CN113256144A - Target object determination method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a target object determining method, a target object determining device, electronic equipment and a storage medium, wherein the method comprises the following steps: determining at least two objects to be selected associated with the target service type; calling at least one characteristic evaluation attribute corresponding to the target service type, and determining a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected; determining a feature evaluation value of a current object to be selected and a weight value corresponding to each feature evaluation attribute for each object to be selected, and determining a matching degree value of the current object to be selected; and determining the target object according to the matching value of each object to be selected. The technical scheme of the embodiment of the invention improves the accuracy of determining the target object.
Description
Technical Field
The embodiment of the invention relates to the technical field of data processing, in particular to a target object determining method and device, electronic equipment and a storage medium.
Background
With the rapid development of information technology, more and more fields select to sort and analyze data through a network, and a user can screen out target objects such as commodities, shops and the like through data analysis on the network.
Data processing platforms in different fields cannot be unified at present, and data of the data processing platforms are processed, so that a user needs to select a required target object on different platforms when selecting the target object, and the operation process is complicated. Moreover, a large amount of manpower and material resources are required for the operation and maintenance management of each platform. In addition, when data is analyzed, the screening condition is single, so that the screened target object is difficult to meet the requirement of the user. Therefore, a way to improve the accuracy of screening of objects is needed.
Disclosure of Invention
The embodiment of the invention provides a target object determination method and device, electronic equipment and a storage medium, aiming at determining a target object aiming at each object to be selected, improving the accuracy of target object determination and improving the user experience.
In a first aspect, an embodiment of the present invention provides a target object determining method, where the method includes:
determining at least two objects to be selected associated with the target service type;
calling at least one characteristic evaluation attribute corresponding to the target service type, and determining a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected;
determining a feature evaluation value of a current object to be selected and a weight value corresponding to each feature evaluation attribute for each object to be selected, and determining a matching degree value of the current object to be selected;
and determining the target object according to the matching value of each object to be selected.
In a second aspect, an embodiment of the present invention further provides a target object determining apparatus, where the apparatus includes:
the device comprises a to-be-selected object determining module, a to-be-selected object determining module and a selecting module, wherein the to-be-selected object determining module is used for determining at least two to-be-selected objects associated with a target service type;
a feature evaluation value determining module, configured to invoke at least one feature evaluation attribute corresponding to the target service type, and determine a feature evaluation value of the at least one feature evaluation attribute of each object to be selected;
the matching degree value determining module is used for determining the feature evaluation value of the current object to be selected and the weight value corresponding to each feature evaluation attribute aiming at each object to be selected, and determining the matching degree value of the current object to be selected;
and the target object determining module is used for determining the target object according to the matching value of each object to be selected.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement the target object determination method according to any one of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the target object determination method according to any one of the embodiments of the present invention.
According to the technical scheme, at least two objects to be selected related to the target service type are determined, at least one characteristic evaluation attribute corresponding to the target service type is called, the characteristic evaluation value of the at least one characteristic evaluation attribute of each object to be selected is determined, the characteristic evaluation value of the current object to be selected and the weight value corresponding to each characteristic evaluation attribute are determined for each object to be selected, the matching degree of the current object to be selected is determined, and the target object is determined according to the matching degree of each object to be selected. According to the technical scheme of the embodiment of the invention, the target object is determined according to the characteristic evaluation value corresponding to the characteristic evaluation attribute and the weight value corresponding to the characteristic evaluation attribute aiming at the object to be selected in different service types, so that the accuracy of determining the target object is improved.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flowchart of a target object determining method according to a first embodiment of the present invention;
fig. 2 is a schematic flowchart of a target object determination method according to a second embodiment of the present invention;
fig. 3 is a schematic view of a display interface of a target object determination system in a third embodiment of the present invention;
fig. 4 is a schematic structural diagram of a target object determining apparatus according to a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flowchart of a target object determining method according to an embodiment of the present invention, where the embodiment is applicable to a case where objects are screened according to a screening condition, and the method may be executed by a target object determining apparatus, and the apparatus may be implemented in a form of software and/or hardware.
As shown in fig. 1, the method for determining a target object according to the embodiment of the present invention specifically includes the following steps:
s110, determining at least two objects to be selected associated with the target service type.
