CN109961304B - Method and apparatus for generating information - Google Patents
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Abstract
The embodiment of the application discloses a method and a device for generating information. One embodiment of the method comprises: acquiring first attribute data of a first attribute of a target object, a user attention data set and second attribute data of a second attribute, wherein the first attribute data comprise an initial value of a first attribute value, a first attribute coefficient is used for representing the attention degree of a user to the first attribute, the second attribute data comprise an initial value of a second attribute value, and the first attribute is positively correlated with the second attribute; determining a first attribute coefficient of a first attribute based on the user attention data set; the first attribute value and the second attribute value are generated based on the first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value. The embodiment improves the accuracy of information generation.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to the technical field of internet, and particularly relates to a method and a device for generating information.
Background
Currently, for newly produced items, it is often necessary to determine certain attribute information (e.g., sales information, price information, etc.) of the newly produced items before they are put into the market (or for a preset number of items already put into the market before they are put into the market again). In the prior art, for the attribute information to be determined, the related technical personnel often make a direct prediction through other attribute information (such as inventory information, quality information and the like) of the article.
Disclosure of Invention
The embodiment of the application provides a method and a device for generating information.
In a first aspect, an embodiment of the present application provides a method for generating information, where the method includes: acquiring first attribute data of a first attribute of a target object, a user attention data set and second attribute data of a second attribute, wherein the first attribute data comprise an initial value of a first attribute value of the first attribute, a first attribute coefficient is used for representing the attention degree of a user to the first attribute, the second attribute data comprise an initial value of a second attribute value of the second attribute, and the first attribute is positively correlated with the second attribute; determining a first attribute coefficient of a first attribute based on the user attention data set; generating a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
In some embodiments, generating a first attribute value for the first attribute and a second attribute value for the second attribute comprises: and generating a first attribute value of the first attribute and a second attribute value of the second attribute through a dynamic programming algorithm.
In some embodiments, the first attribute comprises at least two first sub-attributes; and determining a first attribute coefficient of the first attribute based on the user attention data set, including: for each first sub-attribute of the at least two first sub-attributes, determining a first sub-attribute coefficient of the first sub-attribute by performing data analysis on a user attention data set, wherein the first sub-attribute coefficient is used for representing the attention degree of a user to the first sub-attribute; acquiring a weight pre-allocated to each of at least two first sub-attributes; according to the obtained weight, carrying out weighted summation processing on the determined first sub-attribute coefficient to generate a weighted summation value; the weighted sum is determined as a first property coefficient of the first property.
In some embodiments, generating a second attribute value for the second attribute based on the determined first attribute coefficient, the first attribute value, and the initial value comprises: determining whether the first attribute coefficient is larger than a preset first attribute coefficient threshold value; in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value, a first attribute value of the first attribute and a second attribute value of the second attribute are generated based on the first attribute coefficient, an initial value of the first attribute value, and an initial value of the second attribute value.
In a second aspect, the present application provides an apparatus for generating information, the apparatus comprising: the system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is configured to acquire first attribute data of a first attribute of a target object, a user attention data set and second attribute data of a second attribute, the first attribute data comprise an initial value of a first attribute value of the first attribute, a first attribute coefficient is used for representing the attention degree of a user to the first attribute, the second attribute data comprise an initial value of a second attribute value of the second attribute, and the first attribute is positively correlated with the second attribute; a determining unit configured to determine a first attribute coefficient of a first attribute based on the user attention data set; a generating unit configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
In some embodiments, the generating unit comprises: the first generation module is configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute through a dynamic programming algorithm.
In some embodiments, the first attribute comprises at least two first sub-attributes; and the determination unit includes: the third determining module is configured to determine, for each first sub-attribute of the at least two first sub-attributes, a first sub-attribute coefficient of the first sub-attribute by performing data analysis on the user attention data set, where the first sub-attribute coefficient is used to characterize the user attention to the first sub-attribute; the acquisition module is configured to acquire a weight pre-allocated to each of the at least two first sub-attributes; the processing module is configured to perform weighted summation processing on the determined first sub-attribute coefficient according to the obtained weight to generate a weighted summation value; a fourth determination module configured to determine the weighted sum as a first property coefficient of the first property.
