CN115393008A - Method and device for recommending portrait of electricity selling company - Google Patents

Method and device for recommending portrait of electricity selling company Download PDF

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CN115393008A
CN115393008A CN202210953357.6A CN202210953357A CN115393008A CN 115393008 A CN115393008 A CN 115393008A CN 202210953357 A CN202210953357 A CN 202210953357A CN 115393008 A CN115393008 A CN 115393008A
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company
user
data
portrait
power selling
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吴敬慧
黄远明
曾智健
姚星安
朱文俊
舒康安
徐云
胡鑫
罗锦庆
吴明兴
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Guangdong Electric Power Transaction Center Co ltd
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Abstract

The invention discloses a method and a device for recommending portrait of an electricity selling company, wherein the method comprises the following steps: respectively acquiring user data and a plurality of power selling company data, wherein the user data relates to user power demand information or preference information; calculating a matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values; screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values; and recommending the corresponding company portrait of the power selling company to the user based on the plurality of target matching weight values for the user to refer. According to the invention, after the user data is collected, the matching degree of the user data and the data of a plurality of power selling companies can be calculated, and the portrait of the power selling company is preferentially recommended to the user according to the matching degree, so that the actual requirements of the user can be met, and the recommendation accuracy can be improved.

Description

Method and device for recommending portrait of electricity selling company
Technical Field
The invention relates to the technical field of portrait updating, in particular to a portrait recommendation method and device for a power selling company.
Background
With the gradual increase of the number of the power selling companies, a user needs to look up a large amount of information of the power selling companies when purchasing electric power, and then selects a proper power selling company by comparing a large amount of information.
In order to allow a user to view various information of a large number of power selling companies comprehensively and intuitively, a currently common method is to acquire previous purchase record information of the user, select a corresponding power selling company based on previous history information, and recommend a corresponding portrait to the user for the user to refer to.
However, the above method has the following technical problems: the actual needs and preferences of the user may change continuously, and it is difficult to meet the current application needs of the user by recommending company images using previous historical information.
Disclosure of Invention
The invention provides a method and a device for recommending portrait of an electricity selling company.
The first aspect of the embodiment of the invention provides a method for recommending portrait of an electric power selling company, which comprises the following steps:
respectively acquiring user data and a plurality of power selling company data, wherein the user data relates to user power demand information or preference information;
calculating a matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values;
screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values;
and recommending the corresponding company portrait of the power selling company to the user based on a plurality of target matching weight values for the user to refer to.
In a possible implementation manner of the first aspect, the calculating a matching weight value of the user data and each of the power selling company data includes:
extracting a plurality of company labels from each power selling company data, and determining semantic information of the labels corresponding to the company labels;
extracting user semantic information from the user data, and screening target semantic information which is the same as the user semantic information from the plurality of label semantic information;
and calculating the weight ratio of the target semantic information in the plurality of label semantic information, and taking the weight ratio as a matching weight value.
In a possible implementation manner of the first aspect, the acquiring user data includes:
randomly selecting and displaying a plurality of preset intention option contents from a preset information list;
and screening a plurality of user-selected intention option contents from the preset intention option contents, and taking the user-selected intention option contents as user data.
In a possible implementation manner of the first aspect, the recommending, to a user, a company representation of a corresponding power selling company based on a plurality of the target matching weight values includes:
based on the numerical value of the target matching weight value, sorting the data of the plurality of corresponding power selling companies from high to low;
according to the sorting result, sequentially adopting the data of the power selling company corresponding to each target matching weight value to depict a company portrait;
and recommending a plurality of company portraits to the user according to the sorting result.
In a possible implementation manner of the first aspect, after the step of recommending, to a user, a company representation of a corresponding electricity selling company based on a plurality of the target matching weight values, the method further includes:
acquiring change data of a user, wherein the change data comprises the turning-over information and browsing records of the user;
calculating a data association value of the changed data and the user data;
if the data correlation value is smaller than a preset correlation value, searching corresponding target company data from the plurality of power selling company data according to the changed data;
updating a company representation using the target company data.
In a possible implementation manner of the first aspect, the updating the company image by using the target company data includes:
determining semantic information corresponding to the changed data to obtain changed semantic information;
determining whether the company portrait contains a portrait label corresponding to the changed semantic information;
if the company portrait does not include the portrait label corresponding to the changed semantic information, generating a changed label corresponding to the changed semantic information, and adding the changed label to the company portrait;
if the company portrait includes the portrait label corresponding to the changed semantic information, adding a highlight display effect to the portrait label corresponding to the changed semantic information.
