CN111881169A - Model-based expired domain name judgment method and device - Google Patents
Model-based expired domain name judgment method and device Download PDFInfo
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Abstract
The application discloses a method and a device for judging an expired domain name based on a model. The method comprises the following steps: receiving a domain name to be processed; inputting the domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue; obtaining a classification result output by the domain name detection model; and judging whether the domain name to be processed is overdue or not according to the classification result output by the domain name detection model. By adopting the scheme disclosed by the application, as long as the domain name to be processed is input into the domain name detection model, whether the domain name is overdue or not can be judged through the domain name detection model, the application range of overdue domain name inquiry is improved, whether the domain name is overdue or not is automatically inquired through the model, and the domain name inquiry efficiency is also improved.
Description
Technical Field
The application relates to the technical field of internet, in particular to a method and a device for judging an expired domain name based on a model.
Background
Domain name registration is expirable, and when the owner of the domain name does not renew or forgets to renew the domain name after the domain name expires, the domain name is identified as the "expired domain name" in a short time.
In the prior art, the method for querying whether a domain name is expired includes: the manufacturer provides a domain name inquiry system under the flag of the manufacturer, and can inquire whether the domain name is overdue or not, or manually open the domain name and manually judge whether the domain name is overdue or not according to a prompt returned by a page.
The scheme for inquiring the expired domain name in the prior art has certain disadvantages, for example, the scheme for automatically judging the expired domain name can only inquire whether the own flag domain name is expired by each domain name provider, so the application range is small and the limitation is high. Although the manual method is not limited, the manual method for querying the outdated domain name has high labor cost, cannot automatically perform batch domain name judgment, and has low query efficiency, so how to provide the outdated domain name judgment method for improving the query efficiency of the outdated domain name under the condition of improving the application range.
Disclosure of Invention
The embodiment of the application aims to provide a method and a device for judging an expired domain name based on a model.
In order to solve the technical problem, the embodiment of the application adopts the following technical scheme: a method for judging an expired domain name based on a model comprises the following steps:
receiving a domain name to be processed;
inputting the domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue;
obtaining a classification result output by the domain name detection model;
and judging whether the domain name to be processed is overdue or not according to the classification result output by the domain name detection model.
The beneficial effect of this embodiment lies in: inputting the domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue; obtaining a classification result output by the domain name detection model; and judging whether the domain name to be processed is overdue or not according to the classification result output by the domain name detection model, so that the domain name to be processed can be judged to be overdue or not through the domain name detection model as long as the domain name to be processed is input into the domain name detection model, the application range of overdue domain name query is improved, the model is used for automatically querying whether the domain name is overdue or not, and the efficiency of domain name query is also improved.
In one embodiment, the method further comprises:
creating the domain name detection model;
collecting training samples related to the domain name detection model;
and pre-training the domain name detection model based on the training samples.
In one embodiment, creating the domain name detection model comprises:
creating the domain name detection model based on at least one of the following algorithms:
the Kmeans algorithm, the K-Medoids algorithm, the CLARANS algorithm, the Canopy algorithm, the BIRCH algorithm, and the DBSCAN algorithm.
In one embodiment, the collecting training samples related to the domain name detection model includes:
and selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
In one embodiment, the pre-training the domain name detection model based on the training samples includes:
preprocessing the training sample to obtain a feature vector corresponding to the training sample;
inputting the feature vector corresponding to the training sample into the domain name detection model;
obtaining a classification result output by the domain name detection model;
and when the classification result output by the domain name detection model meets a preset condition, determining that the domain name detection model is trained.
In one embodiment, the classification result output by the domain name detection model satisfies a preset condition, and includes:
comparing the classification result output by the domain name detection model with a preset result to judge whether the domain name detection model gathers the outdated domain name into a classification identifier representing the outdated domain name;
and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
The present application further provides a device for determining an expired domain name based on a model, comprising:
the receiving module is used for receiving the domain name to be processed;
the input module is used for inputting the domain name to be processed into a domain name detection model, and the domain name detection model is used for judging whether the domain name is overdue or not;
the acquisition module is used for acquiring the classification result output by the domain name detection model;
and the judging module is used for judging whether the domain name to be processed is overdue according to the classification result output by the domain name detection model.