In some embodiments, the generating unit comprises: a fifth determining module configured to determine whether the first attribute coefficient is greater than a preset first attribute coefficient threshold; and the second generation module is configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the first attribute coefficient, the initial value of the first attribute value and the initial value of the second attribute value in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value.
In a third aspect, an embodiment of the present application provides a server, including: one or more processors; a storage device for storing one or more programs which, when executed by one or more processors, cause the one or more processors to implement the method of any of the embodiments of the method for generating information described above.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the method of any of the above-described methods for generating information.
According to the method and the device for generating information, the first attribute data of the first attribute of the target object, the user attention data set and the second attribute data of the second attribute are obtained, wherein the first attribute data comprise the first attribute value of the first attribute, the first attribute coefficient is used for representing the attention degree of the user to the first attribute, the second attribute data comprise the initial value of the second attribute, the first attribute is positively correlated with the second attribute, then the first attribute coefficient of the first attribute is determined based on the user attention data set, and finally the second attribute value of the second attribute is generated based on the determined first attribute coefficient, the determined first attribute value and the determined initial value. In the process, the first attribute coefficient of the first attribute is determined through the user attention data of the first attribute, and the first attribute value of the first attribute and the second attribute value of the second attribute are generated based on the first attribute coefficient, so that the user attention data of the attribute of the article are effectively utilized, and the accuracy of information generation is improved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of a method for generating information according to the present application;
FIG. 3 is a schematic illustration of an application scenario of a method for generating information according to the present application;
FIG. 4 is a flow diagram of yet another embodiment of a method for generating information according to the present application;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for generating information according to the present application;
FIG. 6 is a schematic block diagram of a computer system suitable for use in implementing a server according to embodiments of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 shows an exemplary system architecture 100 to which embodiments of the method for generating information or the apparatus for generating information of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have various communication client applications installed thereon, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.
The terminal devices 101, 102, 103 may be various electronic devices, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, mpeg compression standard Audio Layer 3), MP4 players (Moving Picture Experts Group Audio Layer IV, mpeg compression standard Audio Layer 4), laptop and desktop computers, and the like.
The server 105 may be a server that provides various services, such as a data processing server that processes attribute data transmitted by the terminal apparatuses 101, 102, 103. The data processing server may perform processing such as analysis on the received attribute data, attribute coefficient data, and the like, and feed back a processing result (for example, attribute information) to the terminal device.
It should be noted that the method for generating information provided in the embodiment of the present application is generally performed by the server 105, and accordingly, the apparatus for generating information is generally disposed in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for generating information in accordance with the present application is shown. The method for generating information comprises the following steps:
In this embodiment, an electronic device (for example, a server shown in fig. 1) on which the method for generating information operates may obtain, through a wired connection manner or a wireless connection manner, first attribute data of a first attribute, a user attention data set, and second attribute data of a second attribute of a target item, where the target item may be an item corresponding to data sent by a client (for example, a terminal device shown in fig. 1) or an item corresponding to data stored in advance on the electronic device.
In this embodiment, the first attribute of the target item may be used to characterize a property of the target item. As an example, the target item may be brand a apparel and the first attribute may be an attribute of greater interest to the user for the brand a apparel (e.g., price, quality, etc.). The first attribute data may be data transmitted by a client (for example, the terminal device shown in fig. 1) or data stored in advance on the electronic device. The first attribute data may include an initial value of a first attribute value of the first attribute. The first attribute value may be a value to be determined for characterizing the level, quality, length, etc. of the first attribute. The initial value of the first attribute value may be a determined value used to determine the value of the second attribute. For example, the first attribute may be mass, the value of the first attribute may be a mass value of the target object in the third quarter, and the initial value of the first attribute may be a mass value of the target object in the second quarter, wherein the greater the mass value, the better the mass. The user attention data set may be a data set sent by a client (e.g., a terminal device shown in fig. 1), or a data set obtained by the electronic device based on a big data technology. It should be noted that the big data technology is a well-known technology widely studied and applied at present, and is not described herein again. The user attention data set may be used to determine a first attribute coefficient for the first attribute. The first attribute coefficient may be used to characterize the degree of user attention to the first attribute, e.g., a larger value of the first attribute coefficient characterizes a larger attention of the user to the first attribute.
