CN109344327B - Method and apparatus for generating information - Google Patents
Method and apparatus for generating information Download PDFInfo
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- CN109344327B CN109344327B CN201811106140.1A CN201811106140A CN109344327B CN 109344327 B CN109344327 B CN 109344327B CN 201811106140 A CN201811106140 A CN 201811106140A CN 109344327 B CN109344327 B CN 109344327B
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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: receiving query conditions input by a user aiming at a search result statistical data set, wherein the search result statistical data comprise search terms and object description information, and the object description information comprises attribute information of at least one object attribute type; then, determining the search result statistical data matched with the query conditions in the search result statistical data set as a target search result statistical data set; finally, for each search result statistic in the target search result statistic set, a match score determination operation is performed. The implementation mode effectively utilizes the statistical data of the search results, and realizes the automatic quantitative evaluation of the user experience of searching websites/searching products.
Description
Technical Field
The embodiment of the application relates to the technical field of computers, in particular to a method and a device for generating information.
Background
A user may obtain information related to a search term by entering the search term in a search website. Different search sites employ different presentation styles or ranking algorithms to provide search services to users. For the same search website, the user inputs the same search word, and the search website can also provide different presentation styles or sorting algorithms through different search products to provide search services for the user.
Currently, the user experience of searching websites or searching products is mostly evaluated in a manual or questionnaire manner.
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: receiving query conditions input by a user aiming at a search result statistical data set, wherein the search result statistical data comprise search words and object description information, and the object description information comprises attribute information of at least one object attribute type; determining the search result statistical data matched with the query conditions in the search result statistical data set as a target search result statistical data set; for each search result statistic in the target search result statistic set, performing the following matching score determination operation to obtain a matching score corresponding to the search result statistic.
In some embodiments, the match score determination operation comprises: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data; for each detection condition in the determined first detection condition set, determining whether the search result statistical data meets the detection condition according to a condition detection method corresponding to the detection condition, setting the matching score of the search result statistical data under the detection condition to be a first preset value in response to the determination that the search result statistical data meets the detection condition, and setting the matching score of the search result statistical data under the detection condition to be a second preset value smaller than the first preset value in response to the determination that the search result statistical data does not meet the detection condition.
In some embodiments, the search result statistics further include a search product identification; and the method further comprises: generating a target search product identification set by using search product identifications included in each search result statistical data in the target search result statistical data set; generating a second detection condition set by using the first detection condition set corresponding to each search result statistical data in the target search result statistical data set; for each detection condition in the second set of detection conditions, performing the following condition satisfaction rate determination operations: for each search product identifier in the target search product identifier set, determining the number of pieces of search result statistical data, in which the search product identifier in the target search result statistical data set is the search product identifier, as the number of pieces of first search result statistical data, determining the sum of matching scores of each piece of search result statistical data, in which the search product identifier in the target search result statistical data set is the search product identifier, under the detection condition as a first matching score sum, and determining the ratio of the first matching score sum divided by the product of the number of pieces of first search result statistical data and a first preset value as the condition satisfaction rate of the search product indicated by the search product identifier under the detection condition.
In some embodiments, the method further comprises: and for each search product identifier in the target search product identifier set, determining the comprehensive condition satisfaction rate of the search product indicated by the search product identifier according to the condition satisfaction rate of the search product indicated by the search product identifier under various detection conditions in the second detection condition set.
In some embodiments, the method further comprises: and determining the comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search products indicated by each search product identification in the target search product identification set.
In some embodiments, the method further comprises: and for each search product identifier in the target search product identifier set, presenting the condition satisfaction rate of the product indicated by the search product identifier under various detection conditions in the second detection condition set according to a preset presentation mode.
In some embodiments, the method further comprises: and presenting the comprehensive condition satisfaction rate of the search products indicated by the search product identification for each search product identification in the target search product identification set.
In some embodiments, the search result statistics further comprise: the number of times of showing, the object attribute type includes at least one of the following: title, page address.
In a second aspect, an embodiment of the present application provides an apparatus for generating information, where the apparatus includes: the device comprises a receiving unit, a query processing unit and a query processing unit, wherein the receiving unit is configured to receive query conditions input by a user aiming at a search result statistical data set, the search result statistical data comprises search words and object description information, and the object description information comprises attribute information of at least one object attribute type; a first determination unit configured to determine search result statistical data matching the query condition in the search result statistical data set as a target search result statistical data set; and a second determination unit configured to perform, for each search result statistic data in the target search result statistic data set, the following matching score determination operation to obtain a matching score corresponding to the search result statistic data.
In some embodiments, the match score determination operation comprises: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data; for each detection condition in the determined first detection condition set, determining whether the search result statistical data meets the detection condition according to a condition detection method corresponding to the detection condition, setting the matching score of the search result statistical data under the detection condition to be a first preset value in response to the determination that the detection condition is met, and setting the matching score of the search result statistical data under the detection condition to be a second preset value smaller than the first preset value in response to the determination that the detection condition is not met.
