned step S103, determining the target output device based on the type of the recommended content may also be performed. Correspondingly, step S103 may include: the recommended content is transmitted to the target output device so that the target output device outputs the recommended content. In some embodiments of the present disclosure, a user may be in an environment with a variety of output devices, for example, a user may be located in an automobile with an intelligent central control display. At this time, if the user interacts with an electronic device such as a smart phone, and the electronic device determines that the user wants to view map information of a certain place based on the intention after use, the electronic device may push the map information to an intelligent central control display screen of the automobile, so as to display the map information by using the intelligent central control display screen.

In order to more clearly understand the solution provided in the embodiments of the present application, the solution provided in the embodiments of the present disclosure will be described below with reference to an example.

Fig. 2 is an interface schematic diagram of an electronic device provided in one embodiment of the present disclosure. As shown in fig. 2, in one embodiment of the present disclosure, the content interaction area 201 of the electronic device displays the following interaction content: the interactive question "the independent highway is driven for the first time" the interactive answer fed back by the electronic device "the independent highway is recovered to be driven for 25 days in 6 months", the interactive question "the Barbeu having a instant food" is used for the second time input, and the interactive answer fed back by the electronic device "recommends you to try to cut mutton by hand before charcoal baking".

After the interactive content is obtained from the content interaction area 201, the electronic device performs intent analysis on the interactive content, and the obtained user intent includes "independent highway self-driving tour", "babble brussels travel", "taste babble brussels food", and based on the user intent, the implicit requirement that the user may have independent highway self-driving tour, babble brussels travel, and the implicit requirement of taste babble brussels food is obtained, so that the corresponding recommended content is found to include recommended content such as "independent highway navigation planning", "independent highway self-driving strategy", "babble brussels food", and weather forecast of a relevant area, and the recommended content is displayed in the content recommendation area 202.

In another embodiment of the present disclosure, the user uses voice to input the interaction question "query the ticket of Beijing Shenzhen for 11 months and 12 days" to the electronic device, and then the electronic device queries "the ticket of Beijing Shenzhen for 11 months and 13 days" that the ticket is sold out "and asks" the remaining ticket of XX for 11 months and 13 days "when the answer of the interaction is fed back, and considers to change the travel date. On the basis, the extracted interactive content comprises 'Beijing to Shenzhen air ticket', 'No. 12 Beijing flying Shenzhen air ticket sold out', and the obtained user intention comprises 'Shenzhen going', 'vehicle is plane', 'air ticket reservation', 'hotel reservation', 'food inquiry', 'travel strategy', 'weather inquiry'. On the basis, the obtained recommended content comprises: XX air ticket booking & purchasing service (Beijing- > Shenzhen 11 months 3 days, remaining ticket & fare display), b. Shenzhen 12 days &13 weather condition and dressing guide, c. Shenzhen hotel booking service, d. Shenzhen food recommendation, e. Shenzhen play strategy.

Then, the user replies to the electronic device ' must be 12 days ', and on the basis, the electronic device obtains the interaction content ' Beijing to Shenzhen air ticket ', ' must be 12 days ', ' vehicle is an airplane ', ' air ticket booking ', ' user intention obtained based on the interaction content comprises ' 12 days to Shenzhen ', ' vehicle is an airplane ', ' air ticket booking ', ' hotel booking ', ' delicious food inquiry ', ' travel strategy ', ' weather inquiry '. On the basis, the obtained recommended content comprises: a. other 12 # can be transferred to Shenzhen's flight reservation service, b.12 # to Shenzhen's high speed rail or train remaining ticket information and the reservation service c.12 # Shenzhen's weather and other related recommended content.

Fig. 3 is a schematic structural diagram of a content recommendation device according to some embodiments of the present disclosure, and the processing device may be understood as part of the functional modules of the electronic device. As illustrated in fig. 3, the content recommendation apparatus 300 provided in the embodiment of the present disclosure includes an interactive content acquisition unit 301, a user intention prediction unit 302, and a content recommendation unit 303.

The interactive content acquisition unit 301 is configured to acquire interactive content that interacts with a user for at least one round.

The user intention prediction unit 302 is used for predicting the user intention based on the interactive contents.

The content recommendation unit 303 is configured to determine corresponding recommended content according to the predicted user intention, and output the recommended content.

In some embodiments of the present disclosure, the user intent prediction unit 302 includes a natural semantic analysis subunit and an intent prediction subunit. The natural semantic analysis subunit is used for carrying out natural semantic analysis on the interactive content to obtain word segmentation results corresponding to the interactive content. The intention prediction subunit is used for predicting the intention of the user based on the word segmentation result.

