CN106708872B - Method and device for identifying associated object - Google Patents
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- CN106708872B CN106708872B CN201510784684.3A CN201510784684A CN106708872B CN 106708872 B CN106708872 B CN 106708872B CN 201510784684 A CN201510784684 A CN 201510784684A CN 106708872 B CN106708872 B CN 106708872B
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Abstract
The application discloses a method for identifying a related object, which is used for solving the problem that the related object of a reference object in the prior art is low in identification accuracy. The method comprises the following steps: determining a criterion for identifying an associated object of the reference object; the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information; obtaining characteristic information of an object to be identified; and judging whether the characteristic information of the object to be recognized is matched with the judgment reference, and if so, determining the object to be recognized as the associated object of the reference object. The application also discloses a device for identifying the associated object.
Description
Technical Field
The present application relates to the field of big data technologies, and in particular, to a method and an apparatus for identifying a related object.
Background
With the development of information technology, objects entering the description domain of people are generally distinguished by the concept of "objects". Different objects (object entities) are different in expression form, characteristic attribute, and the like. However, it is common for each object to have both an independence trait that distinguishes it from other objects and a relevance trait associated with other objects. For example, PC terminals that are different objects are generally independent of each other, but they can be associated with each other through a network. Since there is an association between different objects, in some cases, other objects associated with an object may be identified by the object by virtue of such association. Here, an object serving as a reference for identifying a related object may be referred to as a reference object, and another object identified by the association relationship may be referred to as a related object.
The strength of the association relationship between the reference object and the associated object and the manner of utilizing the association relationship affect whether the identified associated object is accurate, that is, the associated object identified by the weak association relationship or the improper manner of utilizing the association relationship may not be the associated object desired by the user. In order to improve the accuracy of identifying the related object, in the related art, the related object of the reference object is mainly identified by determining whether or not certain information of the reference object completely matches with certain information of the object to be identified (i.e., the object that may become the related object). However, in such a "single information complete matching" manner, the association relationship between the reference object and the associated object may not be fully utilized, resulting in a low accuracy of the recognition result.
Disclosure of Invention
The embodiment of the application provides an identification method of a related object, which is used for solving the problem that the related object of a reference object in the prior art is low in identification accuracy.
The embodiment of the application further provides a device for identifying the associated object, which is used for solving the problem that the accuracy of identifying the associated object of the reference object is low in the prior art.
The embodiment of the application adopts the following technical scheme:
a method for identifying an associated object, comprising:
determining a judgment reference for identifying a related object of a reference object, wherein the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information; obtaining characteristic information of an object to be identified; and judging whether the characteristic information of the object to be recognized is matched with the judgment reference, and if so, determining the object to be recognized as the associated object of the reference object.
An apparatus for identifying an associated object, comprising:
a criterion specifying unit that specifies a criterion for identifying an object associated with the reference object; the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information; the device comprises a to-be-identified object characteristic information obtaining unit, a recognition unit and a recognition unit, wherein the to-be-identified object characteristic information obtaining unit is used for obtaining characteristic information of an object to be identified; and the identification unit is used for judging whether the characteristic information of the object to be identified is matched with the judgment reference or not, and if so, determining the object to be identified as the related object of the reference object.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
by adopting the method provided by the embodiment of the application, whether the object to be identified is the related object of the reference object can be judged according to the judgment standard of the related object, and the judgment standard is determined according to the at least two pieces of feature information of the reference object and the preset deviation range of the feature information, so compared with the mode that whether the object to be identified is the related object of the reference object is judged mainly by judging whether the certain information of the reference object is completely consistent with the certain information of the object to be identified in the prior art, the judgment standard of the scheme provided by the application covers more feature information and is more reasonable, and higher identification result accuracy can be achieved when the relevance between each piece of information of the reference object and each piece of information of the object to be identified (which is actually the related object) is weaker.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart illustrating a specific implementation of a method for identifying an associated object according to an embodiment of the present application;
fig. 2 is a schematic flowchart illustrating a specific implementation of a method for identifying members of a specified group according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an apparatus for identifying an associated object according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Example 1
The embodiment of the application provides an identification method of a related object, which is used for solving the problem that the related object of a reference object in the prior art is low in identification accuracy.