In one embodiment, the apparatus further comprises:
the creating module is used for creating the domain name detection model;
the collection module is used for collecting training samples related to the domain name detection model;
and the pre-training module is used for pre-training the domain name detection model based on the training sample.
In one embodiment, the creating module includes:
a creating sub-module for creating the domain name detection model based on at least one of the following algorithms:
the Kmeans algorithm, the K-Medoids algorithm, the CLARANS algorithm, the Canopy algorithm, the BIRCH algorithm, and the DBSCAN algorithm.
In one embodiment, the collection module includes:
and the selection submodule is used for selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
In one embodiment, the pre-training module comprises:
the preprocessing submodule is used for preprocessing the training sample to obtain a feature vector corresponding to the training sample;
the input sub-module is used for inputting the feature vectors corresponding to the training samples into the domain name detection model;
the obtaining sub-module is used for obtaining the classification result output by the domain name detection model;
and the determining submodule is used for determining that the training of the domain name detection model is finished when the classification result output by the domain name detection model meets the preset condition.
In one embodiment, the classification result output by the domain name detection model satisfies a preset condition, and includes:
comparing the classification result output by the domain name detection model with a preset result to judge whether the domain name detection model gathers the outdated domain name into a classification identifier representing the outdated domain name;
and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
Drawings
Fig. 1 is a flowchart of a method for determining an expired domain name based on a model according to an embodiment of the present application;
fig. 2 is a flowchart of a method for determining an expired domain name based on a model according to another embodiment of the present application;
FIG. 3 is a flowchart of a method for determining an expired domain name based on a model according to another embodiment of the present application;
FIG. 4 is a schematic diagram illustrating a process of pre-training a domain name detection model according to an embodiment of the present application;
fig. 5 is a block diagram of a model-based domain name expiration determination apparatus according to an embodiment of the present application;
fig. 6 is a block diagram of a model-based domain name expiration determination apparatus according to an embodiment of the present application.
Detailed Description
Various aspects and features of the present application are described herein with reference to the drawings.
It will be understood that various modifications may be made to the embodiments of the present application. Accordingly, the foregoing description should not be construed as limiting, but merely as exemplifications of embodiments. Those skilled in the art will envision other modifications within the scope and spirit of the application.
The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the application and, together with a general description of the application given above and the detailed description of the embodiments given below, serve to explain the principles of the application.
These and other characteristics of the present application will become apparent from the following description of preferred forms of embodiment, given as non-limiting examples, with reference to the attached drawings.
It should also be understood that, although the present application has been described with reference to some specific examples, a person of skill in the art shall certainly be able to achieve many other equivalent forms of application, having the characteristics as set forth in the claims and hence all coming within the field of protection defined thereby.
The above and other aspects, features and advantages of the present application will become more apparent in view of the following detailed description when taken in conjunction with the accompanying drawings.
Specific embodiments of the present application are described hereinafter with reference to the accompanying drawings; however, it is to be understood that the disclosed embodiments are merely exemplary of the application, which can be embodied in various forms. Well-known and/or repeated functions and constructions are not described in detail to avoid obscuring the application of unnecessary or unnecessary detail. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a basis for the claims and as a representative basis for teaching one skilled in the art to variously employ the present application in virtually any appropriately detailed structure.
The specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may each refer to one or more of the same or different embodiments in accordance with the application.
Fig. 1 is a flowchart of a method for determining an expired domain name based on a model according to an embodiment of the present application, where the method includes the following steps S11-S14:
in step S11, receiving a domain name to be processed;
in step S12, inputting the domain name to be processed into a domain name detection model, where the domain name detection model is used to determine whether the domain name is expired;
in step S13, a classification result output by the domain name detection model is obtained;
in step S14, it is determined whether the domain name to be processed is expired according to the classification result output by the domain name detection model.