The service types comprise hospital grade service types, hospital department service types, doctor grade service types, shop service types and article service types. The hospital grade refers to the grade of the hospital which is comprehensively evaluated in different modes such as three-year, two-year, civil and official modes. The hospital grade business type includes a business type that evaluates a hospital grade. A hospital department includes multiple departments of dentistry, neurology, brain, etc., and a hospital department business type includes a business type that is evaluated for multiple departments of the same hospital. The doctor level business type includes a business type that evaluates doctors in the same field. Similarly, the store business type includes a business type evaluated for stores in the same field. Item traffic types include traffic types that are evaluated for the same type of item. The target traffic type refers to the traffic type currently being processed. The object to be selected refers to an object to be evaluated in the target business type.
Specifically, at least two objects to be selected associated with the target service type are determined, and the subsequent objects to be selected are processed to obtain the target object. Optionally, the manner of determining the object to be selected may be that, on the display interface, the detection user performs a click operation on the object in the current target service type, and determines that the object corresponding to the click operation is the object to be selected. It should be appreciated that before determining the object to be selected, a target business type is selected from the plurality of business types, and then the object to be selected is selected under the target business type.
S120, at least one characteristic evaluation attribute corresponding to the target service type is called, and a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected is determined.
A plurality of characteristic evaluation attributes corresponding to each service type are preset, wherein the characteristic evaluation attributes refer to attribute information for evaluating each object in a target service type in different aspects. For example, the business type is a store business type, and the characteristic evaluation attribute may be at least one of monthly sales volume, return rate, and goodness rate. The feature evaluation value refers to an evaluation value of a feature evaluation attribute of each object to be selected in the target service type. For example, the service type is a store service type, the feature evaluation attribute includes monthly sales, a return rate, and a goodness rate, the object to be selected includes a store a and a store B, the feature evaluation values for the feature evaluation attribute of the store a are 0.4, 0.5, and 0.8 in this order, and the feature evaluation values for the feature evaluation attribute of the store B are 0.7, 0.1, and 0.9 in this order.
Specifically, at least one feature evaluation attribute corresponding to the target service type is called, and then a feature evaluation value of at least one feature evaluation attribute of each object to be selected under the target service type is determined, so that preparation work is made for subsequent processing based on the feature evaluation value.
S130, determining the feature evaluation value of the current object to be selected and the weight value corresponding to each feature evaluation attribute aiming at each object to be selected, and determining the matching degree value of the current object to be selected.
The current object to be selected refers to the object to be selected which is currently being processed, the weight value corresponding to each feature evaluation attribute may be preset, and when each feature evaluation attribute corresponding to the target service type is predetermined, the weight value corresponding to each feature evaluation attribute is determined. Of course, in order to better meet the requirements of the user, the weight value may be manually set for the weight value corresponding to each feature evaluation attribute after the user selects the target service type. For example, the business type is a store business type, the characteristic evaluation attribute may be monthly sales, return rate and goodness, and the weight values of the characteristic evaluation attribute are 0.4, 0.1 and 0.5 in sequence. The matching degree value is a score corresponding to the object to be selected, and whether the object to be selected is the target object can be determined according to the matching degree value.
Specifically, the feature evaluation value of the current object to be selected and the weight value corresponding to each feature evaluation attribute are determined, and the matching degree value of the current object to be selected is determined based on the feature evaluation value and the corresponding weight value. Optionally, based on the feature evaluation values and the corresponding weight values, a plurality of multiplication results may be obtained by multiplying each feature evaluation value by a weight value, and the plurality of multiplication results are accumulated to obtain a matching value of the current object to be selected.
In this embodiment of the present invention, in a case where a weight value corresponding to each feature evaluation attribute is preset, determining a weight value corresponding to each feature evaluation attribute includes: determining the weight value of each characteristic evaluation attribute associated with the target service type from a pre-established corresponding relation table; the corresponding relation table comprises service types, characteristic evaluation attributes associated with the service types and weight values corresponding to the characteristic evaluation attributes.
The corresponding relation table refers to a one-to-one correspondence relation table of each service type, the characteristic evaluation attribute associated with each service type, and the weight value corresponding to each characteristic evaluation attribute.
Specifically, the weight value of each feature evaluation attribute associated with the target service type is determined from a pre-established correspondence table, so as to obtain a matching value based on the feature evaluation value and the corresponding weight value.
