CN114548787A - User generated content management method, device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the application discloses a method and a device for managing user generated content, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring text information of first user generated content to be processed, and processing the text information to obtain a plurality of characteristic values of the first user generated content to be processed under the plurality of first indexes; determining a first score of the first to-be-processed user generated content under each second index according to the plurality of feature values and a plurality of first weights of the plurality of first indexes; determining a target score of the first to-be-processed user generated content according to a plurality of second weights of the plurality of second indexes and the first score under each second index; and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for managing user-generated content, an electronic device, and a storage medium.
Background
With the development of the internet era, the sales mode of off-line visit is highly depended, and part of the sales mode needs to be replaced by on-line remote visit. In visiting a customer, the sales agent needs to exercise many professional contents, such as: insurance plans, insurance drawings, and the like, for sales demonstrations to the customer.
The production mode of professional content is that the headquarters of the company or each organization generally outputs a standardized scheme for the agent to use. However, based on different situations such as sales habits and customer requirements, different agents often need to edit and assemble the standardized schemes to form new personalized online sales schemes, that is, User Generated Content (User Generated Content). At present, companies provide online meeting tools for agents, plan online assembly, editing, uploading and other functions of a scheme, and after user generated contents of the agents are checked for compliance, the contents are displayed on a platform for all sales agents to use.
In view of the above situation that the user generated content can be uploaded, a large amount of user generated content for online sales may be generated, and how to effectively manage the user generated content is an urgent problem to be solved at present.
Disclosure of Invention
The embodiment of the application provides a user generated content management method and device, electronic equipment and a storage medium, and the user generated content is effectively managed.
In a first aspect, an embodiment of the present application provides a method for managing user-generated content, including:
determining a plurality of first weights of a plurality of first indexes relative to each second index respectively according to an analytic hierarchy process, wherein the plurality of first indexes correspond to the plurality of first weights one to one, the plurality of first indexes are used for determining basic information of user-generated content, each second index is composed of a part of the first indexes, and the part of the first indexes corresponding to any two second indexes is completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
acquiring text information of first to-be-processed user generated content, and processing the text information to obtain a plurality of characteristic values of the first to-be-processed user generated content under the plurality of first indexes, wherein the first to-be-processed user generated content is any one of the plurality of to-be-processed user generated content;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
In a second aspect, an embodiment of the present application provides a user-generated content management apparatus, including: an acquisition unit and a processing unit;
the processing unit is used for determining a plurality of first weights of a plurality of first indexes relative to each second index respectively according to an analytic hierarchy process, wherein the plurality of first indexes correspond to the plurality of first weights one by one, the plurality of first indexes are used for determining basic information of user-generated content, each second index is composed of a part of the first indexes, and the parts of the first indexes corresponding to any two second indexes are completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
the acquiring unit is used for acquiring text information of the first user-generated content to be processed;
the processing unit is further configured to process the text information to obtain a plurality of feature values of the first to-be-processed user generated content under the plurality of first indexes, where the first to-be-processed user generated content is any one of the plurality of to-be-processed user generated contents;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
In a third aspect, an embodiment of the present application provides an electronic device, including: a processor coupled to a memory, the memory configured to store a computer program, the processor configured to execute the computer program stored in the memory to cause the electronic device to perform the method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, which stores a computer program, where the computer program makes a computer execute the method according to the first aspect.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a non-transitory computer-readable storage medium storing a computer program, the computer being operable to cause a computer to perform the method according to the first aspect.
The embodiment of the application has the following beneficial effects:
it can be seen that, in the embodiment of the present application, first, a plurality of first weights of a plurality of first indexes with respect to each second index and a plurality of second weights of a plurality of second indexes with respect to a third index are determined through an analytic hierarchy process; the determined weight is determined by an analytic hierarchy process instead of the manually set weight, so that the determined weight has higher precision; and finally, successively weighting and summing the scores corresponding to each first index according to the multiple first weights, the multiple second weights and the scores corresponding to each first index to obtain the target score of the content generated by each user to be processed. Finally, the target score of the content name generated by each user to be processed reflects the quality of the content generated by each user to be processed. Therefore, the generated contents of the plurality of users to be processed are managed according to the target scores of the generated contents of each user to be processed, and a solution is provided for the fine management of the generated contents of the users to be processed.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic diagram of a user-generated content management system provided in the practice of the present application;
fig. 2 is a schematic flowchart of a user-generated content management method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a hierarchy analysis method for determining weights provided by an embodiment of the present application;
fig. 4 is a schematic flowchart of another user-generated content management method according to an embodiment of the present application;
FIG. 5 is a block diagram illustrating functional units of a user-generated content management apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of this application and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, result, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Referring to fig. 1, fig. 1 is a user generated content management system according to an embodiment of the present application. The user generated content management system includes a first user terminal 10, a user generated content management device 20 and a second user terminal 30, wherein users of the first user terminal 10 and the second user terminal 30 may be the same or different, and the application is not limited thereto.
