Internet access method and Internet access system

Abstract

The invention is applicable to the technical field of Internet, and provides an Internet access method and an Internet access system, comprising the following steps: receiving an information access instruction, the information access instruction comprising access time, an access account and an access address; calling user historical data according to the access account and the access address, and determining a plurality of recommended access addresses according to the user historical data and the access big data; obtaining a predicted access track according to the access time, the access account and the access address, and caching data to be accessed in advance according to the predicted access track; determining a real access track of the user, and updating the predicted access track based on the real access track; and based on the real access condition of the pre-cached data, the pre-cached data is cleared in a differentiated manner. According to the method, the data to be accessed are cached in advance according to the predicted access trajectory, and the predictive caching strategy based on the user access behavior can significantly improve the cache hit rate and reduce the access delay.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet, and in particular to an Internet access method and an Internet access system. Background Art

[0002] With the rapid development of Internet technology, users' access needs for network information are becoming increasingly diversified and personalized. Traditional Internet access methods usually rely on users to directly enter the access address or search for the required information through search engines. This method has certain limitations in user experience and access efficiency. Especially in scenarios with high concurrent access or high network latency, users may need to wait for a long time to obtain the required information, which not only reduces the user experience, but may also lead to user loss. Therefore, it is necessary to provide an Internet access method and an Internet access system to solve the above problems. Summary of the invention

[0003] In view of the deficiencies in the prior art, the object of the present invention is to provide an Internet access method and an Internet access system to solve the problems existing in the above-mentioned background technology.

[0004] The present invention is implemented in a method for accessing the Internet, the method comprising the following steps:

[0005] receiving an information access instruction, wherein the information access instruction includes an access time, an access account number, and an access address;

[0006] Retrieve user history data based on the access account and access address, and determine several recommended access addresses based on the user history data and access big data;

[0007] Obtain a predicted access trajectory according to the access time, access account and access address, and cache the data to be accessed in advance according to the predicted access trajectory;

[0008] Determine the user's actual access trajectory and update the predicted access trajectory based on the actual access trajectory;

[0009] Based on the actual access situation of the pre-cached data, the pre-cached data is cleared in a differentiated manner.

[0010] As a further solution of the present invention: the step of retrieving user history data according to the access account and access address, and determining a plurality of recommended access addresses according to the user history data and the access big data, specifically includes:

[0011] Query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data;

[0012] Calculate the similarity between the current user and other users in access behavior based on the access big data, and determine the similar user set based on the similarity calculation results;

[0013] Addresses in a similar user set whose access frequencies are higher than a preset frequency value are counted to generate a recommended access address list, where the recommended access address list includes a number of recommended access addresses.

[0014] As a further solution of the present invention: the step of obtaining a predicted access trajectory according to the access time, access account and access address specifically includes:

[0015] Retrieving the historical access records of the access account, and extracting the time features, user features, and address features in the historical access records;

[0016] Use time series analysis as a prediction algorithm and use historical access records and features as training sets to train the prediction model;

[0017] The current access time and access address are input into the prediction model as prediction parameters to generate a predicted access trajectory.

[0018] As a further solution of the present invention: the step of determining the user's real access trajectory and updating the predicted access trajectory based on the real access trajectory specifically includes:

[0019] Get the user's real access track based on several access times and corresponding access addresses;

[0020] Input the latest N access times and access addresses in the actual access trajectory into the prediction model to generate the latest predicted access trajectory;

[0021] The actual access trajectory is set as the historical access record to verify and optimize the prediction model.

[0022] As a further solution of the present invention: the step of performing differentiated clearing of the pre-cached data based on the actual access situation of the pre-cached data specifically includes:

[0023] Determine the actual access situation of the pre-cached data, where the actual access situation is accessed within a time threshold or not accessed within a time threshold;

[0024] When the data is not accessed within the time threshold and the cache time of the pre-cached data is greater than the first set time, the pre-cached data is cleared;

[0025] When accessed within the time threshold, and the access end time of the advance cached data is greater than the second set time, the advance cached data is cleared.

[0026] Another object of the present invention is to provide an Internet access system, the system comprising:

[0027] An information access instruction module, used to receive an information access instruction, wherein the information access instruction includes an access time, an access account number and an access address;

[0028] The recommended access address module is used to retrieve user history data based on the access account and access address, and determine several recommended access addresses based on the user history data and access big data;

[0029] A data pre-caching module is used to obtain a predicted access trajectory according to the access time, access account and access address, and to pre-cache the data to be accessed according to the predicted access trajectory;

[0030] A predicted track update module is used to determine the user's real access track and update the predicted access track based on the real access track;

[0031] The cache data clearing module is used to perform differentiated clearing of pre-cached data based on actual access conditions of the pre-cached data.