In some embodiments, the search result statistics further include a search product identification; and the apparatus further comprises: a first generation unit configured to generate a target search product identification set using search product identifications included in respective search result statistics data in the target search result statistics data set; a second generating unit configured to generate a second detection condition set by using the first detection condition set corresponding to each search result statistic data in the target search result statistic data set; a third determination unit configured to perform, for each detection condition in the second detection condition set, the following condition satisfaction rate determination operation: for each search product identifier in the target search product identifier set, determining the number of the search result statistical data of which the search product identifier in the target search result statistical data set is the search product identifier as the number of the first search result statistical data, determining the sum of the matching scores of the search result statistical data of which the search product identifier in the target search result statistical data set is the search product identifier under the detection condition as the sum of the first matching scores, and determining the ratio of the sum of the first matching scores and the sum of the ratios obtained by dividing the number of the first search result statistical data by the product of the first preset value as the condition satisfaction rate of the search product indicated by the search product identifier under the detection condition.
In some embodiments, the apparatus further comprises: and the fourth determining unit is configured to determine the comprehensive condition satisfaction rate of the search products indicated by the search product identification according to the condition satisfaction rates of the search products indicated by the search product identification under various detection conditions in the second detection condition set for each search product identification in the target search product identification set.
In some embodiments, the apparatus further comprises: and the fifth determining unit is configured to determine the comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search products indicated by each search product identification in the target search product identification set.
In some embodiments, the apparatus further comprises: and the first presentation unit is configured to present the condition satisfaction rate of the product indicated by the search product identifier under various detection conditions in the second detection condition set according to a preset presentation mode for each search product identifier in the target search product identifier set.
In some embodiments, the apparatus further comprises: and the second presentation unit is configured to present the comprehensive condition satisfaction rate of the search products indicated by the search product identification for each search product identification in the target search product identification set.
In some embodiments, the search result statistics further comprise: the showing times and the object attribute types comprise at least one of the following items: title, page address.
In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; a storage device, on which one or more programs are stored, which, when executed by the one or more processors, cause the one or more processors to implement the method as described in any implementation manner of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium on which a computer program is stored, where the computer program, when executed by one or more processors, implements the method as described in any implementation manner of the first aspect.
According to the method and the device for generating the information, query conditions input by a user aiming at a search result statistical data set are received, wherein the search result statistical data comprise search terms and object description information, and the object description information comprises attribute information of at least one object attribute type; then, determining the search result statistical data matched with the query conditions in the search result statistical data set as a target search result statistical data set; and finally, executing matching score determination operation on each search result statistical data in the target search result statistical data set. Therefore, the statistical data of the search results are effectively utilized, and the automatic quantitative evaluation of the user experience of searching websites/searching products is realized.
Drawings
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 one embodiment of the present application may be applied;
FIG. 2A is a flow diagram for one embodiment of a method for generating information according to the present application;
FIG. 2B is a flowchart of one embodiment of a match score determination operation 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. 4A is a flow diagram of yet another embodiment of a method for generating information according to the present application;
FIG. 4B is a flow diagram for one embodiment of a condition satisfaction rate determination operation in accordance with 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 to implement the electronic device of an embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the 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 data servers 101, 102, 103, a network 104, and an information generating device 105. The network 104 is used to provide a medium for communication links between the data servers 101, 102, 103 and the information generating device 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 information generating device 105 to interact with the data servers 101, 102, 103 via the network 104 to receive or send messages or the like. Various messaging client applications, such as an application for generating information, a web browser application, a shopping-like application, a search-like application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the information generating device 105.
The information generating apparatus 105 may be hardware or software. When the information generating device 105 is hardware, it may be a variety of electronic devices with a display screen, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like. When the information generating apparatus 105 is software, it can be installed in the electronic apparatuses listed above. It may be implemented as a plurality of software or software modules (for example, for providing an information generating service), or as a single software or software module. And is not particularly limited herein.
The data servers 101, 102, 103 may be servers that provide various services, such as a background data server that provides support for an application displayed on the information generating device 105 for generating information. The background data server may analyze and otherwise process the received data such as the search result statistical data query request, and feed back the processing result (e.g., the search result statistical data) to the information generating device.
It should be noted that the method for generating information provided in the embodiment of the present application is generally performed by the information generating apparatus 105, and accordingly, the apparatus for generating information is generally disposed in the information generating apparatus 105. In some cases, the system architecture 100 may not include the data servers 101, 102, 103 and the network 104, that is, the method for generating information provided by the embodiment of the present application may be executed by the information generating device 105 alone.