Illustratively, the sales agent may edit the user-generated content, i.e., the online sales plan, at the first user terminal 10 and upload the online sales plan to the user-generated content management apparatus 20. The sales agent may directly edit and generate the user-generated content on the front page of the user-generated content management apparatus 20. Therefore, the present application does not limit the manner in which the sales agent generates the user-generated content.
Then, the user-generated content management apparatus 20 determines, according to an analytic hierarchy process, a plurality of first weights of a plurality of first indexes with respect to each of second indexes, respectively, where the plurality of first indexes are used to determine basic information of the user-generated content, each of the second indexes is composed of a part of the plurality of first indexes, and the parts of the first indexes corresponding to any two of the second indexes are different; then, according to an analytic hierarchy process, determining a plurality of second weights of a plurality of second indexes relative to a third index, wherein the third index is used for determining the quality of the user-generated content;
further, after the multiple first weights and the multiple second weights are determined, obtaining text information of the first to-be-processed user generated content, and processing the text information to obtain multiple feature values of the first to-be-processed user generated content under multiple first indexes, wherein the first to-be-processed user generated content is any one of the multiple to-be-processed user generated contents; then, according to the plurality of first characteristic values and the plurality of first weights, determining a first score of the first to-be-processed user generated content under each second index; determining a target score of the first to-be-processed user-generated content according to the plurality of third weights and the first score under each second index; and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
For example, the plurality of to-be-processed user generated contents can be displayed on the front-end visual interface according to the target scores.
Accordingly, when the user obtains the user generated content (the online sales scheme) through the second user terminal 30, the user can see the generated content of the plurality of users to be processed, which is displayed in the order from high to low according to the target score (i.e., quality), so that the online sales scheme with the highest quality can be quickly located, and the sales success rate is further improved.
It can be seen that, in the embodiment of the present application, first, a plurality of first weights of a plurality of first indexes with respect to each second index and a plurality of second weights of a plurality of second indexes with respect to a third index are determined through an analytic hierarchy process; the determined weight is determined by an analytic hierarchy process instead of the manually set weight, so that the determined weight has higher precision; and finally, successively weighting and summing the scores corresponding to each first index according to the multiple first weights, the multiple second weights and the scores corresponding to each first index to obtain the target score of the content generated by each user to be processed. Finally, the target score of the content name generated by each user to be processed reflects the quality of the content generated by each user to be processed. Therefore, the generated contents of the plurality of users to be processed are managed according to the target scores of the generated contents of each user to be processed, and a solution is provided for the fine management of the generated contents of the users to be processed.
Referring to fig. 2, fig. 2 is a diagram illustrating a user generated content management method according to an embodiment of the present application. The method is applied to the user-generated content management apparatus described above. The method comprises the following steps:
201: according to the analytic hierarchy process, a plurality of first weights of the first indexes relative to each second index are determined.
The plurality of first indexes are used for determining basic information of user generated content, the user generated content is an online sales scheme, namely the online sales scheme edited and uploaded by a sales agent, and the plurality of first indexes correspond to the plurality of first weights one to one. Each second index is composed of part of the first indexes, and the part of the first indexes corresponding to any two second indexes is completely different.
Exemplary, the first indicators of the present application include, but are not limited to: the creator performance, creator department age, creator personal reputation, click-through rate, number of browses, number of praise, collection times, and number of conversions of the order generated by the user. Wherein the author performance of the user-generated content is the total performance (e.g., total sales) of the author before the user-generated content is released; the click rate is the accumulated number of browsed people from the moment of releasing the generated content of the user to the current moment; the browsing times are the browsing times from the time of the user generating the content release to the current time; the number of praise people is the number of praise people from the time of content release generated by the user to the current time; the collection times are collection times from the time of content release generated by a user to the current time; the order output conversion quantity is the quantity of successful transaction after the user generates the online sales scheme in the content from the content release time to the current time.
Exemplary, second plurality of indicators of the present application include, but are not limited to: the user generates an originator portrait of the content, a content consumption and a business value, wherein the originator portrait is composed of originator performance, originator department age and originator personal honor, the content consumption is composed of click rate, number of browsing people and number of praise people, and the business value is composed of collection times and number of order output conversion.
Illustratively, the third index of the present application is a target score of the user-generated content, i.e., a quality score of the user-generated content.
It should be noted that the reason why the above three second indexes are set is that for the remote visit scenario (i.e. the online sales scenario), the key point is whether the user generated content can be actually applied to the customer service and produce the service value, i.e. directly reflect the quality of the user generated content; furthermore, the author acts as the subject of user-generated content whose quality is closely related to the author's existing behavioral attributes, such as: it is difficult for an agent with a short working experience and poor performance to create high quality user-generated content. Therefore, the representation of the creator can indirectly reflect the quality of the user generated content; finally, the consumption and use conditions of the user generated content by other users reflect the popularity of the user generated content on the platform, namely, the content consumption can also indirectly reflect the quality of the user generated content. Therefore, the three second indexes are arranged to comprehensively judge the quality of the content generated by one user, so that the judgment result can be more accurate, and the management precision of the content generated by the user is further improved.