[0032] As a further solution of the present invention: the recommended access address module includes:

[0033] The user history data unit is used to query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data;

[0034] A similar user set unit is used to calculate the similarity between the current user and other users in access behavior based on the access big data, and determine the similar user set according to the similarity calculation result;

[0035] The recommended access address unit is used to count addresses in a similar user set whose access frequency is higher than a preset frequency value, and generate a recommended access address list, which includes several recommended access addresses.

[0036] As a further solution of the present invention: the data advance cache module includes:

[0037] A historical feature extraction unit, used to retrieve the historical access records of the access account, and extract time features, user features and address features in the historical access records;

[0038] A prediction model training unit is used to train the prediction model by using time series analysis as a prediction algorithm and using historical access records and features as a training set;

[0039] The access trajectory prediction unit is used to input the current access time and access address as prediction parameters into the prediction model to generate a predicted access trajectory.

[0040] As a further solution of the present invention: the predicted trajectory updating module includes:

[0041] A real access track unit, used to obtain the user's real access track based on a number of access times and corresponding access addresses;

[0042] An access trajectory updating unit, used for inputting the latest N access times and access addresses in the real access trajectory into the prediction model to generate the latest predicted access trajectory;

[0043] The prediction model optimization unit is used to set the real access trajectory as the historical access record to verify and optimize the prediction model.

[0044] As a further solution of the present invention: the cache data clearing module includes:

[0045] An access situation determination unit, used to determine the actual access situation of the pre-cached data, where the actual access situation is accessed within a time threshold or not accessed within the time threshold;

[0046] A first cache clearing unit, configured to clear the pre-cached data when it has not been accessed within a time threshold and the cache time of the pre-cached data is greater than a first set time;

[0047] The second cache clearing unit is used to clear the pre-cached data when it is accessed within a time threshold and the access end time of the pre-cached data is greater than a second set time.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] The present invention determines the recommended access address based on the user's historical data and access big data, thereby helping users quickly locate the required information and reducing search time. In addition, the present invention also obtains a predicted access trajectory based on the access time, access account and access address, and caches the data to be accessed in advance based on the predicted access trajectory. This predictive caching strategy based on user access behavior can significantly improve the cache hit rate, reduce access delays, and greatly improve the user's Internet experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 A flowchart of a method for accessing the Internet is shown.

[0051] Figure 2 The present invention is a flow chart for determining a recommended access address in a method for accessing the Internet.

[0052] Figure 3 A flowchart of obtaining a predicted access trajectory in an Internet access method.

[0053] Figure 4 The present invention is a flowchart of updating a predicted access trajectory in an Internet access method.

[0054] Figure 5 The present invention is a flow chart for performing differentiated clearing of pre-cached data in an Internet access method.

[0055] Figure 6 A schematic diagram of the structure of an Internet access system. DETAILED DESCRIPTION

[0056] In order to make the purpose, technical solution and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0057] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0058] like Figure 1 As shown, an embodiment of the present invention provides an Internet access method, the method comprising the following steps:

[0059] S100, receiving an information access instruction, wherein the information access instruction includes an access time, an access account number and an access address;

[0060] S200, retrieving user history data according to the access account and the access address, and determining a number of recommended access addresses according to the user history data and the access big data;

[0061] S300, obtaining a predicted access trajectory according to the access time, the access account and the access address, and caching the data to be accessed in advance according to the predicted access trajectory;

[0062] S400, determining the user's real access trajectory, and updating the predicted access trajectory based on the real access trajectory;

[0063] S500: based on the actual access situation of the pre-cached data, clear the pre-cached data in a differentiated manner.

[0064] It should be noted that existing Internet access systems often lack in-depth analysis and prediction of user access behavior. Although the user's historical access data can reflect their interests and preferences to a certain extent, how to effectively use this data to optimize the access process and improve access efficiency is still a problem that needs to be solved in the current Internet technology field. At the same time, with the widespread application of big data technology, the amount of data on the Internet has shown explosive growth. How to quickly locate and cache the data that the user is about to access in massive data to reduce access delays and increase access speeds has become an important technical challenge. However, existing caching strategies are often based on simple rules or fixed algorithms, lacking dynamic adaptability and flexibility to user access behaviors. The embodiments of the present invention are intended to solve the above problems.