The data servers 101, 102, and 103 may be hardware or software. When the data server is hardware, it can be implemented as a distributed server cluster composed of multiple data servers, or as a single server. When the data server is software, it may be implemented as a plurality of software or software modules (for example, for providing a data query service), or may be implemented as a single software or software module. And is not particularly limited herein.
It should be understood that the number of data servers, networks, and information generating devices in fig. 1 is merely illustrative. There may be any number of data servers, networks, and information generating devices, as desired for implementation.
With continued reference to FIG. 2A, a flow 200 of one embodiment of a method for generating information in accordance with the present application is illustrated. The method for generating information comprises the following steps:
In this embodiment, an executing agent (e.g., the information generating device shown in fig. 1) of the method for generating information may receive, locally or remotely, a query condition input by a user for a search result statistic set from a terminal device network-connected to the executing agent. The search result statistics may include search terms and object description information.
The object description information here is various information for describing an object. The object may include a real object, a service, a person, an event, and the like, and the object may be described by information (including text, pictures, and sounds). The object description information may include attribute information of at least one object attribute type. For example, object description information describing the object "flower delivery" may include: the flower shop name, the service commitment description, the flower usage classification description, the flower shop avatar picture, the flower shop address, the flower delivery service website, and so on. For another example, the object description information describing the object "car" may include: vehicle manufacturer, vehicle model, engine parameters, price, vehicle picture, vehicle description title, and the like.
In some optional implementations of this embodiment, the object property type may include at least one of: title, page address. The header is used for summarizing the object description information, and the page address is used for indicating a specific page address corresponding to the object description information.
In practice, the search result statistics may include other fields besides the search term, for example, may include: number of presentations, search time, etc. Here, the query condition refers to a condition that is restricted for each field included in the search result statistic data.
In practice, the search result statistical data set may be obtained by performing statistical analysis on a search log, where the search log includes search words and corresponding search results input by a user.
Here, the search result statistic data set may be stored locally in the execution subject, or may be stored in another electronic device (for example, a data server shown in fig. 1) that is network-connected to the execution subject.
In this embodiment, based on the query condition obtained in step 201, the execution subject (e.g., the information generating apparatus shown in fig. 1) may first query the search result statistics matching the query condition in the search result statistics set. And then, determining the searched search result statistical data as a target search result statistical data set.
It is to be understood that if the search result statistics set is stored locally in the execution subject, the execution subject may query the search result statistics set stored locally for search result statistics matching the query criteria. And then, determining the searched search result statistical data as a target search result statistical data set. If the search result statistic set is stored in another electronic device (for example, the data server shown in fig. 1) connected to the execution main body via a network, the execution main body may first send the query condition to the another electronic device, and then the another electronic device may query the search result statistic matching the query condition and send the queried search result statistic to the execution main body, and finally the execution main body determines each piece of search result statistic received from the another electronic device as the target search result statistic set.
In this embodiment, the executing agent may execute a matching score determining operation for each search result statistic in the target search result statistic set determined in step 202, so as to obtain a matching score corresponding to the search result statistic.
Here, the execution body may adopt various implementation matching score determination operations to obtain a matching score corresponding to the search result statistic.
As an example, the execution subject may calculate the degree of correlation between the search word in the search result statistic and the object description information, and use the calculated degree of correlation as the matching score corresponding to the search result statistic. For example, when text is included in the object description information, the similarity between the text and the search word may be calculated as the correlation between the search word and the object description information. For example, when the object description information includes a picture, the picture content text may be obtained by performing content identification on the picture, and a text similarity between the picture content text and the search word may be calculated as a correlation between the search word and the object description information.
As another example, the executing entity may further input the search result statistics into a pre-trained match score determination model to obtain a match score corresponding to the search result statistics, where the match score determination model is used to characterize a correspondence between the search result statistics and the match score. The matching score determination model may be obtained by training based on a training sample set by using a machine learning method, where the training sample may include sample search result statistics and corresponding labeled matching scores.
In some optional implementations of this embodiment, the match score determination operation may include sub-steps 2031 and 2032 as shown in fig. 2B:
sub-step 2031, selecting at least one detection condition from a preset detection condition set according to the object attribute type corresponding to various attribute information included in the object description information of the search result statistical data, and determining as a first detection condition set corresponding to the search result statistical data.
Here, the execution body may first determine an object attribute type corresponding to various attribute information included in the object description information of the search result statistic data. Then, the execution subject may adopt various implementation manners, and according to the determined various object attribute types, select at least one detection condition from a preset detection condition set, and determine the at least one detection condition as a first detection condition set corresponding to the search result statistical data.
Here, the detection conditions in the preset detection condition set characterize conditions for constraining the attribute information of at least one object attribute type.
As an example, the execution body described above may store a correspondence table for characterizing a correspondence between the object attribute type and the detection condition. In this way, the execution main body may first create an empty first detection condition set, then, for each determined object attribute type, query the corresponding detection condition in the correspondence table for the object attribute type, and add the found detection condition to the first detection condition set.