Illustratively, as shown in fig. 3, a plurality of first indexes are used as a plurality of indexes in the schema layer, a plurality of second indexes are used as a plurality of indexes in the criterion layer, and a third index is used as an index of the target layer. Therefore, according to the analytic hierarchy process, a plurality of first weights of the first indexes in the scheme layer relative to each second index in the criterion layer are determined, wherein the first indexes correspond to the first weights one to one. For example, a plurality of weights may be determined for the creator performance, creator department age, creator personal reputation, click-through rate, number of browsing people, number of praise people, collection times, and number of singleton conversions, each relative to the creator profile.
Specifically, for each second index, a first importance of an influence of any two first indexes of the plurality of first indexes on each second index is obtained. And constructing a pair comparison matrix corresponding to each second index according to the first importance of the influence of any two first indexes on each second index.
Illustratively, the first importance of the effect of a first index on each of the second indices may be measured on a 1-9 scale, where 1 represents the same importance, 3 represents slightly important, 5 represents important, 7 represents much more important, and 9 represents extremely important. It is of course also possible to characterize the degree of importance between the above-mentioned several degrees of importance separately by 2/4/6/8, for example, 2 characterizes the degree of importance between 1 and 3. For example, if a first index i is slightly more important than a first index j than the influence of a second index in a layer if the first index i is aligned with the first index j, the corresponding element of the first index i and the first index j in the pair-wise comparison matrix is 3.
Therefore, according to the above-mentioned scaling method, a pair comparison matrix corresponding to a plurality of first indexes and any one second index of the present application as shown in table 1 may be constructed:
table 1:
wherein, T1, T2, T3, T4, T5, T6, T7 and T8 are a plurality of first indexes, and the first importance of the influence of the ith first index and the jth first index on the second index is characterized by the elements in the ith row and the jth column in the pair comparison matrix. If the element in the ith row and jth column is 3, it means that the ith first indicator is slightly more important than the jth first indicator than the first importance of the effect of the jth first indicator on the second indicator.
Optionally, the first importance of the influence of any two first indexes on the second index may be preset by an expert. For example, the expert presets the creator performance to be slightly more important than the personal reputation than the first importance of the effect of the personal reputation on the creator profile. Thus, the ratio of originator performance to individual reputation in the pairwise comparison matrix is 3.
Alternatively, the first importance of the influence of any two first indicators on the second indicator may be obtained by means of an electronic questionnaire. For example, an electronic questionnaire is set for each second index, wherein the electronic questionnaire is used for ranking the first importance of the second index for the plurality of first indexes; acquiring the voting number (namely the number of the electronic questionnaires) of each first index ranked first according to the collected results of the plurality of electronic questionnaires; and taking the ratio of the voting numbers of the two first indexes ranked first as the first importance of the influence of the two first indexes on the second index. It should be noted that, if the number of votes ranked first by a first index is zero, the importance degree of any other first index is most important compared with the first index, the ratio of any other first index to the first index is the highest value in a scaling method, for example, 1-9 scaling method, and the ratio of any other first index to the first index is 9.
For example, if the number of votes for the first index is 100 and the number of votes for the second first index is 300, the importance of the two first indexes on the second index is 1/3, i.e. the second first index is slightly more important than the first index.
Further, a first maximum feature root of the pair comparison matrix corresponding to each second index is obtained; and acquiring a first feature vector corresponding to the first maximum feature root, and taking each value in the first feature vector as a plurality of weights of a plurality of first indexes relative to each second index.
202: according to the analytic hierarchy process, a plurality of second weights of the plurality of second indicators relative to a third indicator used for determining the quality of the user-generated content are determined.
Wherein the plurality of second indexes correspond to the plurality of second weights one to one.
Similarly, a second importance of the influence of any two second indexes of the plurality of second indexes on the third index can be obtained, wherein the second importance is obtained in a similar manner to the first importance obtained in step 201, and will not be described again. Then, according to the second importance, a pair comparison matrix corresponding to the third index is constructed; acquiring a second maximum characteristic root of the paired comparison matrix corresponding to the third index; and acquiring a second feature vector corresponding to the second maximum feature root, and taking each value in the second feature vector as a plurality of weights of a plurality of second indexes relative to the third index respectively.
203: and acquiring text information of the first user generated content to be processed, and processing the text information to obtain a plurality of characteristic values of the first user generated content to be processed under a plurality of first indexes.
The first to-be-processed user generated content is any one of a plurality of to-be-processed user generated contents.