[0065] In the embodiment of the present invention, when a user accesses the Internet, he will enter an information access instruction, which includes the access time, access account and access address, and then automatically retrieve the user's historical data according to the access account and access address, and determine several recommended access addresses according to the user's historical data and access big data, and the access big data refers to the access data of other users, so as to help users quickly locate the required information and reduce the search time. In addition, the embodiment of the present invention will also obtain a predicted access trajectory according to the access time, access account and access address, and cache the data to be accessed in advance according to the predicted access trajectory. This predictive caching strategy based on user access behavior can significantly improve the cache hit rate, reduce access delay, and greatly improve the user's Internet experience; and the real access trajectory will be determined according to the user's access facts, and the predicted access trajectory will be updated based on the real access trajectory. This dynamic update mechanism can ensure the accuracy and timeliness of the prediction model, so that it can better adapt to changes in user access behavior. In addition, the embodiment of the present invention will also differentiate and clear the pre-cached data based on the real access situation of the pre-cached data. This strategy can avoid the long-term occupation of storage space by invalid data and improve the utilization of cache resources.

[0066] like Figure 2 As shown, as a preferred embodiment of the present invention, the step of retrieving user history data according to the access account and the access address, and determining a plurality of recommended access addresses according to the user history data and the access big data, specifically includes:

[0067] S201, query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data;

[0068] S202, calculating the similarity between the current user and other users in access behavior based on the access big data, and determining a similar user set according to the similarity calculation result;

[0069] S203, counting addresses in the similar user set whose access frequencies are higher than a preset frequency value, and generating a recommended access address list, wherein the recommended access address list includes a plurality of recommended access addresses.

[0070] In the embodiment of the present invention, in order to determine the recommended access address, the database is queried according to the access account and the access address to retrieve the user's historical access record and obtain the user's historical data, which includes the addresses, access time, access frequency and other information that the user has visited in the past. Based on the access big data, the similarity between the current user and other users in access behavior is calculated, and a similar user set is determined according to the similarity calculation result. The similarity calculation algorithm used is cosine similarity or Pearson correlation coefficient. Then, addresses in the similar user set with access frequencies higher than a preset frequency value are counted to generate a recommended access address list. The recommended access address list contains several recommended access addresses, and the several recommended access addresses are also sorted according to the similarity calculation result.

[0071] like Figure 3 As shown, as a preferred embodiment of the present invention, the step of obtaining a predicted access trajectory according to the access time, access account and access address specifically includes:

[0072] S301, retrieve the historical access records of the access account, and extract the time features, user features, and address features in the historical access records;

[0073] S302, using time series analysis as a prediction algorithm, using historical access records and features as a training set, and training a prediction model;

[0074] S303: Input the current access time and access address as prediction parameters into the prediction model to generate a predicted access trajectory.

[0075] In the embodiment of the present invention, in order to predict the access trajectory, the historical access records of the access account need to be retrieved first, and the historical access records are cleaned to remove duplicate, invalid or erroneous data; then the time features, user features and address features in the historical access records are extracted, specifically, the time features such as hour, date, week, month, etc. are extracted from the access time, and the user's access preferences in different time periods are considered, such as the difference in access modes between weekdays and weekends, daytime and night; the basic information of the user is extracted according to the access account, such as user type, registration time, activity level, etc., and the user's access habits are analyzed, such as access frequency, access duration, access path, etc.; cluster analysis is performed on the access address to identify popular access areas, user-frequented places, etc., and the correlation between addresses is considered, such as geographical proximity, functional similarity, etc. Then, time series analysis is used as a prediction algorithm, and the historical access records and features are used as training sets to train the prediction model. Finally, the current access time and access address are input into the prediction model as prediction parameters, and a predicted access trajectory is generated.

[0076] like Figure 4 As shown, as a preferred embodiment of the present invention, the step of determining the user's real access trajectory and updating the predicted access trajectory based on the real access trajectory specifically includes:

[0077] S401, obtaining the user's real access track based on a number of access times and corresponding access addresses;

[0078] S402, inputting the latest N access times and access addresses in the real access trajectory into the prediction model to generate the latest predicted access trajectory;

[0079] S403: Set the real access trajectory as the historical access record to verify and optimize the prediction model.

[0080] In the embodiment of the present invention, it is necessary to obtain the user's real access trajectory based on several access times and corresponding access addresses of the user during this Internet access, and then input the latest N access times and access addresses in the real access trajectory into the prediction model to generate the latest predicted access trajectory, where N is a constant, for example, N=5; in addition, the embodiment of the present invention also sets the real access trajectory as the historical access record, verifies and optimizes the prediction model, and makes the prediction model more reliable.