In the technical solution of the embodiment of the present invention, the determining the matching degree value of the current object to be selected includes: calling each characteristic evaluation value and a weight value corresponding to each characteristic evaluation attribute; obtaining a feature matching value based on each feature evaluation value and the corresponding weight value; and determining the matching degree value of the current object to be selected based on each characteristic matching value.
The feature matching value may represent a degree of matching between the object to be selected and the plurality of feature evaluation attributes. The attribute matching method is a matching value of each feature evaluation attribute for each feature evaluation value of the current object to be selected based on the result of processing each feature evaluation value and the corresponding weight value. Alternatively, it may be set here that the characteristic evaluation value is a result of multiplying the characteristic evaluation value and the corresponding weight value.
Specifically, a weight value corresponding to each feature evaluation value and each feature evaluation attribute is called, then a feature matching value is obtained based on each feature evaluation value and the corresponding weight value, each feature evaluation attribute corresponds to one feature matching value, and a matching degree value of the current object to be selected is determined based on a plurality of feature matching values.
And S140, determining the target object according to the matching value of each object to be selected.
Specifically, the matching degree values of the objects to be selected are compared to determine the target object. Optionally, the comparison method of the matching degree values of the objects to be selected may be to determine the object to be selected with the highest matching degree value as the target object, or to determine a preset number of objects to be selected with the highest matching degree values as the target object. The matching degree of the object to be selected and each characteristic evaluation attribute can be visually expressed through the matching degree value, and the target object can be selected from the object to be selected based on the matching degree value.
According to the technical scheme, at least two objects to be selected related to the target service type are determined, at least one characteristic evaluation attribute corresponding to the target service type is called, the characteristic evaluation value of the at least one characteristic evaluation attribute of each object to be selected is determined, the characteristic evaluation value of the current object to be selected and the weight value corresponding to each characteristic evaluation attribute are determined for each object to be selected, the matching degree of the current object to be selected is determined, and the target object is determined according to the matching degree of each object to be selected. According to the technical scheme of the embodiment of the invention, the target object is determined according to the characteristic evaluation value corresponding to the characteristic evaluation attribute and the weight value corresponding to the characteristic evaluation attribute aiming at the object to be selected in different service types, so that the accuracy of determining the target object is improved.
Example two
Fig. 2 is a schematic flow chart of a target object determination method provided in an embodiment of the present invention, which is a refinement of step 140 on the basis of an alternative to the foregoing embodiment, and a specific refinement process will be described in detail in the embodiment of the present invention. Technical terms identical or similar to those of the above embodiments will not be described again.
As shown in fig. 2, the target object determining method according to the embodiment of the present invention includes the following steps:
s210, determining at least two objects to be selected associated with the target service type.
S220, at least one characteristic evaluation attribute corresponding to the target service type is called, and a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected is determined.
S230, aiming at each object to be selected, determining a feature evaluation value of the current object to be selected and a weight value corresponding to each feature evaluation attribute, and determining a matching degree value of the current object to be selected.
S240, using the objects to be selected with high matching degree values in the preset number as the objects to be detected, and using at least one object to be selected except the objects to be detected as the objects to be processed.
Specifically, a preset number of objects to be selected with high matching values are obtained from the matching values corresponding to the objects to be selected. For example, the number of the objects to be selected is 100, and correspondingly, there are 100 matching degree values, and the preset number is 5. And acquiring 5 objects to be selected with high matching values from 100 matching values as objects to be detected, and taking the remaining 95 objects to be selected as objects to be processed.
S250, determining the number to be replaced of the detection objects to be replaced with the minimum matching value, and determining the number to be processed of the objects to be processed corresponding to the minimum matching value from the objects to be processed.
The object to be replaced is an object to be replaced in the object to be detected. The number of the to-be-replaced detection objects with the minimum matching degree value in the to-be-detected objects is used as the to-be-replaced number, for example, two to-be-replaced detection objects with the minimum matching degree value are provided, the minimum matching degree value is 0.8, and the to-be-replaced number is 2.
Specifically, after the number to be replaced of the detection object to be replaced with the smallest matching value is determined, the number to be processed of the object to be processed corresponding to the smallest matching value is determined from the objects to be processed, that is, the object to be selected with the same matching value as the detection object to be replaced is searched from the objects to be processed, and the number to be processed is determined.