For example, the text information of the first to-be-processed user generated content may be obtained through a crawler technology, where the text information may be multiple copies, for example, the text information of the creator (i.e., the representation information) may be obtained from a maintained user database for the creator representation dimension; then, carrying out entity identification on the portrait information to obtain the performance of the creator, the honor of the creator, the age of the creator department and the personal honor of the creator; text information (for example, statistical records of the number of browsing people) for content consumption can be acquired from a maintained browsing record database aiming at the content consumption dimension, and then the text information is processed to obtain the click rate, the number of browsing people and the number of praise people; similarly, for the service value dimension, the text information for the service value can be acquired from the maintained browsing record database, and then the text information is processed to obtain the collection times and the output conversion number.
Therefore, by processing the text information, the feature value in each first index can be obtained.
Exemplarily, sentence division processing is performed on the text information to obtain at least one sentence containing each first index; then, extracting keywords of each sentence in at least one sentence to obtain at least one keyword corresponding to each sentence; then, combining each keyword in the at least one keyword with the first index respectively to obtain at least one phrase corresponding to each first index; and finally, acquiring the confusion degree of each phrase in the at least one phrase, and taking the key word in the phrase with the minimum confusion degree as the characteristic value corresponding to each first index, namely taking the key word in the phrase with the most complete semantics as the characteristic value corresponding to each first index.
204: and determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights.
Illustratively, according to the characteristic value under each first index, the score corresponding to each first index is determined. For example, the score under each first index is obtained according to the feature value under each first index and the corresponding relationship between the feature value and the score. Then, the scores under the multiple first indexes are weighted according to the multiple first weights of the multiple first indexes relative to each second index, and the first score under each second index is obtained.
Wherein the correspondence between the characteristic values and the scores can be characterized by table 2:
table 2:
205: and determining the target score of the first user-generated content to be processed according to the plurality of second weights and the score of the first user-generated content to be processed under each second index.
Illustratively, the first score under each second index is weighted according to a plurality of second weights, so as to obtain a target score of the first to-be-processed user-generated content.
206: and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
Exemplarily, the management strategy of the content generated by each user to be processed is determined according to the corresponding relation between the preset target score and the management strategy and the target score of the content generated by each user to be processed; and managing the generated content of each user to be processed according to the management strategy of the generated content of each user to be processed.
For the first to-be-processed user content, if the target score of the first to-be-processed user generated content is greater than a first threshold, the first to-be-processed user generated content is displayed at the top; if the target score of the first to-be-processed user generated content is larger than a second threshold and smaller than a first threshold, adding a recommendation label for the first to-be-processed user generated content, and increasing a weight coefficient during recommendation so that the first to-be-processed user generated content is pushed to a user when the user searches for the user generated content; if the target score of the first to-be-processed user generated content is smaller than the second threshold value and larger than a third threshold value, the first to-be-processed user generated content is reserved, namely, the first to-be-processed user content is not subjected to additional processing; and if the target score of the first to-be-processed user generated content is smaller than a third threshold value, deleting the first to-be-processed user generated content or making sure that the first to-be-processed user generated content cannot be searched when the user performs user generated content searching. The first threshold may be 8 or another value, the second threshold may be 6 or another value, and the third threshold may be 3 or another value. Wherein the first threshold is greater than the second threshold, which is greater than the third threshold.
Wherein the correspondence between the target score and the management policy can be characterized by table 3:
table 3:
target scoring | Managing policies |
[0,3] | Poor quality, adopting a sinking or lowering frame |
(3,6] | General quality, no intervention |
(6,8] | The quality is better, a recommendation label is given, and the weight coefficient in a recommendation algorithm is increased |
(8,10] | High quality and top display |
In an embodiment of the application, for example, the content generated by the multiple users to be processed may be ranked according to the target scores of the content generated by the multiple users to be processed, so as to obtain a ranking result; and finally, displaying the generated contents of the plurality of users to be processed on a visual interface according to the sequencing result.
It can be seen that, in the embodiment of the present application, first, a plurality of first weights of a plurality of first indexes with respect to each second index and a plurality of second weights of a plurality of second indexes with respect to a third index are determined through an analytic hierarchy process; the weight determined by the analytic hierarchy process is not manually set, so that the determined weight precision is higher; and finally, successively weighting and summing the scores corresponding to each first index according to the multiple first weights, the multiple second weights and the scores corresponding to each first index to obtain the target score of the content generated by each user to be processed. Finally, the target score of the content name generated by each user to be processed reflects the quality of the content generated by each user to be processed. Therefore, the generated contents of the plurality of users to be processed are managed according to the target scores of the generated contents of each user to be processed, and a solution is provided for the fine management of the generated contents of the users to be processed.
Referring to fig. 4, fig. 4 is a schematic flowchart of another user-generated content management method according to an embodiment of the present disclosure. The method is applied to the user-generated content management apparatus described above. The same contents in this embodiment as those in the embodiment shown in fig. 2 will not be repeated here. The method of the embodiment comprises the following steps:
401: a plurality of initial indicators associated with each of the second indicators is obtained.