The domain name is the name of a certain computer or group of computers on the internet, which is composed of a string of characters separated by dots, and is used for identifying the electronic orientation of the computer during data transmission. A domain name is a name for an IP address, so to speak, in order to facilitate remembering the latter. Cn is a domain name, for example, and corresponds to an IP 123.59.85.88 address. Cn can be directly accessed by a person instead of an IP address, which the Domain Name System (DNS) then translates into an IP address that is easy for machine recognition. Com, one need only memorize a string of characters with a special meaning, and not a number without meaning. Domain name registration is expirable, and when the owner of the domain name does not or forgets to renew the domain name after the domain name expires, the domain name is identified as the 'expired domain name' in a short time "
The application aims to provide a model-based overdue domain name judging method, and particularly receives a domain name to be processed; for example, the application may provide an input box of the to-be-processed domain name, and receive the to-be-processed domain name input by the user when the user inputs the to-be-processed domain name. In addition, the method and the device can also provide a task interface for receiving the batch detection domain names, so that the batch to-be-processed domain names sent by other equipment are received through the task interface.
Inputting a domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue; for example, in the present application, only two classification results exist, namely "unexpired" and "expired", respectively, where the classification result of the unexpired domain name identified by the domain name detection model is identified as 1, and the classification result of the identified expired domain name is identified as 2, when classifying the domain names, the classification result columns of all unexpired domain names output 1, and the classification result columns of the expired domain names output 2, it can also be understood that the domain name detection model classifies the unexpired domain name into [1] class, and classifies the expired domain name into [2] class. Com ", for example, for a domain name" crystalluononfshop ", the results of prediction using the model are shown in fig. 2; wherein [ 173530100502 ] in the output result represents the number of labels such as div, a, script, etc., and the model classifies the domain name into [2] classes according to the data of the labels, that is, the domain name is an expired domain name.
The beneficial effect of this embodiment lies in: inputting a domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue; obtaining a classification result output by a domain name detection model; whether the domain name to be processed is overdue or not is judged according to the classification result output by the domain name detection model, so that whether the domain name is overdue or not can be judged through the domain name detection model as long as the domain name to be processed is input into the domain name detection model, the application range of overdue domain name inquiry is improved, whether the domain name is overdue or not is automatically inquired through the model, and the domain name inquiry efficiency is improved.
In one embodiment, as shown in FIG. 2, the method may also be implemented as steps S21-S23 as follows:
in step S21, a domain name detection model is created;
in step S22, collecting training samples related to the domain name detection model;
in step S23, the domain name detection model is pre-trained based on the training samples.
In the present application, a domain name detection model is created, and the domain name detection model is classified according to whether a domain name is expired, and only two categories of "unexpired" and "expired" exist in the category, so the domain name detection model can be created based on various clustering algorithms, for example, a domain name detection model is created by using kmans (K-means clustering algorithm), which is an iterative clustering analysis algorithm, and the method includes the steps of dividing data into K groups in advance, randomly selecting K objects as initial clustering centers, then calculating the distance between each object and each seed clustering center, and assigning each object to the nearest clustering center. The cluster centers and the objects assigned to them represent a cluster. The cluster center of a cluster is recalculated for each sample assigned based on the objects existing in the cluster. This process will be repeated until some termination condition is met. The termination condition may be that no (or minimum number) objects are reassigned to different clusters, no (or minimum number) cluster centers are changed again, and the sum of squared errors is locally minimal.
For another example, the domain name detection model may be created based on an algorithm such as a K-Medoids algorithm, a CLARANS algorithm, a Canopy algorithm, a BIRCH algorithm, or a DBSCAN algorithm. After the domain name detection model is created, the domain name detection model needs to be pre-trained so that the domain name detection model has better classification capability, and specifically, training samples related to the domain name detection model are collected; and pre-training the domain name detection model based on the training samples.
In one embodiment, the step S21 can be implemented as:
creating a domain name detection model based on at least one of the following algorithms:
the Kmeans algorithm, the K-Medoids algorithm, the CLARANS algorithm, the Canopy algorithm, the BIRCH algorithm, and the DBSCAN algorithm.