And S260, if the number to be processed is a preset number threshold, taking each object to be detected as the target object.
Specifically, the preset number threshold includes 0. When the number of the to-be-selected objects is 0, it is indicated that the to-be-processed object having the same matching degree value as that of the to-be-replaced detection object is not found in each to-be-processed object, and at this time, each to-be-detected object can be used as a target object.
In the embodiment of the invention, if the number to be processed is not the preset number threshold, determining a set of objects to be replaced based on the detected object to be replaced and the object to be processed with the minimum matching value; determining target replacement detection objects with the same number as the objects to be replaced from the object set to be replaced; and determining the target object based on the target object to be detected and the object to be detected except the object to be replaced.
Specifically, when the number to be processed is not the preset number threshold, that is, the matching degree value of at least one object to be processed existing in each object to be processed is the same as the matching degree value of the object to be replaced. And determining the object to be replaced and the object to be processed with the minimum matching value as a set of objects to be replaced, and then determining the target replacement detection objects with the same number as the objects to be replaced from the set of objects to be replaced. And replacing the target replacing detection object with the detection object to be replaced, so that the target replacing detection object and the object to be detected except the detection object to be replaced are determined as the target object.
In this embodiment of the present invention, the determining, from the set of objects to be replaced, the target replacement detection object whose number is the same as that of the objects to be replaced includes: determining a target feature evaluation value of each object to be replaced in the set to be replaced when the weight value is the highest; and determining a first evaluation quantity corresponding to the highest target feature evaluation value, and if the first evaluation quantity is the same as the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the target replacement detection object.
Wherein the first evaluation number refers to the number of the belt replacement objects to which the target feature evaluation value is highest.
Specifically, the feature evaluation value with the highest weight value of the feature evaluation attribute of each object to be replaced in the set to be replaced is determined as the target feature evaluation value. The number of objects to be replaced whose target feature evaluation value is highest is determined as a first evaluation number. And comparing the first evaluation quantity with the quantity to be replaced, and when the first evaluation brush is the same as the quantity to be replaced, taking the object to be replaced with the highest target feature evaluation value as the target replacement detection object. The feature evaluation value with the highest weight value of the feature evaluation attributes is selected, the feature evaluation attribute with the highest importance degree can be placed in the leading position, and therefore the target replacement detection object obtained through calculation is more accurate and meets the requirements of users.
In the embodiment of the present invention, if the first evaluation number is not equal to the to-be-replaced number, there are two cases, where the first evaluation number is greater than the to-be-replaced number and the first evaluation number is smaller than the to-be-replaced number, and the following is specifically set forth:
if the first evaluation quantity is smaller than the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as a target replacement detection object, and taking each object to be replaced except the object to be replaced with the highest feature evaluation value as a first object to be processed; or if the first evaluation quantity is greater than the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the first object to be processed; calling a next weight value which is adjacent to the highest weight value in each first object to be processed, and detecting a second evaluation quantity which is the highest feature evaluation value of each first object to be processed and corresponds to the next weight value; and determining the target replacement detection object according to the first evaluation number, the second evaluation number, the first target replacement detection object and the number to be replaced.
Specifically, when the first evaluation number is smaller than the number to be replaced, the object to be replaced corresponding to the highest target feature evaluation value is taken as the target replacement detection object. Each object to be replaced other than the feature replacing object whose feature evaluation value is the highest is taken as the first object to be processed to determine a remaining number (the number to be replaced minus the first evaluation number) of target replacement detection objects from the first object to be processed. Specifically, a next weight value adjacent to the highest weight value in each first object to be processed is called, a second evaluation quantity with the highest feature evaluation value of each first object to be processed corresponding to the weight value is detected, and a target replacement detection object is determined according to the first evaluation quantity, the second evaluation quantity and the quantity to be replaced. For example, when the second evaluation number is equal to the difference between the number to be replaced and the first evaluation number, the first object to be processed and the object replacement detection object determined when the object feature evaluation value is the highest are determined to jointly constitute the number to be replaced of object replacement detection objects.
When the first evaluation quantity is larger than the substitute quantity, taking the object to be replaced corresponding to the highest target feature evaluation value as the first object to be processed, calling a next weight value adjacent to the highest weight value in each first object to be processed, determining a second evaluation quantity with the highest feature evaluation value of each first object to be processed corresponding to the next weight value, and determining the target substitute detection object according to the first evaluation quantity, the second evaluation quantity and the number to be replaced. For example, when the second evaluation number is equal to the number to be replaced, it is determined that the object whose feature evaluation value is the highest among the first objects to be processed is the target replacement detection object.