As an example, the execution main body may further create an empty first detection condition set, then, for each detection condition in a preset detection condition set, query the corresponding relationship table for an object attribute type corresponding to the detection condition, and add the detection condition to the first detection condition set in response to determining that the object description information of the search result statistic data includes the found object attribute type.
For example, the detection condition corresponding to the object attribute type "object description title" may be an expanded word such as a synonym, or an abbreviation that does not include the preset blacklist keyword and the preset blacklist keyword in the object description title, for example, the preset blacklist keyword may include: pornography-related keywords, drugs-related keywords, violence-related keywords, false publicity keywords, exaggeration effect keywords, and so forth.
For another example, the detection condition corresponding to the object attribute type "object description picture" may be that the picture content of the object description picture is related to the search term.
For another example, the detection condition corresponding to the object attribute type "object description picture" may be a picture in which the object description picture is a non-solid color picture and is not composed of solid characters.
Sub-step 2032, for each detection condition in the determined first detection condition set, determining whether the search result statistic satisfies the detection condition according to a condition detection method corresponding to the detection condition, and in response to the determination being satisfied, setting the matching score of the search result statistic under the detection condition to a first preset value, and in response to the determination being not satisfied, setting the matching score of the search result statistic under the detection condition to a second preset value smaller than the first preset value.
Here, for each detection condition in the preset detection condition set, a corresponding condition detection method is associated with the execution subject, and the condition detection methods corresponding to different detection conditions are different.
For example, when the detection condition is that the object description title does not include a word in the preset blacklist keyword set, the corresponding condition detection method may be to determine the detection condition of the synonym, the abbreviation and the like that satisfy that the object description title does not include the preset blacklist keyword and the preset blacklist keyword under the condition that the object description title does not include the preset blacklist keyword and the synonym, the abbreviation and the like of the preset blacklist keyword.
For another example, when the detection condition is that the picture content of the object description picture is related to the search term, the corresponding detection method may be to identify the picture content of the object description picture, obtain a content keyword, and then determine that the detection condition that the picture content of the object description picture is related to the search term is satisfied when it is determined that the similarity between the content keyword and the search term is greater than a preset similarity threshold.
In practice, the corresponding detection method may be preset according to different detection conditions, and no examples are given here.
In this way, the executing body may determine, for each detection condition in the first set of detection conditions determined in sub-step 2031, whether the search result statistic satisfies the detection condition according to a condition detection method corresponding to the detection condition, and set the matching score of the search result statistic under the detection condition to a first preset value in response to the determination being satisfied, and set the matching score of the search result statistic under the detection condition to a second preset value smaller than the first preset value in response to the determination being not satisfied. As an example, here, the first preset value may be 1, and the second preset value may be 0.
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, a user inputs a query condition 302 using the information generation device 301; then, the information generating device 301 sends the query condition 302 to the data server 303, then the data server 303 queries the search result statistical data matched with the query condition 302 in the search result statistical data set, and returns the found search result statistical data serving as the target search result statistical data set 304 to the information generating device 301; then, the information generating apparatus 301 performs a matching score determining operation for each search result statistic in the target search result statistic set 304, resulting in a matching score 305 for each search result statistic.
According to the method provided by the embodiment of the application, the search result statistical data, the preset detection condition set and the detection method corresponding to each detection condition are utilized, so that the automatic quantitative evaluation of the user experience of searching the website/searching products is realized.
With further reference to fig. 4A, 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 following steps:
In this embodiment, an executing agent (e.g., the information generating device shown in fig. 1) of the method for generating information may receive, locally or remotely, a query condition input by a user for a search result statistical data set from a terminal device network-connected to the executing agent. The search result statistics may include search terms, search product identifiers, and object description information, among other things.
Here, regarding the object description information, reference may be made to the related description in step 201 in the embodiment shown in fig. 2A, and details are not repeated here.
Here, the search product identification is used to uniquely identify each search product. The search result presentation style and/or search result ranking algorithm may be different for different search products.
In practice, the search result statistics may include other fields besides the search term, for example, may include: number of presentations, search time, etc. Here, the query condition refers to a condition that is restricted for each field included in the search result statistic data.
In practice, the search result statistical data set may be obtained by performing statistical analysis on a search log, where the search log includes search words and corresponding search results input by a user.
Here, the search result statistic data set may be stored locally in the execution subject, or may be stored in another electronic device (for example, a data server shown in fig. 1) that is network-connected to the execution subject.
In step 403, a match score determination operation is performed for each search result statistic in the target search result statistic set.
In this embodiment, the specific operations of step 402 and step 403 are substantially the same as the operations of step 202 and step 203 in the embodiment shown in fig. 2A, and are not described again here.