In one embodiment, the step S22 can be implemented as the following steps:
and selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
In one embodiment, the above step S23 can be implemented as the following steps S31-S34:
in step S31, preprocessing the training samples to obtain feature vectors corresponding to the training samples;
in step S32, inputting the feature vector corresponding to the training sample into the domain name detection model;
in step S33, a classification result output by the domain name detection model is obtained;
in step S34, when the classification result output by the domain name detection model satisfies a preset condition, it is determined that the domain name detection model training is completed.
The embodiment is used for pre-training a domain name detection model, fig. 4 is a schematic diagram of a process of pre-training a domain name detection model, a large number of normal domain names (namely unexpired domain names) and outdated domain names of a specific mobile phone are used as training samples, and then the training samples are preprocessed to obtain feature vectors corresponding to the training samples; specifically, since the training samples are domain names, preprocessing the training samples includes: and programming and downloading source codes of all domain names, and counting the number of HTML labels in a domain name page, such as div labels, p labels, img labels and the like. The HTML tag consists of a start tag and an end tag, the start tag being the element name enclosed by brackets, the end tag being the slash and the element name enclosed by brackets, e.g. < h1 > Thisis a heading "h 1 > is a web page tag.
And selecting a plurality of typical labels as the corresponding characteristic vectors of the training samples, removing the labels with lower weights to prevent interference, and supplementing the number of the absent labels to 0. Inputting the feature vector corresponding to the training sample into a domain name detection model; the domain name detection model clusters the domain names according to the feature vectors corresponding to the training samples (namely, the domain names), and then outputs the classification results of the domain names from the output end.
And when the classification result output by the domain name detection model meets the preset condition, determining that the training of the domain name detection model is finished. Specifically, whether the classification result meets the preset condition may be determined in the following two ways.
The method is characterized in that the number of clustering centers of the domain name detection model can be changed continuously, the classification effect of the domain name detection model can be evaluated by looking up WSS (Wireless sensor System) and when the domain name detection model can achieve the purpose of accurately clustering expired domain names into one class, the domain name detection model is determined to be trained.
Mode two
In this embodiment, assuming that it is known in advance which of the training samples are outdated domain names and which are non-outdated domain names, after the domain name detection model outputs the classification result, the classification result output by the domain name detection model may be compared with a preset result to determine whether the domain name detection model aggregates the outdated domain names into the classification identifiers representing the outdated domain names; and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
In one embodiment, the classification result output by the domain name detection model in the step S34 meets the preset condition, which includes the following steps a1-a 2:
in step a1, comparing the classification result output by the domain name detection model with a preset result to determine whether the domain name detection model gathers the outdated domain name into a classification identifier representing the outdated domain name;
in step a2, when the domain name detection model aggregates the outdated domain names into the classification identifiers representing the outdated domain names, it is determined that the determination result output by the domain name detection model satisfies the preset condition.
In this embodiment, assuming that it is known in advance which of the training samples are outdated domain names and which are non-outdated domain names, after the domain name detection model outputs the classification result, the classification result output by the domain name detection model may be compared with a preset result to determine whether the domain name detection model aggregates the outdated domain names into the classification identifiers representing the outdated domain names; and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
Fig. 5 is a block diagram of a model-based domain name expiration determination apparatus according to an embodiment of the present application, where the apparatus includes the following modules:
a receiving module 51, configured to receive a domain name to be processed;
an input module 52, configured to input the domain name to be processed into a domain name detection model, where the domain name detection model is used to determine whether the domain name is expired;
an obtaining module 53, configured to obtain a classification result output by the domain name detection model;
and the judging module 54 is configured to judge whether the domain name to be processed is out of date according to the classification result output by the domain name detection model.
In one embodiment, as shown in fig. 6, the apparatus further comprises:
a creating module 61, configured to create a domain name detection model;
a collection module 62 for collecting training samples related to the domain name detection model;
and the pre-training module 63 is configured to pre-train the domain name detection model based on the training samples.
In one embodiment, a creation module includes:
a creating sub-module for creating a domain name detection model based on at least one of the following algorithms:
the Kmeans algorithm, the K-Medoids algorithm, the CLARANS algorithm, the Canopy algorithm, the BIRCH algorithm, and the DBSCAN algorithm.