[0081] like Figure 5 As shown, as a preferred embodiment of the present invention, the step of performing differentiated clearing of pre-cached data based on the actual access situation of the pre-cached data specifically includes:

[0082] S501, determining the actual access status of the pre-cached data, where the actual access status is accessed within a time threshold or not accessed within the time threshold;

[0083] S502, when the data cached in advance is not accessed within the time threshold, and the cache time of the data cached in advance is greater than the first set time, clearing the data cached in advance;

[0084] S503: When the data is accessed within the time threshold and the access end time of the pre-cached data is greater than the second set time, the pre-cached data is cleared.

[0085] In an embodiment of the present invention, in order to perform differentiated clearing of pre-cached data, it is necessary to determine the actual access situation of the pre-cached data. When the pre-cached data is not accessed within a time threshold and the cache time of the pre-cached data is greater than a first set time, it means that the pre-cached data will basically not be accessed, and the pre-cached data will be cleared; when the pre-cached data is accessed within a time threshold and the access end time of the pre-cached data is greater than a second set time, it means that the pre-cached data will basically not be accessed again, and the pre-cached data will be cleared. The first set time and the second set time are both constants.

[0086] like Figure 6 As shown, an embodiment of the present invention further provides an Internet access system, the system comprising:

[0087] The information access instruction module 100 is used to receive an information access instruction, wherein the information access instruction includes an access time, an access account number and an access address;

[0088] The recommended access address module 200 is used to retrieve the user history data according to the access account and the access address, and determine a number of recommended access addresses according to the user history data and the access big data;

[0089] The data pre-caching module 300 is used to obtain a predicted access trajectory according to the access time, access account and access address, and pre-cache the data to be accessed according to the predicted access trajectory;

[0090] The predicted track update module 400 is used to determine the real access track of the user and update the predicted access track based on the real access track;

[0091] The cache data clearing module 500 is used to perform differentiated clearing of the pre-cached data based on the actual access situation of the pre-cached data.

[0092] As a preferred embodiment of the present invention, the recommended access address module 200 includes:

[0093] The user history data unit is used to query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data;

[0094] A similar user set unit is used to calculate the similarity between the current user and other users in access behavior based on the access big data, and determine the similar user set according to the similarity calculation result;

[0095] The recommended access address unit is used to count addresses in a similar user set whose access frequency is higher than a preset frequency value, and generate a recommended access address list, which includes several recommended access addresses.

[0096] As a preferred embodiment of the present invention, the data advance cache module 300 includes:

[0097] A historical feature extraction unit, used to retrieve the historical access records of the access account, and extract time features, user features and address features in the historical access records;

[0098] A prediction model training unit is used to train the prediction model by using time series analysis as a prediction algorithm and using historical access records and features as a training set;

[0099] The access trajectory prediction unit is used to input the current access time and access address as prediction parameters into the prediction model to generate a predicted access trajectory.

[0100] As a preferred embodiment of the present invention, the predicted trajectory updating module 400 includes:

[0101] A real access track unit, used to obtain the user's real access track based on a number of access times and corresponding access addresses;

[0102] An access trajectory updating unit, used for inputting the latest N access times and access addresses in the real access trajectory into the prediction model to generate the latest predicted access trajectory;

[0103] The prediction model optimization unit is used to set the real access trajectory as the historical access record to verify and optimize the prediction model.

[0104] As a preferred embodiment of the present invention, the cache data clearing module 500 includes:

[0105] An access situation determination unit, used to determine the actual access situation of the pre-cached data, where the actual access situation is accessed within a time threshold or not accessed within the time threshold;

[0106] A first cache clearing unit, configured to clear the pre-cached data when it has not been accessed within a time threshold and the cache time of the pre-cached data is greater than a first set time;

[0107] The second cache clearing unit is used to clear the pre-cached data when it is accessed within a time threshold and the access end time of the pre-cached data is greater than a second set time.

[0108] The above only describes in detail the preferred embodiments of the present invention, which is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0109] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0110] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0111] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

Claims

1. A method for accessing the Internet, characterized in that: The method comprises the following steps: receiving an information access instruction, wherein the information access instruction includes an access time, an access account number, and an access address; Retrieve user history data based on the access account and access address, and determine several recommended access addresses based on the user history data and access big data; Obtain a predicted access trajectory according to the access time, access account and access address, and cache the data to be accessed in advance according to the predicted access trajectory; Determine the user's actual access trajectory and update the predicted access trajectory based on the actual access trajectory; Based on the actual access situation of the pre-cached data, the pre-cached data is cleared in a differentiated manner.