In this embodiment, an executing body (for example, the information generating apparatus shown in fig. 1) of the method for generating information may generate the target search product identifier set by removing duplicates with respective search product identifiers included in respective search result statistics data in the target search result statistics data set.
In this embodiment, the executing entity may generate the second detection condition set by removing the duplication from each detection condition in the first detection condition set corresponding to each search result statistic in the target search result statistic set.
At step 406, for each detection condition in the second set of detection conditions, a condition satisfaction rate determination operation is performed.
In the present embodiment, the executing body described above may execute the condition satisfaction rate determination operation for each detection condition in the second detection condition set generated in step 405. Wherein the condition satisfaction rate determination operation may include sub-steps 4061 through 4063 as shown in fig. 4B:
Sub-step 4062, determining the sum of the matching scores of the search result statistics data in the target search result statistics data set, in which the search product identifier is the search product identifier, under the detection condition as the first sum of the matching scores.
For clarity, it is assumed here that the second set of detection conditions C includes N detection conditions { C1，C2，…，CNSuppose that the target search product identification set P includes M search product identifications { P }1，P2，…，PMAnd f, wherein N and M are positive integers. Here, steps 4061 to 4063 are for detection condition C in the second detection condition set CiAnd executing a condition satisfaction rate determination operation, wherein i is a positive integer.
Suppose that the search product identifier in the target search result statistic data set is PjThe number of the search result statistics data is Count _ PjSearching product identification P in target search result statistical data setjCount _ P ofjK-th search result statistical data in the search result statistical data under the detection condition CiDown match Score _ Pj_CiK, where k is 1 to Count _ PjPositive integer in between, the first match Score and Score _ Pj_CiCan be formulated as follows:
suppose that the first predetermined value is V1The second predetermined value is V2Then search for the product identification PjSearch for the product indicated in detection Condition CiThe condition under (2) satisfies the Rate _ Pj_CiCan be formulated as follows:
if V1Is 1, V2Is 0, then Score _ Pj_CiSearching product identification P in target search result statistical data setjCount _ P ofjSatisfying the detection condition C in the statistical data of the search resultsiCount _ P, Count _ Pj×V1I.e. the search product identifier in the target search result statistical data set is PjThe number of the search result statistics data Count _ Pj。
Through steps 404 to 406, the condition satisfaction rates of different search products under different detection conditions can be obtained, so that quantitative information of user experience/evaluation of different search products under different detection conditions can be obtained.
In some optional implementation manners of this embodiment, after the executing step 406 is completed, the executing step 407 may further be executed:
Here, the execution subject may adopt various implementation manners, and for each search product identifier in the target search product identifier set, determine a comprehensive condition satisfaction rate of the search product indicated by the search product identifier according to a condition satisfaction rate of the search product indicated by the search product identifier under various detection conditions in the second detection condition set.
As an example, step 407 may proceed as follows:
and determining the condition satisfaction rate mean value of the search product indicated by the search product identification under various detection conditions in the second detection condition set as the comprehensive condition satisfaction rate of the search product indicated by the search product identification.
As an example, step 407 may also proceed as follows:
and weighting the condition satisfaction rates of the search products indicated by the search product identifiers under various detection conditions in the second detection condition set according to preset weights corresponding to the detection conditions, and determining the weighted sum as the comprehensive condition satisfaction rate of the search products indicated by the search product identifiers. Here, the preset weight corresponding to each detection condition may be positively correlated to the number of the search result statistics data satisfying the detection condition in the historical search result statistics data, if the number of the search result statistics data satisfying the detection condition in the historical search result statistics data is greater, the preset weight corresponding to the detection condition is higher, otherwise, if the number of the search result statistics data satisfying the detection condition in the historical search result statistics data is less, the preset weight corresponding to the detection condition is lower.
Through the step 407, the comprehensive condition satisfaction rates of different search products can be obtained, so that quantitative information of user experience/evaluation of the search products can be obtained.
In some optional implementations of this embodiment, after the executing step 407 is completed, the executing step 408 may further be executed by the executing step:
and step 408, determining the comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search products indicated by each search product identification in the target search product identification set.
Here, the executing agent may adopt various implementation manners to determine the comprehensive condition satisfaction rate of the target search product identifier set according to the comprehensive condition satisfaction rate of the search product indicated by each search product identifier in the target search product identifier set obtained in step 407.
As an example, step 408 may proceed as follows:
and determining the average value of the comprehensive condition satisfaction rates of the search products indicated by each search product identifier in the target search product identifier set as the comprehensive condition satisfaction rate of the target search product identifier set.
As an example, step 408 may also proceed as follows:
and weighting the comprehensive condition satisfaction rate of the search products indicated by each search product identifier in the target search product identifier set according to the preset weight corresponding to the search product identifier, and determining the weighted sum as the comprehensive condition satisfaction rate of the target search product identifier set.