In this embodiment of the present invention, determining the target replacement detection object according to the first evaluation number, the second evaluation number, and the number to be replaced includes: if the second evaluation number is smaller than the difference between the number to be replaced and the first evaluation number, repeatedly executing to take the object to be replaced with the highest feature evaluation value as a target replacement detection object; or, if the second estimated number is larger than the difference between the number to be replaced and the first estimated number, repeatedly performing the operation of taking the object to be replaced with the highest feature evaluation value as the first object to be processed to determine the target replacement detection object from the first object to be processed; or, if the second evaluated number is equal to the difference between the number to be replaced and the first evaluated number, determining the first object to be processed as the target replacement detection object.
Specifically, when the second evaluation number is smaller than the difference between the number to be replaced and the first evaluation number, the replacement of the object to be replaced with the highest feature evaluation value as the target replacement detection object is repeatedly performed, and each object to be replaced other than the object to be replaced with the highest feature evaluation value is used as the first object to be processed, so that the remaining number of the target object to be replaced (the difference between the number to be replaced and the first evaluation number, and the difference is subtracted from the second evaluation number to obtain the difference as the remaining number) is determined based on the first object to be processed. When the second estimated number is larger than the difference between the number to be replaced and the first estimated number, the specific steps of determining the target replacement detection object from the first object to be processed by repeatedly performing the object to be replaced with the highest feature evaluation value as the first object to be processed are described in detail above. When the second evaluation number is equal to the difference between the number to be replaced and the first evaluation number, the first object to be processed is determined as the target replacement detection object. By the method, the target replacing detection object can be determined from the objects to be replaced, so that the target object can be determined based on the target replacing detection object and the objects to be detected except the objects to be replaced.
According to the technical scheme of the embodiment of the invention, at least one characteristic evaluation attribute corresponding to the target service type is called by determining at least two objects to be selected associated with the target service type, and the characteristic evaluation value of the at least one characteristic evaluation attribute of each object to be selected is determined. The method comprises the steps of determining feature evaluation values of current objects to be selected and weight values corresponding to feature evaluation attributes of the current objects to be selected, determining matching degree values of the current objects to be selected, taking the objects to be selected with high matching degree values in a preset number as the objects to be detected, taking at least one object to be selected except the objects to be detected as the objects to be processed, determining the number to be replaced of the objects to be replaced with the minimum matching degree, and determining the number to be processed of the objects to be processed corresponding to the minimum matching degree values from the objects to be processed. And when the number to be processed is a preset number threshold, taking each object to be detected as a target object. By the technical scheme of the embodiment of the invention, the matching degree of the current object to be selected is determined according to the characteristic evaluation value of the current object to be selected and the weight value corresponding to each characteristic evaluation attribute, so that the preset number of target objects are determined based on the matching degree, and the accuracy of determining the target objects is improved.
EXAMPLE III
Fig. 3 is a schematic diagram of a display interface of a target object determination system according to an embodiment of the present invention. The target object determination system of the embodiment of the present invention may implement the target object determination method of any of the above embodiments. The target object determining system comprises a plurality of service types, and can realize screening of objects in different service types to obtain the target object.
As shown in fig. 3, a target service type (hospital-level service type) is determined from the service types, and then a plurality of feature evaluation attributes (screening conditions) corresponding to the service types are determined. A feature evaluation value of at least one feature evaluation attribute of each object to be selected is determined. The objects to be selected comprise a hospital A, a hospital B, a hospital C and a hospital D, and the characteristic evaluation attributes comprise a characteristic evaluation attribute A, a characteristic evaluation attribute B, a characteristic evaluation attribute C, a characteristic evaluation attribute D and the like. The feature evaluation attribute for each hospital has a corresponding feature evaluation value, such as 0.40 for the feature evaluation attribute a of hospital a.