The execution main body of the method for identifying the related object provided by the embodiment of the application can be at least one of terminal equipment such as a mobile phone, a tablet Computer and a Personal Computer (PC). The execution subject of the method may be an Application (APP) installed in the terminal device, or may be a server. The execution main body does not constitute a limitation to the present application, and for convenience of description, the embodiment of the present application is described by taking the example that the execution main body is an APP installed on a mobile phone.
The specific implementation flow diagram of the method is shown in fig. 1, and mainly comprises the following steps:
the judgment reference is determined according to at least two pieces of characteristic information of the reference object.
In order to identify the object to be identified, which is weakly associated with the reference object, by using the determined criterion, in one embodiment, the criterion may be determined according to at least two pieces of feature information of the reference object and a preset deviation range of the feature information. For example, taking a reference object as a person a who enters a hotel, two pieces of feature information of the reference object are: the check-in time is 9 months and 15, and the address of the check-in hotel is in the Hai lake district of Beijing; assume that the preset deviation range of the stay-in time is: the check-in time of the reference object is not more than fifteen days before and after, and the preset check-in place deviation range is as follows: if the number of the reference object is not more than the preset deviation range of the two pieces of information and the characteristic information of the reference object, the judgment reference of the related object of the reference object can be determined as follows: the stay time in September and the place where the hotel stays are Beijing.
In this embodiment of the present application, the implementation manner of step 11 may include: directly obtaining the generated judgment reference; or, the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information.
In the following, taking a reference object as the user a and characteristic information of the reference object as hotel check-in information (hereinafter referred to as check-in information) of the user a, how to determine a criterion of the related object of the user a according to at least two pieces of check-in information of the reference object and a preset deviation range of the characteristic information is described as an example:
it should be noted that the check-in information of the hotel personnel may be: check-in time, name of the hotel checked-in, check-out time, geographic location of the hotel checked-in or star rating of the hotel checked-in, etc.
In the related art, a hotel often needs a check-in person to provide an identification number and a mobile phone number, and upload the information, the check-in time and the check-out time of the check-in person, and characteristic information of the check-in hotel (such as the name of the hotel, the geographic position of the hotel, and the star level of the hotel) to an "check-in information management server" for corresponding storage. The check-in information management server is a big data server, namely a server capable of providing big data support. So-called big data support, such as may include but is not limited to: and data query, download, mining and other services based on big data stored in a database are provided.
In the embodiment of the application, the user can use the APP to send the check-in information acquisition request of the user a to the check-in information management server, so as to obtain the check-in information of the user a sent by the check-in information management server in response to the check-in information acquisition request of the user a. It should be noted that the check-in information obtaining request of the user a may include an identifier of the user a (e.g., an identification number of the user a), and the "check-in information management server" may query, through the identifier, check-in information of the user a that is stored in correspondence with the identifier.
After the server inquires the check-in information of the user A, at least two pieces of check-in information can be selected from the inquired check-in information, and the judgment reference of the related object of the user A is determined according to the at least two pieces of check-in information and the preset deviation range of the characteristic information. Specifically, when the server queries the check-in information of the reference object, the check-in information includes: when the check-in time is 9 month 10, the check-out time is 9 month 12, and the geographic location of the check-in hotel is the sunny region in beijing city, the determination criterion for determining the associated object of the user a may be: the check-in time was in month 9 and the check-in hotel geographic location was in Beijing City.
In the embodiment of the present application, in consideration of the problem that the identification accuracy may be low when identifying the related object of the reference object according to only one piece of check-in information of the reference object, in an implementation manner, the embodiment of the present application may use at least two different types of check-in information of the reference object as the determination reference; alternatively, the determination criterion of the related object may be determined based on preset deviation ranges of at least two different types of occupancy information and feature information of the reference object.
Since the decision criterion setting rule generally varies with the actual demand, the foregoing description is only exemplary, and the specific content is not limited.