That is, for example, for the second index being the creator profile, the index related to the creator profile may include other indexes such as the creator age and the creator gender in addition to the plurality of first indexes mentioned in the present application, but not all indexes are related to the quality evaluation of the user-generated content, for example, the creator gender is not related to the quality of the user-generated content. The object to be achieved by the present embodiment is to screen out candidate indicators related to the quality evaluation of the user-generated content from all the initial indicators related to each of the second indicators.
402: a plurality of training samples are obtained, wherein each training sample generates content for a historical user with a known score that has been labeled.
The generated content of each historical user is scored in a manual marking mode, and the plurality of training samples are obtained.
403: and (4) normalizing the data of each training sample under each initial index to obtain the standard data of each training sample under each initial index.
For example, for a first training sample, a ranking of data of the first training sample under each initial index in the plurality of training samples is obtained, and then normalized data of the first training sample under each initial index is determined according to the ranking of the data of the first training sample under each initial index in the plurality of training samples, wherein the first training sample is any one of the plurality of training samples. For example, the normalized data of the first training sample under each initial metric can be represented by equation (1):
wherein S isAiNormalized data of the first training sample at an i-th initial index of the plurality of initial indexes, N is the number of the plurality of training samples, and rank (ai) is a ranking of the data of the first training sample at the i-th initial index among the N training samples.
404: and standardizing the scores marked by each training sample to obtain the standardized score of each training sample.
Similarly, the score corresponding to each training sample is also normalized to obtain a normalized score of the score of each training sample, wherein the manner of obtaining the normalized score is similar to the manner of obtaining the labeled data, that is, the ranking of the score of each training sample among a plurality of training samples is obtained, and no description is given.
405: and taking the standardized score of each training sample as a label, gradually introducing each initial index through a stepwise regression method, and determining a plurality of candidate indexes which have significance on the quality score of the user-generated content in the plurality of initial indexes through standard data of each training sample under each initial index.
Exemplarily, regarding each training sample, taking the normalized score of each training sample as a label, gradually introducing each initial index through a stepwise regression method, and determining a plurality of initial candidate indexes having significant effects on the quality score of the user-generated content in the training using the training sample according to the standard data of each training sample under the initial index; and finally, voting and selecting a plurality of initial candidate indexes with significant influence corresponding to each training sample based on a voting principle to obtain a plurality of candidate indexes corresponding to each second index, wherein the plurality of candidate indexes corresponding to each second index are parts of the plurality of first indexes.
406: and combining the multiple candidate indexes corresponding to each second index to obtain multiple first indexes.
407: according to the analytic hierarchy process, a plurality of first weights of the first indexes relative to each second index are determined.
408: according to the analytic hierarchy process, a plurality of second weights of the plurality of second indicators relative to a third indicator used for determining the quality of the user-generated content are determined.
409: and acquiring text information of the first user-generated content to be processed, and processing the text information to obtain a plurality of characteristic values of the first user-generated content to be processed under a plurality of first indexes.
410: and determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights.
411: and determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index.
412: and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
It can be seen that, in the embodiment of the present application, first indexes related to quality evaluation of user-generated content are screened out from all indexes by a stepwise regression method, and since the first indexes are all indexes related to quality evaluation, accuracy of subsequent scoring is improved; then determining the weight of the plurality of first indexes relative to each second index and the weight of the plurality of second indexes relative to the third index by an analytic hierarchy process; the determined weight is determined by an analytic hierarchy process instead of the manually set weight, so that the determined weight has higher precision; and then, determining a score corresponding to each first index based on a preset score table and the characteristic value under each first index, and finally, weighting and summing successively according to the weight and the weight corresponding to each first index to obtain a target score of the content generated by each user to be processed. Finally, the target score of the content name generated by each user to be processed reflects the quality of the content generated by each user to be processed, and the generated content of a plurality of users to be processed is managed according to the target score of the content generated by each user to be processed, so that a solution is provided for the fine management of the generated content of the users to be processed.
Referring to fig. 5, fig. 5 is a block diagram illustrating functional units of a user-generated content management apparatus according to an embodiment of the present application. The user-generated content management apparatus 500 includes: an acquisition unit 501 and a processing unit 502;
a processing unit 502, configured to determine, according to an analytic hierarchy process, a plurality of first weights of a plurality of first indicators respectively corresponding to each second indicator, where the plurality of first indicators correspond to the plurality of first weights one to one, the plurality of first indicators are used to determine basic information of user-generated content, each second indicator is composed of a part of the first indicators, and the part of the first indicators corresponding to any two of the second indicators is completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
an obtaining unit 501, configured to obtain text information of a first user-generated content to be processed;
the processing unit 502 is further configured to process the text information to obtain a plurality of feature values of the first to-be-processed user generated content under the plurality of first indexes, where the first to-be-processed user generated content is any one of a plurality of to-be-processed user generated contents;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
In an embodiment of the application, in determining a plurality of first weights of a plurality of first indicators with respect to each second indicator respectively according to an analytic hierarchy process, the processing unit 502 is specifically configured to:
acquiring first importance of influence of any two first indexes on each second index;
constructing a pair comparison matrix corresponding to each second index according to the first importance;
acquiring a first maximum feature root of the paired comparison matrix corresponding to each second index;
and acquiring a first feature vector corresponding to the first maximum feature root, and taking each value in the first feature vector as the plurality of first weights.