2. The Internet access method according to claim 1, characterized in that: The step of retrieving user history data according to the access account and the access address, and determining a plurality of recommended access addresses according to the user history data and the access big data specifically includes: Query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data; Calculate the similarity between the current user and other users in access behavior based on the access big data, and determine the similar user set based on the similarity calculation results; Addresses in a similar user set whose access frequencies are higher than a preset frequency value are counted to generate a recommended access address list, where the recommended access address list includes a number of recommended access addresses.

3. The Internet access method according to claim 1, characterized in that: The step of obtaining a predicted access trajectory according to the access time, access account and access address specifically includes: Retrieving the historical access records of the access account, and extracting the time features, user features, and address features in the historical access records; Use time series analysis as a prediction algorithm and use historical access records and features as training sets to train the prediction model; The current access time and access address are input into the prediction model as prediction parameters to generate a predicted access trajectory.

4. The Internet access method according to claim 3, characterized in that: The step of determining the user's real access trajectory and updating the predicted access trajectory based on the real access trajectory specifically includes: Get the user's real access track based on several access times and corresponding access addresses; Input the latest N access times and access addresses in the actual access trajectory into the prediction model to generate the latest predicted access trajectory; The actual access trajectory is set as the historical access record to verify and optimize the prediction model.

5. The Internet access method according to claim 1, characterized in that: The step of performing differentiated clearing of the pre-cached data based on the actual access situation of the pre-cached data specifically includes: Determine the actual access situation of the pre-cached data, where the actual access situation is accessed within a time threshold or not accessed within a time threshold; When the data is not accessed within the time threshold and the cache time of the pre-cached data is greater than the first set time, the pre-cached data is cleared; When accessed within the time threshold, and the access end time of the advance cached data is greater than the second set time, the advance cached data is cleared.

6. An Internet access system, characterized in that: The system comprises: An information access instruction module, used to receive an information access instruction, wherein the information access instruction includes an access time, an access account number and an access address; The recommended access address module is used to retrieve user history data based on the access account and access address, and determine several recommended access addresses based on the user history data and access big data; A data pre-caching module is used to obtain a predicted access trajectory according to the access time, access account and access address, and to pre-cache the data to be accessed according to the predicted access trajectory; A predicted track update module is used to determine the user's real access track and update the predicted access track based on the real access track; The cache data clearing module is used to perform differentiated clearing of pre-cached data based on actual access conditions of the pre-cached data.

7. The Internet access system according to claim 6, characterized in that: The recommended access address module includes: The user history data unit is used to query the database, retrieve the user's historical access records according to the access account and access address, and obtain the user's historical data; A similar user set unit is used to calculate the similarity between the current user and other users in access behavior based on the access big data, and determine the similar user set according to the similarity calculation result; The recommended access address unit is used to count addresses in a similar user set whose access frequency is higher than a preset frequency value, and generate a recommended access address list, which includes several recommended access addresses.

8. The Internet access system according to claim 6, characterized in that: The data advance cache module includes: A historical feature extraction unit, used to retrieve the historical access records of the access account, and extract time features, user features and address features in the historical access records; A prediction model training unit is used to train the prediction model by using time series analysis as a prediction algorithm and using historical access records and features as a training set; The access trajectory prediction unit is used to input the current access time and access address as prediction parameters into the prediction model to generate a predicted access trajectory.

9. The Internet access system according to claim 8, characterized in that: The predicted trajectory updating module comprises: A real access track unit, used to obtain the user's real access track based on a number of access times and corresponding access addresses; An access trajectory updating unit, used for inputting the latest N access times and access addresses in the real access trajectory into the prediction model to generate the latest predicted access trajectory; The prediction model optimization unit is used to set the real access trajectory as the historical access record to verify and optimize the prediction model.

10. The Internet access system according to claim 6, characterized in that: The cache data clearing module comprises: An access situation determination unit, used to determine the actual access situation of the pre-cached data, where the actual access situation is accessed within a time threshold or not accessed within the time threshold; A first cache clearing unit, configured to clear the pre-cached data when it has not been accessed within a time threshold and the cache time of the pre-cached data is greater than a first set time; The second cache clearing unit is used to clear the pre-cached data when it is accessed within a time threshold and the access end time of the pre-cached data is greater than a second set time.

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