Here, the preset weight corresponding to each search product identifier may be positively correlated to the number of the search result statistics data in which the search product identifier is the search product identifier in the historical search result statistics data, if the number of the search result statistics data in which the search product identifier is the search product identifier in the historical search result statistics data is large, the preset weight corresponding to the search product identifier is high, and otherwise, if the number of the search result statistics data in which the search product identifier is the search product identifier in the historical search result statistics data is small, the preset weight corresponding to the search product identifier is low.
Through step 408, the comprehensive condition satisfaction rate of the target search product identifier set can be obtained, so that the quantitative information of the user experience/evaluation of the target search product identifier set obtained through query in step 401 can be obtained.
In some optional implementations of this embodiment, after the executing step 408 is completed, the executing step 409 may further be executed by the executing main body:
and 409, presenting the comprehensive condition satisfaction rate of the product indicated by the searched product identifier under various detection conditions in the second detection condition set according to a preset presentation mode for each searched product identifier in the target searched product identifier set.
For example, assume that the second set of detection conditions C includes N detection conditions { C1，C2，…，CNLet's assume that the target search product identification set P includes M search product identifications { P }1，P2，…，PMAnd f, wherein N and M are positive integers. Then, here, the preset presentation manner may be M search product identifications { P } in P1，P2，…，PMAnd (4) taking the coordinate of the horizontal axis and the matching score of each searched product identifier in the P under each of the N detection conditions in the C as the vertical coordinate to form N broken lines, wherein each broken line corresponds to one detection condition in the C, and the matching score comparison conditions under different detection conditions for the same searched product can be seen from the N broken lines.
In addition, the preset presentation mode may also be that each of the N detection conditions in C is a horizontal axis coordinate, and M search product identifiers { P in P are respectively used1，P2，…，PMForming M broken lines by taking the matching score under each of the N detection conditions in the C as a vertical coordinate, wherein each broken line corresponds to one search product identifier in the P, and the M broken lines are selected from the M broken linesIt can be seen that for the same detection condition, the matching scores of different search products under the detection condition are compared.
In some optional implementations of this embodiment, after the executing step 409 is completed, the executing step 410 may further be executed:
and step 410, presenting the comprehensive condition satisfaction rate of the search products indicated by the search product identification for each search product identification in the target search product identification set.
Here, it can be presented in various ways. For example, a line graph may be formed to show each search product identifier in the target search product identifier set as a horizontal axis coordinate and the comprehensive condition satisfaction rate of the search product indicated by the search product identifier as a vertical axis coordinate. For another example, each search product identifier in the target search product identifier set may be represented as a horizontal axis coordinate, and the comprehensive condition satisfaction rate of the search product indicated by the search product identifier may be represented as a vertical axis coordinate to form a histogram.
As can be seen from fig. 4A, compared with the embodiment corresponding to fig. 2A, in the flow 400 of the method for generating information in the present embodiment, there are more steps for determining the condition satisfaction rates of the search products indicated by different search product identifiers under various detection conditions. Therefore, the scheme described in the embodiment can introduce the search product identification, so that the quantitative information for evaluating the search product can be generated more comprehensively and dimensionally.
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. 2A, and which is particularly applicable to various electronic devices.
As shown in fig. 5, the apparatus 500 for generating information of the present embodiment includes: a receiving unit 501, a first determining unit 502 and a second determining unit 503. The receiving unit 501 is configured to receive a query condition input by a user for a search result statistic data set, where the search result statistic data includes a search term and object description information, where the object description information includes attribute information of at least one object attribute type; a first determining unit 502 configured to determine search result statistical data matching the query condition in the search result statistical data set as a target search result statistical data set; a second determining unit 503 configured to perform the following matching score determining operation for each search result statistic in the target search result statistic set, resulting in a matching score corresponding to the search result statistic.
In this embodiment, specific processing of the receiving unit 501, the first determining unit 502, and the second determining unit 503 of the apparatus 500 for generating information and technical effects brought by the processing can refer to related descriptions of step 201, step 202, and step 203 in the corresponding embodiment of fig. 2A, respectively, and are not described herein again.
In some optional implementations of this embodiment, the matching score determining operation may include: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data; for each detection condition in the determined first detection condition set, determining whether the search result statistic satisfies the detection condition according to a condition detection method corresponding to the detection condition, and in response to determining that the detection condition is satisfied, setting the matching score of the search result statistic under the detection condition to a first preset value, and in response to determining that the detection condition is not satisfied, setting the matching score of the search result statistic under the detection condition to a second preset value smaller than the first preset value.
