A Network Hotspot Sniffing Method and System Based on User Preferences

Abstract

The present invention relates to the field of network hot spot retrieval and push, and discloses a network hot spot sniffing method and system based on user preferences. Through the shared mounting setting of the preference retrieval tree, the sharing and synchronization of user preference information among multiple software of the same type are realized. Furthermore, when the user conducts relevant information retrieval, complementary retrieval and push can be carried out through the different retrieval logics of multiple software and the available retrieval databases in the cloud, so as to accurately judge and obtain the user's preferred content. Compared with the independent software retrieval method, it can effectively avoid the inaccurate preference judgment caused by the limitations of the software retrieval mode and the database, and at the same time can replace the inefficient behavior mode of the user's own manual multi-software retrieval.

Description

Technical Field

[0001] The present invention relates to the field of network hot spot retrieval and push, and specifically to a method and system for network hot spot sniffing based on user preferences. Background Art

[0002] Sniffing network hot spots and promoting content based on user preferences have many application scenarios in daily life, production, and social activities. For example, the target group of a product can obtain promotion, hot news and videos can be pushed according to the user's preferences, and users can retrieve and obtain information or hot spots on the network, which facilitates users to efficiently obtain information from all aspects and effectively screen it, reducing the time spent by users browsing non-preferred content.

[0003] In the prior art, for different software, there are differences in the retrieval mode, retrieval concept, and total database that can be retrieved provided by its manufacturer. Therefore, when a user uses the retrieval system of a software to retrieve hot content, due to the limitations of the system itself, the efficiency of the retrieval results meeting the user's expectations is low. Even during the user's browsing and selection process, due to the inability to match appropriate preference keywords, the retrieval target direction is lost. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for network hot spot sniffing based on user preferences to solve the problems raised in the above background art.

[0005] To achieve the above purpose, the present invention provides the following technical solutions:

[0006] A method for network hot spot sniffing based on user preferences includes:

[0007] In the current retrieval system, obtain the historical preferences of the user to match hot spot information, and perform preference matching on the hot spot information through user browsing feedback to obtain the user's current preference retrieval tree, where the preference retrieval tree is used to represent the relevance of recording hot spot keywords and hot spot related words;

[0008] Detect software switching of the user. When a switching feedback signal is triggered, generate a shared mount based on the preference retrieval tree, where the shared mount is used to record and update the preference retrieval tree, and the shared mount is independent of the software and the retrieval system;

[0009] Synchronize the preference retrieval tree through the shared mount and perform hot spot information matching based on the new retrieval system to obtain hot spot information complementary to the previous retrieval system, and perform preference matching through user browsing feedback, and update the shared mount based on the preference matching result;

[0010] When the shared mount is updated, re-match the popularity information of multiple retrieval systems based on the updated preference retrieval tree, perform a difference set operation based on the matching results and the corresponding historical push records of the current shared mount, and generate and push updated popularity information according to the operation results.

[0011] As a further solution of the present invention: the shared mount correspondingly includes permission groups, and the permission groups are correspondingly provided with identification codes for distinguishing multiple different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software;

[0012] When a feedback signal is triggered to generate a shared mount, obtain the shared permissions of the software started by subsequent switching, match the permission groups shared with the current software, and copy the preference retrieval tree in the shared mount to push and update it in real time among multiple retrieval systems.

[0013] As a still further solution of the present invention: it further includes a weight evaluation step, specifically including:

[0014] Basic weight evaluation step: Obtain the popularity data of several hot keywords in the preference retrieval tree in the cloud, assign values to the hot keywords based on the popularity data, and select the hot keyword with the highest popularity as the current core weight object;

[0015] Characteristic weight evaluation step: Obtain user browsing feedback in real time, perform statistics based on the user browsing feedback, obtain the browsing times statistics of different hot keywords and the corresponding content browsing completion rate of the user, and assign values to the browsing times statistics and content browsing completion rate according to the preset weights to obtain characteristic weights. The characteristic weights are used to weaken the basic weights at a rated ratio and improve the weight relationship of multiple hot keywords.