In a possible implementation manner of the first aspect, after the step of updating the company representation with the target company data, the method further includes:
and adding a dynamic effect to the updated company portrait, and sending the dynamic effect to a preset user terminal for a user to check.
A second aspect of an embodiment of the present invention provides an apparatus for recommending a portrait of an electric power selling company, the apparatus including:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for respectively acquiring user data and a plurality of power selling company data, and the user data is related to user power demand information or preference information;
the calculating module is used for calculating the matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values;
the screening module is used for screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values;
and the recommending module is used for recommending the company portrait of the corresponding power selling company to the user based on the plurality of target matching weight values so as to be referred by the user.
Compared with the prior art, the method and the device for recommending the portrait of the electricity selling company provided by the embodiment of the invention have the beneficial effects that: the invention is possible.
Drawings
FIG. 1 is a flowchart illustrating a method for recommending a portrait of an electric vendor according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an image recommendation device for a power selling company according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In order to allow a user to comprehensively and intuitively view various information of a large number of power selling companies, a currently common method is to acquire prior purchase record information of the user, select a corresponding power selling company based on prior history information, and recommend a corresponding portrait to the user for the user to refer to.
However, the above method has the following technical problems: the actual needs and preferences of the user may change continuously, and it is difficult to meet the current application needs of the user by recommending company images using previous historical information.
In order to solve the above problem, a method for recommending a portrait of an electric power selling company provided by the embodiments of the present application will be described and explained in detail by the following specific embodiments.
Referring to fig. 1, a flowchart illustrating a method for recommending a portrait of an electric power vendor according to an embodiment of the present invention is shown.
In one embodiment, the method may be applied to a user terminal.
By way of example, the method for recommending a portrait of an electricity selling company may include:
s11, respectively acquiring user data and a plurality of electric power selling company data, wherein the user data relates to user power demand information or preference information.
The user power demand information or the preference information may be purchase intention information of the user, such as data of low price, large capacity, high reputation, and the like. The electricity selling company data can be data of the performance, electricity selling quantity, credit, price, customer evaluation and the like of the electricity selling company.
In order to accurately collect user data, step S11 may include the following sub-steps, as an example:
and S111, randomly selecting and displaying a plurality of preset intention option contents from a preset information list.
Specifically, a plurality of predetermined intention contents may be randomly selected from a predetermined information list, wherein all the intention contents from the predetermined information list may be predetermined and may include a plurality of related intention information. And then, the contents of the plurality of preset intention options can be manufactured into corresponding display pages to be displayed for the user to view and select.
S112, screening a plurality of user-selected intention option contents from the preset intention option contents, and taking the user-selected intention option contents as user data.
Specifically, the user can select option contents meeting personal intention from a plurality of preset intention option contents, and the option contents selected by the user are used as user data to determine the actual purchase intention of the user.
In actual operation, a plurality of preset intention option contents can be displayed on the user terminal and then selected by the user.
And S12, calculating the matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values.
After the purchasing intention of the user is determined, the matching weight value of the user data and the data of each power selling company can be determined, and the power selling company which the user is more matched with is determined according to the matching weight value, so that the data of the power selling company can be recommended to the user in a targeted manner for the user to refer.
In order to accurately calculate the matching weight values, in an alternative embodiment, step S12 may include the following sub-steps:
s121, extracting a plurality of company labels from the data of each power selling company, and determining semantic information of the labels corresponding to the company labels.
Specifically, the company label may be a label included in an original figure of the power selling company, or may be a label that can represent a feature of the power selling company, for example, a low price, a good reputation, or the like.
After the company labels are obtained, semantic information of each company label is determined, and label semantic information is obtained.
S122, extracting user semantic information from the user data, and screening target semantic information which is the same as the user semantic information from the plurality of label semantic information.
User semantic information can be extracted from user data, and specifically, the user semantic information can be directly selected by the user. In an embodiment, if the user selects the multiple pieces of selection intention information, the multiple pieces of selection intention information may be aggregated and classified to obtain the user semantic information.
The information identical to the user semantic information can be selected from a plurality of label semantic information to obtain the target semantic information.
S123, calculating the weight ratio of the target semantic information in the plurality of label semantic information, and taking the weight ratio as a matching weight value.
The weight ratio of the target semantic information in the semantic information of the tags of the power selling company can be calculated.