In some optional implementation manners of this embodiment, the search result statistical data may further include a search product identifier; and the apparatus 500 may further include: a first generating unit 504 configured to generate a target search product identification set using search product identifications included in each search result statistic in the target search result statistic set; a second generating unit 505 configured to generate a second detection condition set by using the first detection condition set corresponding to each search result statistic in the target search result statistic set; a third determining unit 506 configured to perform the following condition satisfaction rate determination operation for each detection condition in the second detection condition set: for each search product identifier in the target search product identifier set, determining the number of pieces of search result statistical data in which a search product identifier in the target search result statistical data set is the search product identifier as the number of pieces of first search result statistical data, determining the sum of matching scores of the search result statistical data in the target search result statistical data set, in which the search product identifier is the search product identifier, under the detection condition as a first matching score sum, and determining a ratio obtained by dividing the first matching score sum by the product of the number of pieces of first search result statistical data and the first preset value as a condition satisfaction rate of the search product indicated by the search product identifier under the detection condition.
In some optional implementations of this embodiment, the apparatus 500 may further include: a fourth determining unit 507, configured to determine, for each search product identifier in the target search product identifier set, a comprehensive condition satisfaction rate of the search product indicated by the search product identifier according to the condition satisfaction rates of the search product indicated by the search product identifier under various detection conditions in the second detection condition set.
In some optional implementations of this embodiment, the apparatus 500 may further include: a fifth determining unit 508, configured to determine a comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search product indicated by each search product identification in the target search product identification set.
In some optional implementations of this embodiment, the apparatus 500 may further include: the first presenting unit 509 is configured to present, according to a preset presenting manner, a condition satisfaction rate of a product indicated by the search product identifier under various detection conditions in the second detection condition set, for each search product identifier in the target search product identifier set.
In some optional implementations of this embodiment, the apparatus 500 may further include: and a second presenting unit 510 configured to present, for each search product identifier in the target search product identifier set, a comprehensive condition satisfaction rate of the search product indicated by the search product identifier.
In some optional implementation manners of this embodiment, the search result statistic may further include: the number of times of exposure, the object attribute type may include at least one of: title, page address.
It should be noted that, for details of implementation and technical effects of each unit in the apparatus for generating information provided in the embodiment of the present application, reference may be made to descriptions of other embodiments in the present application, and details are not described herein again.
Referring now to FIG. 6, shown is a block diagram of a computer system 600 suitable for use in implementing the electronic device of an embodiment of the present application. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the use range of the embodiment of the present application.
As shown in fig. 6, the computer system 600 includes a Central Processing Unit (CPU)601, which 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 Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), 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 (Local Area Network) 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 by 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.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
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 a receiving unit, a first determining unit, and a second determining unit. Where the names of these units do not in some cases constitute a limitation on the units themselves, for example, a receiving unit may also be described as a "unit that receives query conditions entered by a user for a set of search result statistics".
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: receiving query conditions input by a user aiming at a search result statistical data set, wherein the search result statistical data comprise search words and object description information, and the object description information comprises attribute information of at least one object attribute type; determining the search result statistical data matched with the query conditions in the search result statistical data set as a target search result statistical data set; for each search result statistic in the target search result statistic set, performing the following match score determination operations: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data; for each detection condition in the determined first detection condition set, determining whether the search result statistic satisfies the detection condition according to a condition detection method corresponding to the detection condition, and in response to determining that the detection condition is satisfied, setting the matching score of the search result statistic under the detection condition to a first preset value, and in response to determining that the detection condition is not satisfied, setting the matching score of the search result statistic under the detection condition to a second preset value smaller than the first preset value.
The foregoing description is only exemplary of the preferred embodiments 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 (16)
1. A method for generating information, comprising:
receiving query conditions input by a user for a search result statistic data set, wherein the search result statistic data comprises search words and object description information, and the object description information comprises attribute information of at least one object attribute type;
determining the search result statistical data matched with the query conditions in the search result statistical data set as a target search result statistical data set;
executing a matching score determining operation on each search result statistical data in the target search result statistical data set to obtain a matching score corresponding to the search result statistical data;
the match score determination operation includes: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data;
the search result statistics further comprise a search product identification; and the method further comprises:
generating a target search product identification set by using search product identifications included in each search result statistical data in the target search result statistical data set;
generating a second detection condition set by using the first detection condition set corresponding to each search result statistical data in the target search result statistical data set;
for each detection condition of the second set of detection conditions, performing the following condition satisfaction rate determination operations: for each search product identifier in the target search product identifier set, determining the number of the search result statistical data in which the search product identifier in the target search result statistical data set is the search product identifier as the number of the first search result statistical data, determining the sum of the matching scores of the search result statistical data in which the search product identifier in the target search result statistical data set is the search product identifier under the detection condition as a first matching score sum, and determining the ratio of the first matching score sum divided by the product of the number of the first search result statistical data and a first preset value as the condition satisfaction rate of the search product indicated by the search product identifier under the detection condition.