In an embodiment, when the implementation manner of step 11 is to directly obtain the already generated determination criterion, the manner of generating the determination criterion may refer to the foregoing, and is not described herein again. The execution agent that generates the determination criterion may be, for example, a server.
for example, the feature information of the object to be identified provided by the server may be obtained by sending an object to be identified information obtaining request to the server.
Generally, the request may often include an identifier of the object to be recognized, so that the server may find the feature information of the object to be recognized according to the identifier of the object to be recognized.
In an implementation manner, the server may send the identifier of the object to be identified to the APP for display, so that the user may select the identifier from the displayed identifiers through the APP (the selected identifier is the identifier of the object to be identified), and thus the APP may send a personnel information acquisition request including the identifier of the object to be identified to the check-in information management server.
It should be noted that the server is often a big data server, and the big data server is often used to manage and store massive data. At this time, if the data stored in the big data server is acquired without being distinguished, a large amount of processing time is consumed, that is, the efficiency of acquiring the feature information of the object to be identified is low, and a large amount of resources are consumed.
In order to avoid the above problem, in an embodiment, a specific implementation manner of step 12 in this embodiment may include: determining the identification of an object to be identified; and acquiring the characteristic information of the object to be recognized from the characteristic information of the object stored by the big data server according to the identifier of the object to be recognized and the type of the characteristic information corresponding to the judgment reference.
The type of feature information corresponding to the determination criterion is a type of feature information of a reference object for specifying the determination criterion. For example, the type of feature information corresponding to the criterion may be determined by analyzing the criterion or by acquiring a type of feature information of a reference object stored in advance and mapped to the criterion. For example, if the determination criterion is determined according to the arrival time of the reference object, the feature information corresponding to the determination criterion is the arrival time, and the type of the feature information corresponding to the determination criterion is time type information.
It should be noted that, determining the identifier of the object to be recognized may include: obtaining an identification filtering condition by the APP; and the APP determines the object identification meeting the identification filtering condition from the object identifications stored in the big data server according to the identification filtering condition. Specifically, the APP may send the identifier filtering condition to a big data server, and obtain an identifier of the object to be identified, which is returned by the server according to the condition and satisfies the condition. The condition may be set locally by the APP.
After receiving the object identifier to be recognized which is returned by the big data server according to the identifier filtering condition and meets the condition, the APP can display the received object identifier to be recognized. And subsequently, after a selection instruction for the displayed object identifier to be recognized is received, the selected object identifier to be recognized and the type of the characteristic information corresponding to the judgment reference of the associated object can be sent to the big data server, so that the big data server is triggered to send the characteristic information of the selected object to be recognized to the APP according to the selected object identifier to be recognized and the type.
And step 13, judging whether the characteristic information of the object to be recognized obtained by executing the step 12 is matched with the judgment reference determined by executing the step 11, and if so, determining the object to be recognized as the related object of the reference object.
For example, the specific implementation manner of step 13 may include: and respectively judging whether each piece of information of the object to be identified meets a corresponding judgment reference, and determining the object to be identified as a related object of the reference object when the obtained judgment result meets a set condition.
Considering whether the different types of feature information satisfy the determination criterion, the determination result of whether the object to be recognized is the related object of the reference object has different influences. Therefore, in order to reflect the influence in the determination result, so as to make the determination result more accurate, in the embodiment of the present application, different determination result weights may be set for different types of feature information, respectively, and when an obtained determination result satisfies a set condition, the object to be identified is determined as the related object of the reference object. For example, the specific implementation may include: judging whether the obtained judgment result meets the set condition or not according to the obtained judgment result and the judgment result weight set aiming at the different types of feature information; and when the judgment result is yes, determining the object to be identified as the related object of the reference object.
For example, the objects to be recognized may be scored according to the obtained determination results and the determination result weights set for the different types of feature information, so as to obtain the determination result scores of the objects to be recognized, and further, according to the determination result scores of the objects to be recognized, whether the determination result scores of the objects to be recognized are higher than a preset score is determined, and when the determination result is yes, the objects to be recognized are determined as the related objects of the reference object.