Each feature evaluation attribute is provided with a corresponding weight value (not shown in fig. 3), and a matching value of each hospital can be obtained based on the feature evaluation value of the feature evaluation attribute and the corresponding weight value. The feature evaluation values are represented by f (1), f (2), f (3), and.. f (n), and there are n feature evaluation values (scores of feature evaluation attributes). And setting weight values corresponding to the characteristic evaluation values as a1, a2 and an in sequence, wherein a1+ a2+. + an < 1. The importance degree of the feature evaluation attribute is divided by adding a weight value to the feature evaluation value of the feature evaluation attribute. Thus, assuming that the matching score for hospital a is s (a), s (a) ═ f (1) × a1+ f (2) × a2+. f (n) × an. The target object (target hospital) is determined by a matching score, with higher matching score indicating a higher hospital grade. Assuming that a target object needs to be acquired, when s (a) ═ s (b) ═ s (c) ((c)), the feature evaluation value of the corresponding feature evaluation attribute is acquired with the highest weight, and then the feature evaluation value is determined to be the highest from among these feature evaluation values, and the hospital corresponding to the feature evaluation value is the target hospital. If the characteristic evaluation values are all the same, determining the next weighted value with the highest weight, then determining each characteristic evaluation value corresponding to the weighted value, determining the evaluation value to be the highest from the characteristic evaluation values, if the evaluation values are all the same, repeatedly executing the steps of obtaining the next weighted value of the current weighted value, determining the highest evaluation value in the characteristic evaluation values, and determining the hospital corresponding to the highest evaluation value as the target hospital.
By the technical scheme of the embodiment of the invention, the objects with different service types are screened, the target object is determined, and the efficiency and the accuracy of determining the target object are improved.
Example four
Fig. 4 is a schematic structural diagram of a target object determining apparatus according to an embodiment of the present invention, where the target object determining apparatus according to the embodiment of the present invention can execute a target object determining method according to any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method. The device includes: a to-be-selected object determining module 410, a feature evaluation value determining module 420, a matching degree value determining module 430, and a target object determining module 440; wherein:
a to-be-selected object determining module 410, configured to determine at least two to-be-selected objects associated with the target service type; a feature evaluation value determining module 420, configured to retrieve at least one feature evaluation attribute corresponding to the target service type, and determine a feature evaluation value of the at least one feature evaluation attribute of each object to be selected; a matching degree value determining module 430, configured to determine, for each object to be selected, a feature evaluation value of a current object to be selected and a weight value corresponding to each feature evaluation attribute, and determine a matching degree value of the current object to be selected; and the target object determining module 440 is configured to determine a target object according to the matching value of each object to be selected.
Further, the matching degree value determining module 430 includes:
the weight value determining submodule is used for determining the weight value of each characteristic evaluation attribute associated with the target service type from a pre-established corresponding relation table; the corresponding relation table comprises service types, characteristic evaluation attributes associated with the service types and weight values corresponding to the characteristic evaluation attributes.
Further, the matching degree value determining module 430 includes:
the matching degree value determining submodule is used for calling each characteristic evaluation value and a weight value corresponding to each characteristic evaluation attribute; obtaining a feature matching value based on each feature evaluation value and the corresponding weight value; and determining the matching degree value of the current object to be selected based on each characteristic matching value.
Further, the target object determination module 440 includes:
the object to be processed determining submodule is used for taking the object to be selected with a high matching degree value in the preset quantity as the object to be detected, and taking at least one object to be selected except the object to be detected as the object to be processed; the to-be-processed number determining submodule is used for determining the to-be-replaced number of the to-be-replaced detection objects with the minimum matching value and determining the to-be-processed number of the to-be-processed objects corresponding to the minimum matching value from the to-be-processed objects; and the first target object determining submodule is used for taking each object to be detected as the target object if the quantity to be processed is a preset quantity threshold value.
Further, the apparatus comprises: a to-be-replaced object set determining module, configured to determine, if the to-be-processed number is not a preset number threshold, a to-be-replaced object set based on the to-be-replaced detection object and the to-be-processed object with the smallest matching value; a target replacement detection object determining module, configured to determine, from the set of objects to be replaced, target replacement detection objects whose number is the same as that of the objects to be replaced; and the second target object determination module is used for determining the target object based on the target object to be detected and the object to be detected except the object to be replaced.
Further, the target replacement detection object determination module includes:
a target feature evaluation value determining submodule, configured to determine a target feature evaluation value of each object to be replaced in the set to be replaced when the weight value is highest; and the target replacement detection object determining submodule is used for determining a first evaluation number corresponding to the highest target feature evaluation value, and if the first evaluation number is the same as the number to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the target replacement detection object.