In this embodiment, the second attribute of the target item may be used to characterize a property of the target item. The second attribute data may be data transmitted by a client (for example, the terminal device shown in fig. 1) or data stored in advance on the electronic device. The second attribute data may include an initial value of a second attribute value of the second attribute. The second attribute value may be a value to be determined for characterizing the level, quality, length, etc. of the second attribute. The initial value of the second attribute value may be a determined value used to determine the value of the second attribute. For example, the second attribute may be a price, the value of the second attribute may be a price value of the target item for the third quarter, and the initial value of the second attribute may be a price value of the target item for the second quarter, wherein the larger the price value, the higher the price.
In this embodiment, if the first attribute of the target item is positively correlated with the second attribute, the correlation coefficient between the first attribute and the second attribute of the target item is positive, that is, the larger the first attribute value of the first attribute of the target item is, the larger the second attribute value of the second attribute is. For example, the first attribute of the target item is quality and the second attribute is price, and generally, the greater the quality value (i.e., the better the quality), the higher the cost required to produce the target item, and the greater the price value (i.e., the higher the price) of the target item.
In this embodiment, based on the user attention data set obtained in step 201, the electronic device (for example, the server shown in fig. 1) may determine a first attribute coefficient of the first attribute based on the user attention data set.
For example, the electronic device may first determine a mean value of the user attention data set, and then determine the determined mean value as a first attribute coefficient of the first attribute. For example, if the user attention data set is "0.4, 0.7, 0.5", the first attribute coefficient is (0.4+0.7+0.5)/3 is 0.53 (two decimal places are reserved).
In some optional implementations of this embodiment, the electronic device may determine the first attribute coefficient of the first attribute by: firstly, the electronic equipment can compare the values included in the user attention data set and determine the maximum value and the minimum value in the values included in the user attention data set; then, the electronic device may delete the maximum value and the minimum value of the values included in the user attention data set, and generate a user attention data set after deleting the maximum value; finally, the electronic device may perform an average calculation on the numerical values included in the user attention data set after the deletion of the maximum value, and determine the calculated average as a first attribute coefficient of the first attribute.
Illustratively, the user attention data set is "0.4; 0.7; 0.5; 0.8". Firstly, the electronic equipment can compare a user attention data set of '0.4'; 0.7; 0.5; 0.8 "includes values of" 0.4 "," 0.7 "," 0.5 "and" 0.8 ", and the maximum value is determined to be" 0.8 ", and the minimum value is determined to be" 0.4 "; then, the electronic device may delete the user attention data set "0.4; 0.7; 0.5; 0.8 ", and generating a user attention data set" 0.7 "from which the latest value is deleted, wherein the maximum value" 0.8 "and the minimum value" 0.4 "are included in the numerical values; 0.5 ", finally, the electronic device may delete the user attention data set" 0.7 "after the latest value is deleted; the values included in 0.5 "are subjected to a mean value calculation, i.e., (0.7+0.5)/2 ═ 0.6, and the calculated mean value" 0.6 "is determined as the first attribute coefficient of the first attribute.
In some optional implementations of this embodiment, the first attribute may include at least two first sub-attributes; and the electronic device may determine, based on the user attention data set, a first attribute coefficient of the first attribute by: firstly, for each first sub-attribute in at least two first sub-attributes, determining a first sub-attribute coefficient of the first sub-attribute by performing data analysis on a user attention data set, wherein the first sub-attribute coefficient is used for representing the attention degree of a user to the first sub-attribute; then, acquiring a weight pre-distributed to each first sub-attribute in at least two first sub-attributes; then according to the obtained weight, carrying out weighted summation processing on the determined first sub-attribute coefficient to generate a weighted summation value; finally, the weighted sum is determined as a first attribute coefficient of the first attribute.
Illustratively, the target item is brand a apparel and the first attribute is mass, the first attribute mass may include two first sub-attributes, respectively, pilling note and abrasion resistance. Here, the electronic apparatus may first acquire a user attention data set "0.4 (pilling note: 0.3, abrasion resistance: 0.1); 0.5 (pilling note: 0.2, abrasion resistance: 0.3) ". Then, the electronic device may sum and average values corresponding to the pilling note percentage, that is, (0.3+0.2)/2 is 0.25, and determine the obtained average value "0.25" as the first sub-attribute coefficient of the first sub-attribute pilling note percentage; similarly, the electronic device may sum and average values corresponding to the wear resistance, that is, (0.1+0.3)/2 is 0.2, and determine the obtained average value "0.2" as the first sub-attribute coefficient of the first sub-attribute wear resistance; the electronic device described above may then obtain the weights "0.4" and "0.6" pre-assigned for pilling note and abrasion resistance; then, according to the obtained weights, the electronic device may perform weighted summation processing on the determined first sub-attribute coefficients of the pilling note and the wear resistance, so as to generate a weighted summation value, that is, 0.4 × 0.25+0.6 × 0.2 — 0.22; finally, the weighted sum value "0.22" is determined as the first attribute coefficient of the first attribute quality.