2. The method of claim 1, wherein the match score determination operation comprises:
for each detection condition in the determined first detection condition set, determining whether the search result statistical data meets the detection condition according to a condition detection method corresponding to the detection condition, setting the matching score of the search result statistical data under the detection condition to be a first preset value in response to the determination that the search result statistical data meets the detection condition, and setting the matching score of the search result statistical data under the detection condition to be a second preset value smaller than the first preset value in response to the determination that the search result statistical data does not meet the detection condition.
3. The method of claim 1, wherein the method further comprises:
and for each search product identifier in the target search product identifier set, determining the comprehensive condition satisfaction rate of the search product indicated by the search product identifier according to the condition satisfaction rate of the search product indicated by the search product identifier under various detection conditions in the second detection condition set.
4. The method of claim 3, wherein the method further comprises:
and determining the comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search products indicated by each search product identification in the target search product identification set.
5. The method of claim 4, wherein the method further comprises:
and presenting the condition satisfaction rate of the product indicated by the search product identifier under various detection conditions in the second detection condition set according to a preset presentation mode for each search product identifier in the target search product identifier set.
6. The method of claim 5, wherein the method further comprises:
and presenting the comprehensive condition satisfaction rate of the search products indicated by the search product identification for each search product identification in the target search product identification set.
7. The method of any of claims 1-6, wherein the search result statistics further comprise: the showing times, the object attribute type includes at least one of the following items: title, page address.
8. An apparatus for generating information, comprising:
a receiving unit configured to receive a query condition input by a user for a search result statistic data set, wherein the search result statistic data includes a search word and object description information, and the object description information includes attribute information of at least one object attribute type;
a first determination unit configured to determine search result statistics data matching the query condition among the search result statistics data set as a target search result statistics data set;
a second determination unit configured to perform, for each search result statistic data in the target search result statistic data set, the following matching score determination operation to obtain a matching score corresponding to the search result statistic data;
the match score determination operation includes: selecting at least one detection condition from a preset detection condition set according to object attribute types corresponding to various attribute information included in object description information of the search result statistical data, and determining the at least one detection condition as a first detection condition set corresponding to the search result statistical data;
the search result statistical data further comprises a search product identifier; and the apparatus further comprises:
a first generating unit configured to generate a target search product identification set using search product identifications included in respective search result statistics data in the target search result statistics data set;
a second generating unit configured to generate a second detection condition set by using the first detection condition set corresponding to each search result statistical data in the target search result statistical data set;
a third determination unit configured to perform, for each detection condition in the second detection condition set, the following condition satisfaction rate determination operation: for each search product identifier in the target search product identifier set, determining the number of the search result statistical data of which the search product identifier in the target search result statistical data set is the search product identifier as the number of the first search result statistical data, determining the sum of the matching scores of the search result statistical data of which the search product identifier in the target search result statistical data set is the search product identifier under the detection condition as a first matching score sum, and determining the ratio of the first matching score sum divided by the product of the number of the first search result statistical data and a first preset value as the condition satisfaction rate of the search product indicated by the search product identifier under the detection condition.
9. The apparatus of claim 8, wherein the match score determination operation comprises:
for each detection condition in the determined first detection condition set, determining whether the search result statistical data meets the detection condition according to a condition detection method corresponding to the detection condition, setting the matching score of the search result statistical data under the detection condition to be a first preset value in response to the determination that the search result statistical data meets the detection condition, and setting the matching score of the search result statistical data under the detection condition to be a second preset value smaller than the first preset value in response to the determination that the search result statistical data does not meet the detection condition.
10. The apparatus of claim 8, wherein the apparatus further comprises:
and the fourth determining unit is configured to determine, for each search product identifier in the target search product identifier set, a comprehensive condition satisfaction rate of the search product indicated by the search product identifier according to the condition satisfaction rates of the search product indicated by the search product identifier under various detection conditions in the second detection condition set.
11. The apparatus of claim 10, wherein the apparatus further comprises:
a fifth determining unit, configured to determine a comprehensive condition satisfaction rate of the target search product identification set according to the comprehensive condition satisfaction rate of the search product indicated by each search product identification in the target search product identification set.
12. The apparatus of claim 10, wherein the apparatus further comprises:
and the first presentation unit is configured to present the condition satisfaction rate of the product indicated by the searched product identifier under various detection conditions in the second detection condition set according to a preset presentation mode for each searched product identifier in the target searched product identifier set.
13. The apparatus of claim 12, wherein the apparatus further comprises:
and the second presentation unit is configured to present the comprehensive condition satisfaction rate of the search product indicated by the search product identification for each search product identification in the target search product identification set.
14. The apparatus of any of claims 8-13, wherein the search result statistics further comprise: the showing times, the object attribute type includes at least one of the following items: title, page address.
15. An electronic device, comprising:
one or more processors;
a storage device having one or more programs stored thereon;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method recited in any of claims 1-7.
16. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.
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