[0016] As a still further solution of the present invention: it further includes a local association step:

[0017] Perform an associated retrieval on the input system based on the high-weight hot keywords corresponding to the preference retrieval tree, and obtain multiple associated phrases with the hot keywords through the user's historical retrieval preferences. The associated phrases are used to represent the similar phrases to the hot keywords in the user's frequently used vocabulary;

[0018] Update the preference retrieval tree through the associated phrases, and synchronously perform the matching and pushing of hot information. The associated retrieval acts on multiple corresponding software with shared permissions based on the current permission group.

[0019] As a still further solution of the present invention: it further includes steps:

[0020] When the user performs software switching, the software corresponding retrieval system retrieves through cloud hot-spot information and user preference information within the software, generates a personalized push list, and the personalized push list is used to represent the basic push content of the software;

[0021] Generate a promotion replacement data link based on the hot-spot information obtained from the preference retrieval tree. The promotion replacement data link is juxtaposed with the basic push content and is in an independent user space. The user preference browsing behavior generated based on the promotion replacement data link does not act on the user preference record of the software itself;

[0022] Obtain the selection signal of the user for the promotion replacement data link, and perform selective push on the personalized push list or hot-spot information based on the selection signal.

[0023] An embodiment of the present invention aims to provide a network hot-spot sniffing system based on user preferences, including:

[0024] A preference rating module, which is used to obtain the historical preferences of the user in the current retrieval system to match the hot-spot information, and perform preference matching on the hot-spot information through the user browsing feedback to obtain the current preference retrieval tree of the user. The preference retrieval tree is used to represent the relevance of recording hot-spot keywords and hot-spot related words;

[0025] A shared mounting module, which is used to detect software switching of the user. When a switching feedback signal is triggered, a shared mount is generated based on the preference retrieval tree. The shared mount is used to record and update the preference retrieval tree, and the shared mount is independent of the software and the retrieval system;

[0026] A complementary matching module, which is used to synchronize the preference retrieval tree through the shared mount and perform hot-spot information matching based on the new retrieval system, obtain hot-spot information complementary to the previous retrieval system, and perform preference matching through the user browsing feedback, and update the shared mount based on the preference matching result;

[0027] An update synchronization module, which is used to, when the shared mount is updated, perform re-matching of the heat information on multiple retrieval systems based on the updated preference retrieval tree, perform a difference set operation based on the matching result and the corresponding historical push record of the current shared mount, and generate and push updated heat information according to the operation result.

[0028] As a further solution of the present invention: The shared mount correspondingly includes permission groups, and the permission groups are correspondingly provided with identification codes for distinguishing multiple different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software, and also includes a cloning grouping unit;

[0029] The cloning grouping unit is used to obtain the shared permissions of the subsequent switched-on software when a feedback signal is triggered to generate a shared mount, so as to match the permission group shared with the current software, and copy the preference retrieval tree in the shared mount for real-time push and update among multiple retrieval systems.

[0030] As a further aspect of the present invention: it further includes a weight evaluation module, specifically including:

[0031] The basic weight evaluation unit is used to obtain the popularity data of several hot keywords in the preference retrieval tree in the cloud, assign values to the hot keywords based on the popularity data, and select the hot keyword with the highest popularity as the current core weight object;

[0032] The characteristic weight evaluation unit is used to obtain the user browsing feedback in real time, perform statistics based on the user browsing feedback, obtain the browsing times statistics of different hot keywords by the user and the corresponding content browsing completion rate, and assign values to the browsing times statistics and content browsing completion rate according to the preset weights to obtain the characteristic weights, and the characteristic weights are used to weaken the basic weights at a rated ratio and improve the weight relationship of multiple hot keywords.