Optionally, the electronic device may further preset a weight threshold of the first sub-attribute, and further determine, for each first sub-attribute of the at least two first sub-attributes, whether the obtained weight pre-assigned to the first sub-attribute is smaller than the weight threshold, and update the weight of the first sub-attribute to 0 in response to determining that the obtained weight pre-assigned to the first sub-attribute is smaller than the weight threshold.
In this embodiment, the electronic device may generate the first attribute value of the first attribute and the second attribute value of the second attribute based on the first attribute coefficient obtained in step 202 and the initial value of the first attribute value and the initial value of the second attribute value obtained in step 201.
Illustratively, the target item is brand a clothing, the first attribute is quality, the initial value of the quality value is "6", the coefficient of the first attribute determined based on step 202 is "0.53", the second attribute is price, and the initial value of the price value is "99". Depending on the level of the quality-price correlation of brand a apparel, the technician may preset a quality-price correlation coefficient, for example, a quality-price correlation coefficient of "0.6". Combining the known information, the electronic device may first determine a product of the initial value "6" of the quality value and the first attribute coefficient "0.53", sum the determined product and the initial value "6" of the quality value to obtain a sum value, and determine the sum value as the quality value (first attribute value), that is, the quality value is 6+0.53 × 6 or 9.18; next, the electronic device may determine the percentage of increase of the quality value "9.18" with respect to the initial value of the quality value "6", multiply the percentage by the correlation coefficient "0.6", determine the product as the percentage of increase of the price value with respect to the initial value of the price value "99", that is, [ (9.18-6)/6 × 0.6] -% 100 [ [ (price value-99)/99 ] - ] 100%, and determine the price value as "130" (the result remains an integer).
In some optional implementation manners of this embodiment, the electronic device may generate, by using a dynamic programming algorithm, a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value. Dynamic programming (Dynamic programming) is a branch of operations research and is a mathematical method for solving the optimization of Decision process (Decision process). Specifically, the electronic device may first determine an initial value of the first attribute value and an initial value of the second attribute value as a numerical value of the first attribute and a numerical value of the second attribute in the history stage, and determine the first attribute value of the first attribute and the second attribute value of the second attribute as a numerical value of the first attribute and a numerical value of the second attribute in the future stage; then, the electronic device may establish a dynamic programming model based on the determined first attribute coefficient, the value of the first attribute in the history phase (the initial value of the first attribute value), and the value of the second attribute in the history phase (the initial value of the second attribute value), and generate an optimal solution of the value of the first attribute and an optimal solution of the value of the second attribute in a future phase; and finally, determining the generated optimal solution of the numerical value of the first attribute as a first attribute value, and determining the optimal solution of the numerical value of the second attribute as a second attribute value. It should be noted that the dynamic programming algorithm is a well-known technology widely used and studied at present, and is not described herein again.
Optionally, the electronic device may generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value, and push the generated first attribute value of the first attribute and the generated second attribute value of the second attribute to a client (for example, a terminal device shown in fig. 1).
With continued reference to fig. 3, fig. 3 is a schematic diagram of an application scenario of the method for generating information according to the present embodiment. In the application scenario of fig. 3, the server 301 may first obtain quality data 303 of a first attribute quality, a quality coefficient data set 304, and price data 305 of a second attribute price of the brand a garment, where the quality data 303 includes an initial value "6" of a quality value, such as reference numeral 3031, the quality coefficient data set 304 is used to determine a quality coefficient 306 of the quality, the quality coefficient 306 is used to characterize the attention degree of the user to the quality, the price data 305 includes an initial value "99" of a price value, such as reference numeral 3051, and the quality is positively correlated with the price; server 301 may then determine a quality coefficient for the quality, as indicated by reference numeral 306, based on quality coefficient data set 304; finally, the server 301 may generate the quality value 307 and the price value 308 based on the quality coefficient 306, the initial value of the quality value 3031, and the initial value of the price value 3051.