In an embodiment of the application, in processing the text information to obtain a plurality of feature values of the first to-be-processed user generated content under the plurality of first indexes, the processing unit 502 is specifically configured to:
sentence division processing is carried out on the text information to obtain at least one sentence containing each first index;
extracting keywords of each sentence in the at least one sentence to obtain at least one keyword corresponding to each sentence;
combining each keyword in the at least one keyword with each first index to obtain at least one phrase;
and acquiring the confusion degree of each phrase in the at least one phrase, and taking the keyword in the phrase with the minimum confusion degree as the characteristic value of each first index.
In an embodiment of the application, before determining the first weights of the first indexes relative to the second indexes according to the analytic hierarchy process, the processing unit 502 is further configured to:
acquiring a plurality of initial indexes related to each second index;
obtaining a plurality of training samples, wherein each training sample generates content for the labeled historical users with known scores;
standardizing data of each training sample under each initial index to obtain standard data of each training sample under each initial index;
standardizing the scores marked by each training sample to obtain the standardized scores of each training sample;
gradually introducing each initial index and standard data of each training sample under each initial index by using the standardized score of each training sample as a label through a stepwise regression method, and determining a plurality of candidate indexes which have significance on the quality score of the user-generated content in the plurality of initial indexes;
and combining the multiple candidate indexes corresponding to each second index to obtain the multiple first indexes.
In an embodiment of the application, in terms of normalizing data of each training sample under each initial indicator to obtain standard data of each training sample under each initial indicator, the processing unit 502 is specifically configured to:
for a first training sample, obtaining the ranking of the data of the first training sample under each initial index in the plurality of training samples, wherein the first training sample is any one of the plurality of training samples;
according to the ranking, determining standardized data of the first training sample under each initial index; wherein the normalized data satisfies the following formula:
wherein S isAiNormalized data of the first training sample at an i-th initial index of the plurality of initial indexes, N is the number of the plurality of training samples, and rank (ai) is a ranking of the data of the first training sample at the i-th initial index among the N training samples.
In an embodiment of the application, in terms of managing the multiple user-generated contents according to the score of each user-generated content in the multiple user-generated contents, the processing unit 502 is specifically configured to:
if the target score of the first user-generated content to be processed is larger than a first threshold value, performing top display on the first user-generated content to be processed;
if the target score of the first user-to-be-processed generated content is larger than a second threshold and smaller than the first threshold, adding a recommendation label to the first user-to-be-processed generated content;
if the target score of the first user-generated content to be processed is smaller than the second threshold value and larger than a third threshold value, retaining the first user-generated content to be processed;
if the target score of the first user-generated content to be processed is smaller than the third threshold, the first user-generated content to be processed is set down or sunk;
wherein the first threshold is greater than the second threshold, which is greater than the third threshold.
In one embodiment of the present application, the plurality of first indicators include creator performance, creator department age, creator personal reputation, click rate, number of browsing people, number of praise people, number of collection times, and number of order conversions of the user-generated content;
the plurality of second indicators include an originator representation of the user-generated content, content consumption, and a business value;
the third indicator includes a target score for the user-generated content.
Referring to fig. 6, fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the electronic device 600 includes a transceiver 601, a processor 602, and a memory 603. Connected to each other by a bus 604. The memory 603 is used to store computer programs and data, and can transfer data stored in the memory 603 to the processor 602.
The processor 602 is configured to read the computer program in the memory 603 to perform the following operations:
determining a plurality of first weights of a plurality of first indexes relative to each second index respectively according to an analytic hierarchy process, wherein the plurality of first indexes correspond to the plurality of first weights one to one, the plurality of first indexes are used for determining basic information of user-generated content, each second index is composed of a part of the first indexes, and the part of the first indexes corresponding to any two second indexes is completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
controlling the transceiver 601 to obtain text information of the first user-generated content to be processed;
processing the text information to obtain a plurality of characteristic values of the first to-be-processed user generated content under the plurality of first indexes, wherein the first to-be-processed user generated content is any one of the plurality of to-be-processed user generated contents;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
In an embodiment of the application, the processor 602 is specifically configured to perform the following steps in determining a plurality of first weights of a plurality of first indicators with respect to each second indicator according to an analytic hierarchy process:
acquiring first importance of influence of any two first indexes on each second index;
constructing a pair comparison matrix corresponding to each second index according to the first importance;
acquiring a first maximum characteristic root of the paired comparison matrix corresponding to each second index;
and acquiring a first feature vector corresponding to the first maximum feature root, and taking each value in the first feature vector as the plurality of first weights.