For example, assume that the following conditions hold:
1. in step 11, the obtained criteria for determining the related object are: "check-in time in august" and "check-in hotel address in city B";
2. by executing step 12, the obtained entrance information feature items of the object a to be identified are: "check-in time is 9 months and 5" and "check-in hotel address is in city B";
3. by executing step 12, the obtained entrance information feature items of the object B to be recognized are: "the check-in time is 8 months and 5 # and" the check-in hotel address is in B city ";
4. setting that when each check-in information characteristic item of the personnel to be identified is compared with a judgment standard, and the obtained corresponding comparison result is 'in accordance with the judgment standard', adding one point to the judgment result of the personnel to be identified;
5. setting the weight of the judgment result of the check-in time to be 2; the weight of the determination result of the geographic position of the check-in hotel is set to be 1.
6. And when the judgment result score of the object to be recognized is higher than 2 minutes or not, judging that the judgment result meets the set condition.
Then, by respectively determining whether each check-in information of the object a to be recognized meets the corresponding determination criterion, it can be obtained that: the check-in time of the object A to be recognized does not accord with the judgment reference, and the geographic position of the hotel meets the judgment reference. The score of the judgment result of the object A to be identified is as follows: if the score of the determination result of the object a to be recognized is less than 2 points, that is, the determination result of the object a to be recognized does not satisfy the set condition, it may be determined that the object a to be recognized is not the related object of the reference object.
Similarly, by respectively judging whether each check-in information of the object B to be recognized meets the corresponding judgment criterion, it can be obtained that: the check-in time and check-in time of the object B to be recognized accord with the judgment reference, and the geographic position of the hotel to be checked also accord with the judgment reference. The score of the determination result of the object B to be recognized is: if the score of the determination result of the object B to be recognized is higher than 2, that is, the determination result of the object B to be recognized satisfies the set condition, the object B to be recognized may be determined as the related object of the reference object if 1 × 2+1 × 1 is 3.
By adopting the method provided by embodiment 1 of the present application, it is supported that whether the object to be recognized is the related object of the reference object is determined according to the determination criterion of the related object, and the determination criterion is determined according to the at least two pieces of feature information of the reference object and the preset deviation range of the feature information, so compared with the mode that whether the object to be recognized is the related object of the reference object is determined mainly by determining whether a piece of information of the reference object is completely consistent with a piece of information of the object to be recognized in the prior art, the determination criterion of the scheme provided by the present application covers more feature information and is more reasonable, so that when the relevance between each piece of information of the reference object and each piece of information of the object to be recognized (which is actually the related object) is weak, a higher accuracy of the recognition result can be achieved.
It should be noted that the execution subjects of the steps of the method provided in embodiment 1 may be the same device, or different devices may be used as the execution subjects of the method. For example, the execution subject of steps 11 and 12 may be device 1, and the execution subject of step 13 may be device 2; for another example, the execution subject of step 11 may be device 1, and the execution subjects of step 12 and step 13 may be device 2; and so on.
Example 2
The embodiment of the application provides a method for identifying designated crowd members, which is used for solving the problem that the identification accuracy of the designated crowd members in the prior art is low. The specific implementation flow diagram of the method is shown in fig. 2, and mainly comprises the following steps:
It should be noted that the "identification APP" may be connected to the check-in information management server through the internet, so that check-in information of the hotel check-in persons may be queried through the APP, and persons belonging to members of the designated group may be identified from the persons to be identified through the APP, and the specific identification method is described in embodiment 1, and is not described herein again.
For example, suppose a certain member of the specified crowd is user B, and according to the name or identification number of the user B, the server may be queried about the hotel stay information of the user B in the near future. For example, in the last month, the user B has checked in 3 hotels in B city, and the check-in time in the three hotels is 9 month 1, 9 month 10 and 9 month 23, respectively.
It should be further noted that, in order to avoid leakage of the information of the check-in personnel, "the suspected identification APP" provided in the embodiment of the present application may perform identity authentication (for example, fingerprint authentication, voice authentication, password authentication, and the like) on the user, and after the identity authentication passes, the APP may be used.