Alternatively, a plurality of label semantic information may be input into a preset convolutional neural network, a weight ratio of each label semantic information is calculated, and then the weight ratio of the label semantic information which is the same as the target semantic information is searched for as a matching weight.
Alternatively, the user may set a weight ratio for each tag semantic information in advance, and then use the weight ratio of the tag semantic information that is the same as the target semantic information as the matching weight.
S13, screening a plurality of target matching weight values larger than a preset threshold value from the plurality of matching weight values.
After the matching weight values of the user and each power selling company are calculated, the matching weight values larger than a preset threshold value can be screened from the multiple matching weight values to obtain a plurality of target matching weight values.
And S14, recommending the company portrait of the corresponding power selling company to the user based on the plurality of target matching weight values for the user to refer.
The power selling company data corresponding to the target matching weight value can be the power selling company data matched with the user, the power selling company data can be directly adopted to depict the corresponding company portrait, and then the company portrait is recommended and presented to the user for the user to refer, so that the quick and accurate recommendation is realized, the user does not need to check all the power selling company data, the checking efficiency is improved, and the user can conveniently select the power selling company of the mood.
In one embodiment, there are a plurality of possible target matching weight values, and in order to recommend the representation of the power selling company to the user more accurately, in one embodiment, the step S14 may include the following sub-steps:
and S141, sorting the data of the plurality of corresponding power selling companies from high to low based on the numerical value of the target matching weight value.
And S142, according to the sorting result, sequentially adopting the data of the power selling companies corresponding to the target matching weight values to depict the company portrait.
And S143, recommending a plurality of company portraits to the user according to the sorting result.
Specifically, the data of the power selling companies can be sorted from high to low according to the numerical value of the first target matching weight value, then company pictures are depicted one by one according to the sorting result, and the company pictures are recommended to the user one by one according to the sorting result and displayed.
In actual operation, each portrait can be displayed on an interface of a user, and the display mode can be that a plurality of company portraits to be recommended are overlapped together, then the first one is the company portrait with the maximum target matching weight value, and the last one is the company portrait with the minimum target matching weight value. The user can check in sequence, slide away if the current view is not proper, and then search for the next one.
In an embodiment, the purchase intention of the user may be changed, and the direction of the change is different from the previous intention, which may indicate that the attention point of the user is changed, in order to cater for the change of the user, wherein, as an example, the method may further include:
s15, obtaining the change data of the user, wherein the change data comprises the browsing information and the browsing record of the user.
Alternatively, as in the operation manner of steps S111-S112, the intention option may be displayed to the user and then selected by the user, and it is determined whether the intention option reselected by the user is the same as the intention option selected previously, and if not, the newly selected intention option is change data.
And S16, calculating a data association value of the changed data and the user data.
In particular, a data association of change data with previous user data may be calculated, in particular an association of both a new intent option and a previously selected intent option may be calculated.
And S17, if the data correlation value is smaller than a preset correlation value, searching corresponding target company data from the plurality of power selling company data according to the changed data.
If the data correlation value is smaller than the preset correlation value, it indicates that the correlation degree between the two data is small, and the focus point of the user is changed, the matched target company data can be searched again in the multiple electric power selling company data according to the changed data, and the specific operation mode can be as in steps S121 to S123.
And S18, updating the company image by using the target company data.
Finally, the displayed company representation may be updated with the change data for reference by the user.
In one embodiment, step S18 may include the following sub-steps:
and S181, determining semantic information corresponding to the changed data to obtain changed semantic information.
S182, determining whether the company portrait contains a portrait label corresponding to the changed semantic information.
Specifically, it may be determined whether the content of the alteration semantic information is contained in the previously presented company representation.
S183, if the company image does not include the image label corresponding to the change semantic information, generating a change label corresponding to the change semantic information, and adding the change label to the company image.
S184, if the company image comprises the image label corresponding to the changed semantic information, adding a highlight display effect to the image label corresponding to the changed semantic information.
If the company image contains the portrait label corresponding to the changed semantic information, the data of the power selling company can meet the requirements of the user, and a highlight display effect can be added to the portrait label corresponding to the changed semantic information in the company image, so that the user can quickly see the portrait of the power selling company.
If the company image does not contain the image label corresponding to the changed semantic information, a change label corresponding to the changed semantic information is generated, and the change label is added to the company image to inform the user that the company does not contain the intention content of the user. Specifically, a reverse direction mark is added, so that the user can know that the company has no intention content required by the user in the change label.
If the company image contains the portrait label corresponding to the changed semantic information, adding a highlight display effect to the portrait label corresponding to the changed semantic information, wherein the highlight display effect may be a display effect of a prominent color or a corresponding animation display effect, for example, the label continuously flickers.