The method provided by the above embodiment of the application improves the accuracy of information generation by acquiring first attribute data of a first attribute of a target item, a user attention data set, and second attribute data of a second attribute, where the first attribute data includes an initial value of a first attribute value of the first attribute, a first attribute coefficient is used to characterize the attention degree of a user to the first attribute, and the second attribute data includes an initial value of a second attribute value of the second attribute, the first attribute is positively correlated with the second attribute, then determining a first attribute coefficient of the first attribute based on the user attention data set, and finally generating the first attribute value of the first attribute and the second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
With further reference to fig. 4, a flow 400 of yet another embodiment of a method for generating information is shown. The flow 400 of the method for generating information comprises the steps of:
In this embodiment, step 401 is substantially the same as step 201 in the corresponding embodiment of fig. 2, and is not described here again.
In this embodiment, step 402 is substantially the same as step 202 in the corresponding embodiment of fig. 2, and is not described herein again.
In this embodiment, based on the first attribute coefficient obtained in step 402, the electronic device may determine whether the first attribute coefficient is greater than a preset first attribute coefficient threshold.
In response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value, a first attribute value of the first attribute and a second attribute value of the second attribute are generated based on the first attribute coefficient, an initial value of the first attribute value and an initial value of the second attribute value, step 404.
In this embodiment, the electronic device may generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the first attribute coefficient, an initial value of the first attribute value, and an initial value of the second attribute value in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value.
For example, based on step 402, the electronic device may determine that the quality coefficient (first attribute coefficient) of the brand a garment is 0.53 and the preset quality index threshold (first attribute coefficient threshold) is 0.2, the electronic device may determine that "0.53" is greater than "0.2" based on step 403, and in response to determining that "0.53" is greater than "0.2", the electronic device may generate a quality value of the quality and a price value of the price (second attribute) based on the quality coefficient, the initial value of the quality value, and the initial value of the price (second attribute value).
It should be noted that the steps of generating the first attribute value of the first attribute and the second attribute value of the second attribute based on the first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value, and generating and outputting the attribute information including the first attribute value and the second attribute value are substantially the same as step 203 in the corresponding embodiment of fig. 2, and are not repeated here.
As can be seen from fig. 4, compared with the embodiment corresponding to fig. 2, the flow 400 of the method for generating information in the present embodiment highlights the step of determining whether the first attribute coefficient is greater than the preset first attribute coefficient threshold. Therefore, the scheme described in the embodiment can avoid the generation of the information when the first attribute coefficient is too small, thereby saving resources and improving the effectiveness of information generation.
With further reference to fig. 5, as an implementation of the method shown in the above figures, the present application provides an embodiment of an apparatus for generating information, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to various electronic devices.
As shown in fig. 5, the apparatus 500 for generating information of the present embodiment may include: an obtaining unit 501, configured to obtain first attribute data of a first attribute of a target item, a user attention data set, and second attribute data of a second attribute, where the first attribute data includes an initial value of a first attribute value of the first attribute, the user attention data set is used to determine a first attribute coefficient of the first attribute, the first attribute coefficient is used to represent a user attention degree to the first attribute, the second attribute data includes an initial value of a second attribute value of the second attribute, and the first attribute is positively correlated with the second attribute; a determining unit 502 configured to determine a first attribute coefficient of a first attribute based on the user attention data set; a generating unit 503 configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
In this embodiment, the obtaining unit 501 may obtain, by a wired connection manner or a wireless connection manner, first attribute data of a first attribute, a user attention data set, and second attribute data of a second attribute of a target item, where the target item may be an item corresponding to data sent by a client (for example, a terminal device shown in fig. 1).
In this embodiment, the first attribute of the target item may be used to characterize a property of the target item. The first attribute data may be data transmitted by a client (e.g., a terminal device shown in fig. 1). The first attribute data may include an initial value of a first attribute value of the first attribute. The first attribute value may be a value to be determined for characterizing the level, quality, length, etc. of the first attribute. The initial value of the first attribute value may be a determined value used to determine the value of the second attribute. The user attention data set may be a data set transmitted by a client (e.g., a terminal device shown in fig. 1), and the user attention data set may be used to determine a first attribute coefficient of the first attribute. The first attribute coefficient may be used to characterize a degree of attention of the user to the first attribute.