By executing step 21, the check-in information of the user B in the specified group that has been determined is obtained as follows: the user B checked in a hotel in the city B in 9/10, and the deviation range of the set characteristic information is as follows: the check-in time and the check-in time of the user B are not more than 5 days before and after; the place of check-in is within 1 km around the place of check-in of the user B. Then the "identifying APP" may determine the check-in time between 9 months 5 and 9 months 15 and the geographic location of the check-in hotel is within 1 km of the city B as the determination criterion of the designated crowd member.
And step 23, determining the identification of the person to be recognized meeting the filtering condition of the identification of the person to be recognized from the stored identification of the person to be recognized according to the filtering condition of the identification of the person to be recognized, and searching the person to be recognized according to the determined identification of the person to be recognized meeting the filtering condition of the identification of the person to be recognized.
For example, "identify APP" may set the filtering condition of the person identifier to be identified as: and only acquiring the check-in information of the personnel checking in the hotel in the city B in the month of September, determining the identification of the personnel to be identified meeting the condition according to the filtering condition, and searching the personnel to be identified who check in the hotel in the city B in the month of September according to the identification of the personnel to be identified meeting the condition.
Assume that by performing step 23, the determined person to be identified is: a person a to be identified, a person b to be identified, and a person c to be identified.
And 24, acquiring the check-in information of the personnel to be identified.
For example, by performing step 22, the type of feature information corresponding to the determination criterion for specifying the crowd member is determined as follows: the check-in time and the geographic location of the check-in hotel.
So that the person to be identified is determined by performing step 23 as: the person a to be identified, the person b to be identified, and the person c to be identified are taken as examples.
By performing step 24, one can obtain:
the check-in information of the person a to be identified is as follows: the check-in time is No. 9 month and No. 1, and the position of the hotel is B;
the check-in information of the person b to be identified is as follows: the check-in time is No. 9 and 10, and the position of the check-in hotel is B;
the check-in information of the person c to be identified is as follows: the check-in time is No. 9 and 25, and the position of the check-in hotel is B.
And 25, judging whether the person to be identified belongs to the designated crowd member or not by judging whether the check-in information of the person to be identified is matched with the judgment standard of the designated crowd member or not.
Specifically, each item of attendance information of the person to be identified can be scored according to the judgment result of the attendance information included in the person to be identified, the scoring results of each item of attendance information of the person to be identified are added to obtain a result score of the person to be identified, and if the result score of the person to be identified is higher, the possibility that the person to be identified is a member of the designated group is higher.
It should be further noted that, in order to identify the designated members of the group more accurately according to the check-in information, different weights may be set for different types of check-in information according to different types of check-in information in the embodiments of the present application.
For example, if the judgment result obtained by comparing each item of check-in information of the person to be recognized with the judgment reference is a match, a point is added to the judgment result of the person to be recognized, and the type of the check-in information is set as: the weight of the judgment result of the check-in time is 2, and the type of the check-in information is as follows: the weight of the judgment result weight of the geographic position of the hospitalized hotel is 1.
Then, whether the check-in information of the person a to be identified meets the corresponding judgment reference or not is judged respectively, so that the check-in time of the person a to be identified does not meet the judgment reference is obtained, and the geographic position of the hotel to be checked meets the judgment reference, and then according to the obtained judgment results and the judgment result weights set for different types of check-in information, the result score of the person a to be identified is obtained as follows: 2 × 0+1 × 1 is 1 point.
Obtaining the check-in time of the person b to be identified according to the judgment standard by respectively judging whether the check-in information of the person b to be identified accords with the corresponding judgment standard, and obtaining the result score of the person b to be identified according to the obtained judgment results and the judgment result weight set aiming at different types of check-in information, wherein the check-in time of the person b to be identified accords with the judgment standard, and the geographic position of the hotel to be checked also accords with the judgment standard: 2 × 1+1 × 1 is 3 points.