To further facilitate the user's viewing, the method may further comprise, as an example:
and S19, adding a dynamic effect to the updated company portrait, and sending the dynamic effect to a preset user terminal for a user to check.
Specifically, the dynamic effect may be that each portrait label is rotated, and the portrait label may blink, may rebound and move back and forth, fade in and fade out, or other dynamic effects, so that the portrait of the whole company may have a more gorgeous display effect, and then be sent to the user terminal, so that the user terminal may display the corresponding portrait for the user.
In this embodiment, an embodiment of the present invention provides a method for recommending an image of an electricity selling company, which has the following beneficial effects: the invention can respectively obtain the user data and the data of a plurality of power selling companies; then calculating a matching weight value of the user data and each power selling company data; and screening the data of the power selling companies matched with the user according to the matching weight value, and describing and recommending the corresponding company portrait by using the matched data of the power selling companies for the reference of the user, so that the related power selling companies can be quickly and accurately matched with the user, and the recommendation accuracy of the user is improved.
The embodiment of the invention also provides a recommendation device for a portrait of an electric power selling company, and referring to fig. 2, a schematic structural diagram of the recommendation device for a portrait of an electric power selling company provided by the embodiment of the invention is shown.
Wherein, as an example, the recommending device for the image of the power selling company can comprise:
an obtaining module 201, configured to obtain user data and data of a plurality of power selling companies, respectively, where the user data is information about power demand of a user or preference information;
the calculating module 202 is configured to calculate a matching weight value between the user data and each of the power selling company data to obtain a plurality of matching weight values;
a screening module 203, configured to screen a plurality of target matching weight values that are greater than a preset threshold from the plurality of matching weight values;
and the recommending module 204 is configured to recommend a company portrait of a corresponding power selling company to the user based on the plurality of target matching weight values, so as to be referred to by the user.
Respectively acquiring user data and a plurality of power selling company data, wherein the user data relates to user power demand information or preference information;
calculating a matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values;
screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values;
and recommending the corresponding company portrait of the power selling company to the user based on the plurality of target matching weight values for the user to refer.
Optionally, the computing module is further configured to:
extracting a plurality of company labels from each power selling company data, and determining semantic information of the labels corresponding to the company labels;
extracting user semantic information from the user data, and screening target semantic information which is the same as the user semantic information from the plurality of label semantic information;
and calculating the weight ratio of the target semantic information in the plurality of label semantic information, and taking the weight ratio as a matching weight value.
Optionally, the obtaining module is further configured to:
randomly selecting and displaying a plurality of preset intention option contents from a preset information list;
and screening a plurality of user-selected intention option contents from the preset intention option contents, and taking the user-selected intention option contents as user data.
Optionally, the recommending module is further configured to:
based on the numerical value of the target matching weight value, sequencing the data of a plurality of corresponding power selling companies from high to low;
according to the sorting result, the data of the power selling companies corresponding to each target matching weight value are adopted to depict company pictures in sequence;
and recommending a plurality of the company portraits to the user according to the sorting result.
Optionally, the apparatus further comprises:
the data change module is used for acquiring change data of a user, wherein the change data comprises the turning-over information and the browsing record of the user;
the data association module is used for calculating a data association value of the changed data and the user data;
the change searching module is used for searching corresponding target company data from the plurality of power selling company data according to the change data if the data correlation value is smaller than a preset correlation value;
and the portrait updating module is used for updating the company portrait by utilizing the target company data.
Optionally, the representation update module is further configured to:
determining semantic information corresponding to the changed data to obtain changed semantic information;
determining whether the company portrait contains a portrait label corresponding to the changed semantic information;
if the company portrait does not include the portrait label corresponding to the changed semantic information, generating a changed label corresponding to the changed semantic information, and adding the changed label to the company portrait;
if the company portrait includes the portrait label corresponding to the changed semantic information, adding a highlight display effect to the portrait label corresponding to the changed semantic information.
Optionally, the apparatus further comprises:
and the sending module is used for adding a dynamic effect to the updated company portrait and sending the dynamic effect to a preset user terminal for a user to check.
It can be clearly understood by those skilled in the art that, for convenience and brevity, the specific working process of the apparatus described above may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
Further, an embodiment of the present application further provides an electronic device, including: a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for recommending a picture of an electric power selling company.
Further, the present application provides a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the method for recommending a portrait of an electric power selling company according to the above embodiment.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.