In one embodiment, a collection module, comprising:
and the selection submodule is used for selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
In one embodiment, a pre-training module, comprising:
the preprocessing submodule is used for preprocessing the training sample to obtain a feature vector corresponding to the training sample;
the input sub-module is used for inputting the feature vectors corresponding to the training samples into the domain name detection model;
the obtaining sub-module is used for obtaining a classification result output by the domain name detection model;
and the determining submodule is used for determining that the training of the domain name detection model is finished when the classification result output by the domain name detection model meets the preset condition.
In one embodiment, the classification result output by the domain name detection model satisfies a preset condition, including:
comparing the classification result output by the domain name detection model with a preset result to judge whether the domain name detection model gathers the outdated domain name into a classification identifier representing the outdated domain name;
and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
The above embodiments are only exemplary embodiments of the present application, and are not intended to limit the present application, and the protection scope of the present application is defined by the claims. Various modifications and equivalents may be made by those skilled in the art within the spirit and scope of the present application and such modifications and equivalents should also be considered to be within the scope of the present application.
Claims (10)
1. A method for judging an expired domain name based on a model is characterized by comprising the following steps:
receiving a domain name to be processed;
inputting the domain name to be processed into a domain name detection model, wherein the domain name detection model is used for judging whether the domain name is overdue;
obtaining a classification result output by the domain name detection model;
and judging whether the domain name to be processed is overdue or not according to the classification result output by the domain name detection model.
2. The method of claim 1, wherein the method further comprises:
creating the domain name detection model;
collecting training samples related to the domain name detection model;
and pre-training the domain name detection model based on the training samples.
3. The method of claim 2, wherein creating the domain name detection model comprises:
creating the domain name detection model based on at least one of the following algorithms:
the Kmeans algorithm, the K-Medoids algorithm, the CLARANS algorithm, the Canopy algorithm, the BIRCH algorithm, and the DBSCAN algorithm.
4. The method of claim 2, wherein the collecting training samples related to the domain name detection model comprises:
and selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
5. The method of claim 2, wherein the pre-training the domain name detection model based on the training samples comprises:
preprocessing the training sample to obtain a feature vector corresponding to the training sample;
inputting the feature vector corresponding to the training sample into the domain name detection model;
obtaining a classification result output by the domain name detection model;
and when the classification result output by the domain name detection model meets a preset condition, determining that the domain name detection model is trained.
6. The method according to claim 5, wherein the classification result output by the domain name detection model satisfies a preset condition, and comprises:
comparing the classification result output by the domain name detection model with a preset result to judge whether the domain name detection model gathers the outdated domain name into a classification identifier representing the outdated domain name;
and when the domain name detection model gathers the outdated domain name into the classification identification representing the outdated domain name, determining that a judgment result output by the domain name detection model meets a preset condition.
7. A model-based domain name expiration determination apparatus, comprising:
the receiving module is used for receiving the domain name to be processed;
the input module is used for inputting the domain name to be processed into a domain name detection model, and the domain name detection model is used for judging whether the domain name is overdue or not;
the acquisition module is used for acquiring the classification result output by the domain name detection model;
and the judging module is used for judging whether the domain name to be processed is overdue according to the classification result output by the domain name detection model.
8. The apparatus of claim 7, wherein the apparatus further comprises:
the creating module is used for creating the domain name detection model;
the collection module is used for collecting training samples related to the domain name detection model;
and the pre-training module is used for pre-training the domain name detection model based on the training sample.
9. The apparatus of claim 8, wherein the collection module comprises:
and the selection submodule is used for selecting a first preset number of unexpired domain names and a second preset number of expired domain names as training samples related to the domain name detection model.
10. The apparatus of claim 8, wherein the pre-training module comprises:
the preprocessing submodule is used for preprocessing the training sample to obtain a feature vector corresponding to the training sample;
the input sub-module is used for inputting the feature vectors corresponding to the training samples into the domain name detection model;
the obtaining sub-module is used for obtaining the classification result output by the domain name detection model;
and the determining submodule is used for determining that the training of the domain name detection model is finished when the classification result output by the domain name detection model meets the preset condition.
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