Whether the check-in information of the person c to be identified accords with the corresponding judgment standard or not is judged respectively, the fact that the check-in time of the person c to be identified does not accord with the judgment standard is obtained, and the geographic position of the hotel to be checked accords with the judgment standard, and according to the obtained judgment results and judgment result weights set aiming at different types of check-in information, the result score of the person c to be identified is as follows: 2 × 0+1 × 1 is 1 point.
And comparing the result scores of the person a to be identified, the person b to be identified and the person c to be identified, so that the possibility that the person b to be identified is the member of the designated group is the highest.
By adopting the method provided by embodiment 2 of the present application, since it is possible to support the judgment of whether the object to be recognized is the related object of the reference object according to the judgment criterion of the related object, and the judgment criterion is determined according to the at least two pieces of feature information of the reference object and the preset deviation range of the feature information, compared with the method of judging whether the object to be recognized is the related object of the reference object mainly by judging whether a piece of information of the reference object is completely consistent with a piece of information of the object to be recognized in the prior art, the judgment criterion of the scheme provided by the present application covers more feature information and is more reasonable, so that when the relevance between each piece of information of the reference object and each piece of information of the object to be recognized (which is substantially the related object) is weak, the accuracy of the recognition result can be higher.
Example 3
The embodiment of the application provides a device for identifying a related object, which is used for solving the problem that the related object of a reference object in the prior art is low in identification accuracy. The specific structural diagram of the device is shown in fig. 3, and includes a determination criterion determining unit 31, an object feature information obtaining unit 32 to be recognized, and a recognition unit 33.
Wherein the decision criterion determining unit 31 is configured to: a decision criterion for determining a related object that identifies the reference object; the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information;
an object-to-be-recognized feature information obtaining unit 32 for obtaining feature information of an object to be recognized;
an identification unit 33 for: and the characteristic information is used for judging whether the characteristic information of the object to be identified is matched with the judgment reference, and if so, determining the object to be identified as the associated object of the reference object.
In one embodiment, the object feature information obtaining unit 32 is configured to: determining the identification of an object to be identified; and acquiring the characteristic information of the object to be recognized from the characteristic information of the object stored by the big data server according to the identifier of the object to be recognized and the type of the characteristic information corresponding to the judgment reference.
In one embodiment, the object information to be identified obtaining unit 32 is configured to: obtaining an identification filtering condition; and according to the identification filtering condition, determining the object identification meeting the identification filtering condition from the object identifications stored in the big data server.
In one embodiment, the decision criterion determining unit 31 is configured to: and determining each judgment standard according to at least two different types of feature information of the standard object and the judgment standard setting rules respectively corresponding to the at least two different types of feature information.
In one embodiment, the identification unit 33 is configured to: respectively judging whether each characteristic information of the object to be identified accords with a corresponding judgment standard; and when the obtained judgment result meets the set condition, determining the object to be identified as the related object of the reference object.
In one embodiment, the identifying unit 33 is configured to determine whether the obtained determination result satisfies a set condition according to the obtained determination result and a determination result weight set for different types of feature information; and when the judgment result is yes, determining the object to be identified as the related object of the reference object.
In one embodiment, the reference object is a member of a specified population; the information is a check-in information characteristic item; the at least two characteristic information items comprise at least two of the following check-in information characteristic items:
the time of check-in;
the time of returning to the room;
a name of the hotel checked in;
a geographic location of the check-in hotel;
star class for hospitalized hotels.