In an embodiment of the application, in processing the text information to obtain a plurality of feature values of the first to-be-processed user generated content under the plurality of first indexes, the processor 602 is specifically configured to perform the following steps:
sentence division processing is carried out on the text information to obtain at least one sentence containing each first index;
extracting keywords of each sentence in the at least one sentence to obtain at least one keyword corresponding to each sentence;
combining each keyword in the at least one keyword with each first index to obtain at least one phrase;
and acquiring the confusion degree of each phrase in the at least one phrase, and taking the keyword in the phrase with the minimum confusion degree as the characteristic value of each first index.
In an embodiment of the application, before determining the first weights of the first indexes relative to the second indexes according to the analytic hierarchy process, the processor 602 is further configured to:
acquiring a plurality of initial indexes related to each second index;
acquiring a plurality of training samples, wherein each training sample generates content for the labeled historical users with known scores;
standardizing data of each training sample under each initial index to obtain standard data of each training sample under each initial index;
standardizing the scores marked by each training sample to obtain the standardized score of each training sample;
taking the standardized score of each training sample as a label, gradually introducing each initial index through a stepwise regression method, and determining a plurality of candidate indexes which have significance on the quality score of the user-generated content in the plurality of initial indexes according to standard data of each training sample under each initial index;
and combining the plurality of candidate indexes corresponding to each second index to obtain the plurality of first indexes.
In an embodiment of the present application, in normalizing the data of each training sample under each initial indicator to obtain the standard data of each training sample under each initial indicator, the processor 602 is specifically configured to perform the following steps:
for a first training sample, obtaining the ranking of the data of the first training sample under each initial index in the plurality of training samples, wherein the first training sample is any one of the plurality of training samples;
according to the ranking, determining standardized data of the first training sample under each initial index; wherein the normalized data satisfies the following formula:
wherein S isAiNormalized data of the first training sample at an i-th initial index of the plurality of initial indexes, N is the number of the plurality of training samples, and rank (ai) is a ranking of the data of the first training sample at the i-th initial index among the N training samples.
In an embodiment of the present application, in managing the plurality of user-generated contents according to the score of each of the plurality of user-generated contents, the processor 602 is specifically configured to perform the following steps:
if the target score of the first user-generated content to be processed is larger than a first threshold value, performing top display on the first user-generated content to be processed;
if the target score of the first user-to-be-processed generated content is larger than a second threshold and smaller than the first threshold, adding a recommendation label to the first user-to-be-processed generated content;
if the target score of the first user-generated content to be processed is smaller than the second threshold value and larger than a third threshold value, retaining the first user-generated content to be processed;
if the target score of the first user-generated content to be processed is smaller than the third threshold, the first user-generated content to be processed is set down or sunk;
wherein the first threshold is greater than the second threshold, which is greater than the third threshold.
In one embodiment of the application, the plurality of first indicators comprise the performance of the creators, the company department age, the personal reputation of the creators, the click rate, the number of browsing people, the number of praise people, the collection times and the number of the order-making conversion of the user-generated content;
the plurality of second indicators include an originator representation of the user-generated content, content consumption, and a business value;
the third indicator includes a target score for the user-generated content.
Specifically, the transceiver 601 may be the obtaining unit 501 of the user generated content management apparatus 500 in the embodiment shown in fig. 5, and the processor 602 may be the processing unit 502 of the user generated content management apparatus 500 in the embodiment shown in fig. 5.
It should be understood that the electronic device in the present application may include a smart Phone (e.g., an Android Phone, an iOS Phone, a Windows Phone, etc.), a tablet computer, a palm computer, a notebook computer, a Mobile Internet device MID (MID), a wearable device, or the like. The above mentioned electronic devices are only examples, not exhaustive, and include but not limited to the above mentioned electronic devices. In practical applications, the electronic device may further include: intelligent vehicle-mounted terminal, computer equipment and the like.
Embodiments of the present application further provide a computer-readable storage medium, which stores a computer program, where the computer program is executed by a processor to implement part or all of the steps of any one of the user-generated content management methods described in the above method embodiments.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the user-generated content management methods as recited in the above method embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or may be implemented in the form of a software program module.
The integrated units, if implemented in the form of software program modules and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solutions of the present application, in essence or part of the technical solutions contributing to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product, which is stored in a memory and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept 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. A method for managing user-generated content, comprising:
determining a plurality of first weights of a plurality of first indexes relative to each second index respectively according to an analytic hierarchy process, wherein the plurality of first indexes correspond to the plurality of first weights one to one, the plurality of first indexes are used for determining basic information of user-generated content, each second index is composed of a part of the first indexes, and the part of the first indexes corresponding to any two second indexes is completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
acquiring text information of first to-be-processed user generated content, and processing the text information to obtain a plurality of characteristic values of the first to-be-processed user generated content under the plurality of first indexes, wherein the first to-be-processed user generated content is any one of the plurality of to-be-processed user generated content;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
2. The method of claim 1, wherein determining a plurality of first weights for a plurality of first indicators relative to each second indicator according to a hierarchal analysis comprises:
acquiring first importance of influence of any two first indexes on each second index;
constructing a pair comparison matrix corresponding to each second index according to the first importance;
acquiring a first maximum feature root of the paired comparison matrix corresponding to each second index;
and acquiring a first feature vector corresponding to the first maximum feature root, and taking each value in the first feature vector as the plurality of first weights.