Further, the apparatus comprises:
a first evaluation quantity comparison module, configured to, if the first evaluation quantity is smaller than the to-be-replaced quantity, take the to-be-replaced object corresponding to the highest target feature evaluation value as a target replacement detection object, and take each to-be-replaced object except the to-be-replaced object with the highest feature evaluation value as a first to-be-processed object; or if the first evaluation quantity is greater than the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the first object to be processed;
a second evaluation quantity detection module, configured to retrieve a next weight value that is highest and adjacent to the weight value in each first object to be processed, and detect a second evaluation quantity that is highest in a feature evaluation value of each first object to be processed and corresponds to the next weight value;
and the target replacement detection object determining module is used for determining the target replacement detection object according to the first evaluation number, the second evaluation number and the number to be replaced.
Further, the target replacement detection object determination module includes:
a target replacement detection object determining sub-module configured to, if the second evaluation number is smaller than a difference between the number to be replaced and the first evaluation number, repeatedly perform, as a target replacement detection object, an object to be replaced whose feature evaluation value is the highest; or, if the second estimated number is larger than the difference between the number to be replaced and the first estimated number, repeatedly performing the operation of taking the object to be replaced with the highest feature evaluation value as the first object to be processed to determine the target replacement detection object from the first object to be processed; or, if the second evaluated number is equal to the difference between the number to be replaced and the first evaluated number, determining the first object to be processed as the target replacement detection object.
According to the technical scheme, at least two objects to be selected related to the target service type are determined, at least one characteristic evaluation attribute corresponding to the target service type is called, the characteristic evaluation value of the at least one characteristic evaluation attribute of each object to be selected is determined, the characteristic evaluation value of the current object to be selected and the weight value corresponding to each characteristic evaluation attribute are determined for each object to be selected, the matching degree of the current object to be selected is determined, and the target object is determined according to the matching degree of each object to be selected. According to the technical scheme of the embodiment of the invention, the target object is determined according to the characteristic evaluation value corresponding to the characteristic evaluation attribute and the weight value corresponding to the characteristic evaluation attribute aiming at the object to be selected in different service types, so that the accuracy of determining the target object is improved.
It should be noted that, the modules and sub-modules included in the apparatus are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the embodiment of the present invention.
EXAMPLE five
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. FIG. 5 illustrates a block diagram of an exemplary device 50 suitable for use in implementing embodiments of the present invention. The device 50 shown in fig. 5 is only an example and should not bring any limitation to the function and scope of use of the embodiments of the present invention.
As shown in FIG. 5, device 50 is embodied in a general purpose computing device. The components of the device 50 may include, but are not limited to: one or more processors or processing units 501, a system memory 502, and a bus 503 that couples the various system components (including the system memory 502 and the processing unit 501).
The system memory 502 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)504 and/or cache memory 505. The device 50 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 506 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 503 by one or more data media interfaces. Memory 502 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 508 having a set (at least one) of program modules 507 may be stored, for instance, in memory 502, such program modules 507 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 507 generally perform the functions and/or methodologies of embodiments of the invention as described herein.
The processing unit 501 executes various functional applications and data processing, for example, to implement the target object determination method provided by the embodiment of the present invention, by executing the program stored in the system memory 502.
EXAMPLE six
Embodiments of the present invention also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method for target object determination, the method comprising:
determining at least two objects to be selected associated with the target service type; calling at least one characteristic evaluation attribute corresponding to the target service type, and determining a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected; determining a feature evaluation value of a current object to be selected and a weight value corresponding to each feature evaluation attribute for each object to be selected, and determining a matching degree value of the current object to be selected; and determining the target object according to the matching value of each object to be selected.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. 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 (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, 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.
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, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like 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).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (12)
1. A target object determination method, comprising:
determining at least two objects to be selected associated with the target service type;
calling at least one characteristic evaluation attribute corresponding to the target service type, and determining a characteristic evaluation value of at least one characteristic evaluation attribute of each object to be selected;
determining a feature evaluation value of a current object to be selected and a weight value corresponding to each feature evaluation attribute for each object to be selected, and determining a matching degree value of the current object to be selected;
and determining the target object according to the matching value of each object to be selected.