With the above apparatus provided in embodiment 3 of the present application, it is possible to support determination of whether or not an object to be recognized is an object to be recognized associated with a reference object according to a criterion of the object to be recognized, where the criterion is determined according to at least two pieces of feature information of the reference object and a preset deviation range of the feature information, and therefore, compared with a method in which determination of whether or not an object to be recognized is mainly performed by determining whether or not a piece of information of the reference object completely matches a piece of information of the object to be recognized in the related art, the criterion of the scheme provided in the present application covers more feature information and is more reasonable, so that when the relevance between each piece of information of the reference object and each piece of information of the object to be recognized (substantially, the object to be recognized) is weak, a higher accuracy of a recognition result can be achieved.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store characteristic information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (8)
1. A method for identifying a related object, comprising:
determining a judgment reference for identifying a related object of a reference object, wherein the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information;
obtaining characteristic information of an object to be identified;
judging whether the characteristic information of the object to be recognized is matched with the judgment reference, if so, determining the object to be recognized as a related object of the reference object, wherein the reference object is a determined member in a designated group, and the related object is other members in the designated group;
wherein determining a criterion for identifying an associated object of the reference object comprises:
determining each judgment standard according to at least two different types of feature information of a standard object and judgment standard setting rules respectively corresponding to the at least two different types of feature information;
judging whether the characteristic information of the object to be recognized is matched with the judgment reference, if so, determining the object to be recognized as the related object of the reference object, and the method comprises the following steps:
respectively judging whether each piece of feature information of an object to be identified accords with a corresponding judgment standard, wherein the fact that the feature information of the object to be identified accords with the corresponding judgment standard means that the feature information of the object to be identified is located within a preset deviation range of the feature information of the reference object;
and when the obtained judgment result meets the set condition, determining the object to be identified as the related object of the reference object.
2. The method of claim 1, wherein obtaining feature information of an object to be identified comprises:
determining the identification of an object to be identified;
and acquiring the characteristic information of the object to be recognized from the characteristic information of the object stored by the big data server according to the identifier of the object to be recognized and the type of the characteristic information corresponding to the judgment reference.
3. The method of claim 2, wherein determining an identity of an object to be recognized comprises:
obtaining an identification filtering condition;
and according to the identification filtering condition, determining the object identification meeting the identification filtering condition from the object identifications stored in the big data server.
4. The method according to claim 1, wherein determining the object to be recognized as the related object of the reference object when the obtained determination result satisfies a set condition includes:
judging whether the obtained judgment result meets the set condition or not according to the obtained judgment result and the judgment result weight set aiming at the different types of feature information;
and when the judgment result is yes, determining the object to be identified as the related object of the reference object.
5. The method of any one of claims 1 to 4, wherein:
the information is a check-in information characteristic item;
the at least two characteristic information items comprise at least two of the following check-in information characteristic items:
the time of check-in;
the time of returning to the room;
a name of the hotel checked in;
a geographic location of the check-in hotel;
star class for hospitalized hotels.
6. An apparatus for identifying an associated object, comprising:
a criterion specifying unit that specifies a criterion for identifying an object associated with the reference object; the judgment reference is determined according to at least two pieces of characteristic information of the reference object and a preset deviation range of the characteristic information;
the device comprises a to-be-identified object characteristic information obtaining unit, a recognition unit and a recognition unit, wherein the to-be-identified object characteristic information obtaining unit is used for obtaining characteristic information of an object to be identified;
the identification unit is used for judging whether the characteristic information of the object to be identified is matched with the judgment reference or not, and if the characteristic information of the object to be identified is matched with the judgment reference, the object to be identified is determined as a related object of the reference object, wherein the reference object is a determined member in a designated crowd, and the related object is other members in the designated crowd;
wherein the determination criterion determining unit is specifically configured to: determining each judgment standard according to at least two different types of feature information of a standard object and judgment standard setting rules respectively corresponding to the at least two different types of feature information;
the identification unit is specifically configured to: respectively judging whether each feature information of the object to be identified meets a corresponding judgment standard, and determining the object to be identified as a related object of the reference object when the obtained judgment result meets a set condition, wherein the condition that the feature information of the object to be identified meets the corresponding judgment standard means that the feature information of the object to be identified is located in a preset deviation range of the feature information of the reference object.
7. The apparatus of claim 6, wherein the object feature information to be recognized obtaining unit is configured to:
determining the identification of an object to be identified;
and acquiring the characteristic information of the object to be recognized from the characteristic information of the object stored by the big data server according to the identifier of the object to be recognized and the type of the characteristic information corresponding to the judgment reference.
8. The apparatus of claim 7, wherein the object feature information to be recognized obtaining unit is configured to:
obtaining an identification filtering condition;
and according to the identification filtering condition, determining the object identification meeting the identification filtering condition from the object identifications stored in the big data server.
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