In this embodiment, the second attribute of the target item may be used to characterize a property of the target item. The second attribute data may be data transmitted by a client (e.g., the terminal device shown in fig. 1). The second attribute data may include an initial value of a second attribute value of the second attribute. The second attribute value may be a value to be determined for characterizing the level, quality, length, etc. of the second attribute. The initial value of the second attribute value may be a determined value used to determine the value of the second attribute.
In this embodiment, if the first attribute of the target item is positively correlated with the second attribute, the correlation coefficient between the first attribute and the second attribute of the target item is positive, that is, the larger the first attribute value of the first attribute of the target item is, the larger the second attribute value of the second attribute is.
In this embodiment, the determining unit 502 may determine a first attribute coefficient of the first attribute based on the user attention data set obtained by the obtaining unit 501.
In this embodiment, the generating unit 503 may generate the first attribute value of the first attribute and the second attribute value of the second attribute based on the first attribute coefficient obtained by the determining unit 502 and the initial value of the first attribute value and the initial value of the second attribute value obtained by the obtaining unit 501.
In some optional implementations of this embodiment, the generating unit 503 may include: and a first generating module (not shown in the figure) configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute through a dynamic programming algorithm.
In some optional implementations of this embodiment, the first attribute may include at least two first sub-attributes; and the determining unit 502 may include: a third determining module (not shown in the figure), configured to determine, for each first sub-attribute of the at least two first sub-attributes, a first sub-attribute coefficient of the first sub-attribute by performing data analysis on the user attention data set, where the first sub-attribute coefficient is used to characterize the user attention degree to the first sub-attribute; an obtaining module (not shown in the figure) configured to obtain a weight pre-assigned to each of the at least two first sub-attributes; a processing module (not shown in the figure) configured to perform weighted summation processing on the determined first sub-attribute coefficient according to the obtained weight, and generate a weighted summation value; a fourth determining module (not shown in the figure) configured to determine the weighted sum as a first property coefficient of the first property.
In some optional implementations of this embodiment, the generating unit 503 may include: a fifth determining module (not shown in the figure) configured to determine whether the first attribute coefficient is greater than a preset first attribute coefficient threshold; and a second generating module (not shown in the figure) configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold.
The apparatus provided by the above embodiment of the present application, through the obtaining unit 501, obtains the first attribute data of the first attribute of the target item, the user attention data set, and the second attribute data of the second attribute, wherein the first attribute data comprises an initial value of a first attribute value of the first attribute, the first attribute coefficient is used for representing the attention degree of the user to the first attribute, the second attribute data comprises an initial value of a second attribute value of the second attribute, the first attribute is positively correlated with the second attribute, then, the determining unit 502 determines a first attribute coefficient of the first attribute based on the user attention data set, and finally the generating unit 503 generates a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value, thereby improving the accuracy of information generation.
Referring now to FIG. 6, shown is a block diagram of a computer system 600 suitable for use in implementing a server according to embodiments of the present application. The server shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the system 600 are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the method of the present application when executed by a Central Processing Unit (CPU) 601. It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a determination unit, and a generation unit. Where the names of these units do not in some cases constitute a limitation on the unit itself, for example, an acquisition unit may also be described as a "unit to acquire data".
As another aspect, the present application also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be present separately and not assembled into the device. The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: acquiring first attribute data of a first attribute of a target object, a user attention data set and second attribute data of a second attribute, wherein the first attribute data comprise an initial value of a first attribute value of the first attribute, the user attention data set is used for determining a first attribute coefficient of the first attribute, the first attribute coefficient is used for representing the attention degree of a user to the first attribute, the second attribute data comprise an initial value of a second attribute value of the second attribute, and the first attribute is positively correlated with the second attribute; determining a first attribute coefficient of a first attribute based on the user attention data set; generating a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (10)
1. A method for generating information, comprising:
acquiring first attribute data of a first attribute of a target article, a user attention data set and second attribute data of a second attribute, wherein the first attribute data comprise an initial value of a first attribute value of the first attribute, the second attribute data comprise an initial value of a second attribute value of the second attribute, the first attribute is positively correlated with the second attribute, the first attribute value is a numerical value to be determined and representing the height, the superiority or the length of the first attribute, the initial value of the first attribute value is a determined numerical value used for determining the second attribute value, the second attribute value is a numerical value to be determined and representing the height, the superiority or the length of the second attribute, and the initial value of the second attribute is a determined numerical value used for determining the second attribute value;
determining a first attribute coefficient for the first attribute based on the user attention data set, including: deleting the most value in the user attention data set, and determining a first attribute coefficient of the first attribute based on the user attention data set after deleting the most value, wherein the first attribute coefficient is used for representing the attention degree of the user to the first attribute;
generating a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value.