Claims (10)

1. A method for recommending a portrait of a power selling company is characterized by comprising the following steps:
respectively acquiring user data and a plurality of power selling company data, wherein the user data relates to user power demand information or preference information;
calculating a matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values;
screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values;
and recommending the corresponding company portrait of the power selling company to the user based on a plurality of target matching weight values for the user to refer to.
2. The method for recommending a vendor profile of claim 1, wherein said calculating a matching weight value of said user data and each of said vendor data comprises:
extracting a plurality of company labels from each power selling company data, and determining semantic information of the labels corresponding to the company labels;
extracting user semantic information from the user data, and screening target semantic information which is the same as the user semantic information from the plurality of label semantic information;
and calculating the weight ratio of the target semantic information in the plurality of label semantic information, and taking the weight ratio as a matching weight value.
3. The method for recommending a portrait of an electric vendor according to claim 1, wherein said obtaining user data comprises:
randomly selecting and displaying a plurality of preset intention option contents from a preset information list;
and screening a plurality of user-selected intention option contents from the preset intention option contents, and taking the user-selected intention option contents as user data.
4. The method for recommending a company profile of an electric power selling company of claim 1, wherein said recommending a corresponding company profile of an electric power selling company to a user based on a plurality of said target matching weight values comprises:
based on the numerical value of the target matching weight value, sequencing the data of a plurality of corresponding power selling companies from high to low;
according to the sorting result, the data of the power selling companies corresponding to each target matching weight value are adopted to depict company pictures in sequence;
and recommending a plurality of the company portraits to the user according to the sorting result.
5. The method for recommending a company profile of an electric power selling company according to any one of claims 1-4, wherein after said step of recommending a corresponding company profile of an electric power selling company to a user based on a plurality of said target matching weight values, said method further comprises:
acquiring change data of a user, wherein the change data comprises the turning-over information and browsing records of the user;
calculating a data association value of the changed data and the user data;
if the data correlation value is smaller than a preset correlation value, searching corresponding target company data from the plurality of power selling company data according to the changed data;
updating a company representation with the target company data.
6. The method for recommending a picture of an electric power selling company of claim 5, wherein said updating a company picture with said target company data comprises:
determining semantic information corresponding to the changed data to obtain changed semantic information;
determining whether the company portrait contains a portrait label corresponding to the changed semantic information;
if the company portrait does not include the portrait label corresponding to the changed semantic information, generating a changed label corresponding to the changed semantic information, and adding the changed label to the company portrait;
and if the company portrait comprises the portrait label corresponding to the changed semantic information, adding a highlight display effect to the portrait label corresponding to the changed semantic information.
7. The method of recommending a vendor representation of claim 5, wherein after said step of updating a company representation with said target company data, said method further comprises:
and adding a dynamic effect to the updated company portrait, and sending the dynamic effect to a preset user terminal for a user to check.
8. An image recommendation device for an electric power selling company, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for respectively acquiring user data and a plurality of power selling company data, and the user data is related to user power demand information or preference information;
the calculation module is used for calculating the matching weight value of the user data and each power selling company data to obtain a plurality of matching weight values;
the screening module is used for screening a plurality of target matching weight values which are larger than a preset threshold value from the plurality of matching weight values;
and the recommending module is used for recommending the corresponding company portrait of the power selling company to the user based on the target matching weight values so as to be referred by the user.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of recommending a representation of an electricity selling company as claimed in any one of claims 1 to 7 when executing said program.
10. A computer-readable storage medium storing computer-executable instructions for causing a computer to perform the method for recommending a picture of an electric power selling company as recited in any one of claims 1 to 7.
CN202210953357.6A 2022-08-10 2022-08-10 Method and device for recommending portrait of electricity selling company Pending CN115393008A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117390294A (en) * 2023-12-13 2024-01-12 广东电力交易中心有限责任公司 Personalized search method and device for relieving data scarcity of power retail platform

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117390294A (en) * 2023-12-13 2024-01-12 广东电力交易中心有限责任公司 Personalized search method and device for relieving data scarcity of power retail platform
CN117390294B (en) * 2023-12-13 2024-03-08 广东电力交易中心有限责任公司 Personalized search method and device for relieving data scarcity of power retail platform

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