2. The method of claim 1, wherein determining a weight value corresponding to each feature evaluation attribute comprises:
determining the weight value of each characteristic evaluation attribute associated with the target service type from a pre-established corresponding relation table;
the corresponding relation table comprises service types, characteristic evaluation attributes associated with the service types and weight values corresponding to the characteristic evaluation attributes.
3. The method of claim 1, wherein the determining the matching degree value of the current object to be selected comprises:
calling each characteristic evaluation value and a weight value corresponding to each characteristic evaluation attribute;
obtaining a feature matching value based on each feature evaluation value and the corresponding weight value;
and determining the matching degree value of the current object to be selected based on each characteristic matching value.
4. The method according to claim 1, wherein the determining a target object according to the matching degree value of each object to be selected comprises:
taking the objects to be selected with high matching degree values in the preset quantity as objects to be detected, and taking at least one object to be selected except the objects to be detected as the objects to be processed;
determining the number to be replaced of the detection objects to be replaced with the minimum matching value, and determining the number to be processed of the objects to be processed corresponding to the minimum matching value from the objects to be processed;
and if the quantity to be processed is a preset quantity threshold value, taking each object to be detected as the target object.
5. The method of claim 4, further comprising:
if the number to be processed is not the preset number threshold, determining a set of objects to be replaced based on the objects to be replaced and the detected objects to be replaced with the minimum matching values;
determining target replacement detection objects with the same number as the objects to be replaced from the object set to be replaced;
and determining the target object based on the target object to be detected and the object to be detected except the object to be replaced.
6. The method according to claim 5, wherein the determining the target replacement detection objects with the same number as the objects to be replaced from the set of objects to be replaced comprises:
determining a target feature evaluation value of each object to be replaced in the set to be replaced when the weight value is the highest;
and determining a first evaluation quantity corresponding to the highest target feature evaluation value, and if the first evaluation quantity is the same as the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the target replacement detection object.
7. The method of claim 6, further comprising:
if the first evaluation quantity is smaller than the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as a target replacement detection object, and taking each object to be replaced except the object to be replaced with the highest feature evaluation value as a first object to be processed; or if the first evaluation quantity is greater than the quantity to be replaced, taking the object to be replaced corresponding to the highest target feature evaluation value as the first object to be processed;
calling a next weight value which is adjacent to the highest weight value in each first object to be processed, and detecting a second evaluation quantity which is the highest feature evaluation value of each first object to be processed and corresponds to the next weight value;
and determining the target replacement detection object according to the first evaluation quantity, the second evaluation quantity and the quantity to be replaced.
8. The method of claim 7, wherein determining the target replacement detection object according to the first evaluated number, the second evaluated number, and the number to be replaced comprises:
if the second evaluation number is smaller than the difference between the number to be replaced and the first evaluation number, repeatedly executing to take the object to be replaced with the highest feature evaluation value as a target replacement detection object; or,
if the second evaluation number is larger than the difference between the number to be replaced and the first evaluation number, repeatedly executing the step of taking the object to be replaced with the highest feature evaluation value as the first object to be processed so as to determine the target replacement detection object from the first object to be processed; or,
and if the second evaluation quantity is equal to the difference between the quantity to be replaced and the first evaluation quantity, determining the first object to be processed as a target replacement detection object.
9. The method of claim 1, wherein the business types include hospital level business types, hospital department business types, doctor level business types, store business types, and item business types.
10. A target object determination apparatus, comprising:
the device comprises a to-be-selected object determining module, a to-be-selected object determining module and a selecting module, wherein the to-be-selected object determining module is used for determining at least two to-be-selected objects associated with a target service type;
a feature evaluation value determining module, configured to invoke at least one feature evaluation attribute corresponding to the target service type, and determine a feature evaluation value of the at least one feature evaluation attribute of each object to be selected;
the matching degree value determining module is used for determining the feature evaluation value of the current object to be selected and the weight value corresponding to each feature evaluation attribute aiming at each object to be selected, and determining the matching degree value of the current object to be selected;
and the target object determining module is used for determining the target object according to the matching value of each object to be selected.
11. An electronic device, characterized in that the electronic device comprises:
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 a target object determination method as claimed in any one of claims 1-9.
12. A storage medium containing computer executable instructions for performing the target object determination method of any one of claims 1-9 when executed by a computer processor.
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