3. The method according to claim 1 or 2, wherein the processing the text message to obtain a plurality of feature values of the first to-be-processed user-generated content under the plurality of first indicators includes:
sentence division processing is carried out on the text information to obtain at least one sentence containing each first index;
extracting keywords of each sentence in the at least one sentence to obtain at least one keyword corresponding to each sentence;
combining each keyword in the at least one keyword with each first index to obtain at least one phrase;
and acquiring the confusion degree of each phrase in the at least one phrase, and taking the keyword in the phrase with the minimum confusion degree as the characteristic value of each first index.
4. The method of claim 1, wherein prior to determining the plurality of first weights for the plurality of first indicators relative to each of the second indicators according to an analytic hierarchy process, the method further comprises:
acquiring a plurality of initial indexes related to each second index;
obtaining a plurality of training samples, wherein each training sample generates content for the labeled historical users with known scores;
standardizing data of each training sample under each initial index to obtain standard data of each training sample under each initial index;
standardizing the scores marked by each training sample to obtain the standardized score of each training sample;
taking the standardized score of each training sample as a label, gradually introducing each initial index through a stepwise regression method, and determining a plurality of candidate indexes which have significance on the quality score of the user-generated content in the plurality of initial indexes according to standard data of each training sample under each initial index;
and combining the plurality of candidate indexes corresponding to each second index to obtain the plurality of first indexes.
5. The method of claim 4, wherein the normalizing the data of each training sample under each initial index to obtain the standard data of each training sample under each initial index comprises:
for a first training sample, obtaining the ranking of the data of the first training sample under each initial index in the plurality of training samples, wherein the first training sample is any one of the plurality of training samples;
according to the ranking, determining standardized data of the first training sample under each initial index; wherein the normalized data satisfies the following formula:
wherein S isAiNormalized data of the first training sample at an i-th initial index of the plurality of initial indexes, N is the number of the plurality of training samples, and rank (ai) is a ranking of the data of the first training sample at the i-th initial index among the N training samples.
6. The method of claim 1, wherein managing the plurality of user-generated content based on the rating score for each of the plurality of user-generated content comprises:
if the target score of the first user-generated content to be processed is larger than a first threshold value, performing top display on the first user-generated content to be processed;
if the target score of the first user-to-be-processed generated content is larger than a second threshold and smaller than the first threshold, adding a recommendation label to the first user-to-be-processed generated content;
if the target score of the first user-generated content to be processed is smaller than the second threshold value and larger than a third threshold value, retaining the first user-generated content to be processed;
if the target score of the first user-generated content to be processed is smaller than the third threshold, the first user-generated content to be processed is set down or sunk;
wherein the first threshold is greater than the second threshold, which is greater than the third threshold.
7. The method of claim 1,
the plurality of first indexes comprise creator performance, creator department age, creator personal honor, click rate, browsing number, praise number, collection times and output conversion number of the user generated content;
the plurality of second indicators include an originator representation of the user-generated content, content consumption, and a business value;
the third indicator includes a target score for the user-generated content.
8. A user-generated content management apparatus, comprising: an acquisition unit and a processing unit;
the processing unit is used for determining a plurality of first weights of a plurality of first indexes relative to each second index respectively according to an analytic hierarchy process, wherein the plurality of first indexes correspond to the plurality of first weights one by one, the plurality of first indexes are used for determining basic information of user-generated content, each second index is composed of a part of the first indexes, and the parts of the first indexes corresponding to any two second indexes are completely different;
determining a plurality of second weights of a plurality of second indexes relative to a third index according to the analytic hierarchy process, wherein the plurality of second indexes correspond to the plurality of second weights in a one-to-one mode, and the third index is used for determining the quality of the user-generated content;
the acquiring unit is used for acquiring text information of the first user-generated content to be processed;
the processing unit is further configured to process the text information to obtain a plurality of feature values of the first to-be-processed user generated content under the plurality of first indexes, where the first to-be-processed user generated content is any one of the plurality of to-be-processed user generated contents;
determining a first score of the first to-be-processed user generated content under each second index according to the plurality of characteristic values and the plurality of first weights;
determining a target score of the first to-be-processed user generated content according to the plurality of second weights and the first score under each second index;
and managing the generated contents of the plurality of users to be processed according to the target scores of the generated contents of each user to be processed in the generated contents of the plurality of users to be processed.
9. An electronic device, comprising: a processor coupled to the memory, and a memory for storing a computer program, the processor being configured to execute the computer program stored in the memory to cause the electronic device to perform the method of any of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which is executed by a processor to implement the method according to any one of claims 1-7.
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