In some embodiments of the present disclosure, where the interactive content is voice interactive content or picture interactive content, the natural semantic analysis subunit performs natural semantic analysis on the interactive content, including: and converting the voice interaction content or the picture interaction content into text interaction content, and carrying out natural semantic analysis on the text interaction content obtained by conversion. Or the natural semantic analysis subunit firstly processes the voice interaction content or the image interaction content to generate character expression content for representing the voice interaction content or the image interaction content, and then carries out natural semantic analysis on the character expression content.

In some embodiments of the present disclosure, the user intent prediction subunit includes a determination module and an intent prediction module. The judgment module is used for judging whether the segmented words in the segmented word result have corresponding intention labels, and the intention prediction module is used for determining the user intention based on the intention labels under the condition that the segmented words in the segmented word result have the corresponding intention labels and inputting the segmented word result into a preset intention prediction model to obtain the predicted user intention under the condition that the segmented words in the segmented word result do not have the corresponding intention labels.

In some embodiments of the present disclosure, the user intent prediction unit 302 predicts a plurality of user intents based on the interactive content. In this case, the content recommendation device may further include an intention score determination unit. The intention score determining unit is used for obtaining intention scores corresponding to the intention of each user. The content recommendation unit 303 includes a ranking sub-unit for ranking the respective recommended contents according to the intention score and a content recommendation sub-unit for outputting the recommended contents before according to the ranking of the recommended contents.

In some embodiments of the present disclosure, the content recommendation apparatus may further include a portrait information acquisition unit for acquiring user portrait information of the user. Correspondingly, the content recommendation unit 303 may determine the corresponding recommended content according to the predicted user intention and the user portrait information.

In some embodiments of the present disclosure, the content recommendation apparatus may further include a target output device determining unit for determining a target output device based on a type of recommended content; correspondingly, the content recommendation unit 303 may transmit the recommended content to the target output device, so that the target output device outputs the recommended content.

The disclosed embodiments also provide an electronic device comprising a processor and a memory, wherein the memory stores a computer program, and the method of any of the above embodiments can be implemented when the computer program is executed by the processor.

Fig. 4 is a schematic structural diagram of an electronic device provided in some embodiments of the present disclosure. As shown in fig. 4, the electronic device 400 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 401, which may perform various suitable actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage means 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the electronic device 400 are also stored. The processing device 401, the ROM 402, and the RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.

In general, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 408 including, for example, magnetic tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. While fig. 4 shows an electronic device 400 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.

In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via communications device 409, or from storage 408, or from ROM 402. The above-described functions defined in the methods of the embodiments of the present disclosure are performed when the computer program is executed by the processing device 401.

It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.

The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring interaction content of at least one round of interaction with a user; predicting a user intent based on the interactive content; and determining corresponding recommended content according to the predicted user intention, and outputting the recommended content.

Computer program code for carrying out operations of the present disclosure may be written in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

The embodiments of the present disclosure further provide a computer readable storage medium, where a computer program is stored, where the computer program, when executed by a processor, may implement a method according to any one of the foregoing embodiments, and the implementation manner and beneficial effects of the method are similar, and are not described herein again.

The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A content recommendation method, comprising:

acquiring interaction content of at least one round of interaction with a user;

predicting a user intent based on the interactive content;

2. The method of claim 1, wherein predicting user intent based on the interactive content comprises:

predicting the user intention based on the word segmentation result.

3. The method of claim 2, wherein the step of determining the position of the substrate comprises,

in the case that the interactive content is voice interactive content or picture interactive content, the performing natural semantic analysis on the interactive content includes:

and carrying out natural semantic analysis on the text expression content.

4. The method of claim 2, wherein the predicting the user intent based on the word segmentation result comprises:

5. The method of claim 1, wherein the step of determining the position of the substrate comprises,

the predicting the user intention based on the interactive content comprises: predicting a plurality of user intents based on the interactive content;

the outputting the recommended content includes:

ranking each of the recommended content according to the intent score;

6. The method as recited in claim 1, further comprising: acquiring user portrait information of the user;

7. The method of claim 1, wherein prior to outputting the recommended content, the method further comprises:

8. A content recommendation device, comprising:

9. An electronic device, comprising: a processor for executing a computer program stored in a memory, which when executed by the processor carries out the steps of the method according to any one of claims 1-7.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-7.