2. The method of claim 1, wherein the generating a first attribute value of the first attribute and a second attribute value of the second attribute comprises:
and generating a first attribute value of the first attribute and a second attribute value of the second attribute through a dynamic programming algorithm.
3. The method of claim 1, wherein the first attribute comprises at least two first sub-attributes; and
the determining a first attribute coefficient for the first attribute based on the user attention data set comprises:
for each first sub-attribute in the at least two first sub-attributes, determining a first sub-attribute coefficient of the first sub-attribute by performing data analysis on the user attention data set, wherein the first sub-attribute coefficient is used for representing the attention degree of a user to the first sub-attribute;
acquiring a weight pre-allocated to each of the at least two first sub-attributes;
according to the obtained weight, carrying out weighted summation processing on the determined first sub-attribute coefficient to generate a weighted summation value;
determining the weighted sum as a first attribute coefficient of the first attribute.
4. The method of one of claims 1 to 3, wherein the generating a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, an initial value of the first attribute value, and an initial value of the second attribute value comprises:
determining whether the first attribute coefficient is larger than a preset first attribute coefficient threshold value;
in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value, generating a first attribute value of the first attribute and a second attribute value of the second attribute based on the first attribute coefficient, an initial value of the first attribute value, and an initial value of the second attribute value.
5. An apparatus for generating information, comprising:
an obtaining unit, configured to obtain first attribute data of a first attribute of a target item, a user attention data set, and second attribute data of a second attribute, where the first attribute data includes an initial value of a first attribute value of the first attribute, the second attribute data includes an initial value of a second attribute value of the second attribute, the first attribute is positively related to the second attribute, the first attribute value is a value to be determined and representing a height, a goodness, or a length of the first attribute, the initial value of the first attribute value is a determined value used for determining the second attribute value, the second attribute value is a value to be determined and representing a height, a goodness, or a length of the second attribute, and the initial value of the second attribute is a determined value used for determining the second attribute value;
a determining unit configured to determine a first attribute coefficient of the first attribute based on the user attention data set, including: deleting the most value in the user attention data set, and determining a first attribute coefficient of the first attribute based on the user attention data set after deleting the most value, wherein the first attribute coefficient is used for representing the attention degree of the user to the first attribute;
a generating unit configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the determined first attribute coefficient, an initial value of the first attribute value, and an initial value of the second attribute value.
6. The apparatus of claim 5, wherein the generating unit comprises:
and the first generation module is configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute through a dynamic programming algorithm.
7. The apparatus of claim 5, wherein the first attribute comprises at least two first sub-attributes; and
the determination unit includes:
a third determining module, configured to determine, for each first sub-attribute of the at least two first sub-attributes, a first sub-attribute coefficient of the first sub-attribute by performing data analysis on the user attention data set, where the first sub-attribute coefficient is used to characterize the user attention degree to the first sub-attribute;
the acquisition module is configured to acquire a weight pre-allocated to each of the at least two first sub-attributes;
the processing module is configured to perform weighted summation processing on the determined first sub-attribute coefficient according to the obtained weight to generate a weighted summation value;
a fourth determination module configured to determine the weighted sum as a first attribute coefficient of the first attribute.
8. The apparatus according to one of claims 5-7, wherein the generating unit comprises:
a fifth determining module configured to determine whether the first attribute coefficient is greater than a preset first attribute coefficient threshold;
a second generation module configured to generate a first attribute value of the first attribute and a second attribute value of the second attribute based on the first attribute coefficient, the initial value of the first attribute value, and the initial value of the second attribute value in response to determining that the first attribute coefficient is greater than a preset first attribute coefficient threshold value.
9. A server, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1-4.
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