[0033] As a further aspect of the present invention: it further includes a local association optimization module, specifically including:

[0034] The input retrieval matching unit is used to perform associated retrieval on the input system based on the high-weight hot keywords corresponding to the preference retrieval tree, and obtain multiple associated phrases with the hot keywords through the user's historical retrieval preferences, and the associated phrases are used to represent the similar phrases to the hot keywords in the user's frequently used vocabulary;

[0035] The input feature update unit is used to update the preference retrieval tree through the associated phrases, and synchronously perform matching and pushing of hot information, and the associated retrieval acts on multiple corresponding software with shared permissions based on the current permission group.

[0036] As a further aspect of the present invention: it further includes a promotion switching management module, specifically including:

[0037] The basic retrieval unit is used to, when the user performs software switching, the software corresponding retrieval system retrieves through the cloud hot information and the user preference information in the software to generate a personalized push list, and the personalized push list is used to represent the basic push content of the software;

[0038] An interactive retrieval unit, configured to generate a promoted replacement data link based on hot information obtained from a preference retrieval tree. The promoted replacement data link is juxtaposed with the basic push content and is in an independent user space. The user preference browsing behavior generated based on the promoted replacement data link does not act on the user preference record of the software itself.

[0039] A retrieval output unit, configured to obtain a selection signal of the user for the promoted replacement data link, and perform selective push on the personalized push list or hot information based on the selection signal.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: Through the shared mounting setting of the preference retrieval tree, the sharing and synchronization of user preference information among multiple software of the same type are realized. Furthermore, when the user conducts relevant information retrieval, complementary retrieval push can be performed through different retrieval logics of multiple software and the available retrieval databases in the cloud, so as to accurately judge and obtain the user's preference content. Compared with the independent software retrieval method, it can effectively avoid inaccurate preference judgment caused by the limitations of the software retrieval mode and the database, and at the same time can replace the inefficient behavior mode of the user manually retrieving multiple software by himself. Description of the Drawings

[0041] Figure 1 It is a flowchart of a method for sniffing network hotspots based on user preferences.

[0042] Figure 2 It is a flowchart of the software switching judgment step in a method for sniffing network hotspots based on user preferences.

[0043] Figure 3 It is a block diagram of the composition of a system for sniffing network hotspots based on user preferences. Detailed Embodiments

[0044] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and 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.

[0045] The following describes in detail the specific implementation manners of the present invention with reference to specific embodiments.

[0046] As Figure 1 described, a method for sniffing network hotspots based on user preferences provided by an embodiment of the present invention includes the following steps:

[0047] S10. In the current retrieval system, obtain the user's historical preferences to match hot information, and perform preference matching on the hot information through the user's browsing feedback to obtain the user's current preference retrieval tree, where the preference retrieval tree is used to represent the relevance of recording hot keywords and hot associated words;

[0048] S20. Detect software switching for the user. When a switching feedback signal is triggered, generate a shared mount based on the preference retrieval tree. The shared mount is used to record and update the preference retrieval tree, and the shared mount is independent of the software and the retrieval system;

[0049] S30. Synchronize the preference retrieval tree through the shared mount and perform hot information matching based on the new retrieval system to obtain hot information complementary to the previous retrieval system, and perform preference matching through the user's browsing feedback, and update the shared mount based on the preference matching result;

[0050] S40. When the shared mount is updated, perform re-matching of heat information on multiple retrieval systems based on the updated preference retrieval tree, perform a difference set operation based on the matching result and the corresponding historical push record of the current shared mount, and generate and push updated heat information according to the operation result.

[0051] In this embodiment, a network hotspot sniffing method based on user preferences is provided. Through the shared mounting setting of the preference retrieval tree, the sharing and synchronization of user preference information among multiple software of the same type are realized. Furthermore, when the user conducts relevant information retrieval, complementary retrieval push can be performed through the different retrieval logics of multiple software and the available retrieval databases in the cloud, so as to accurately judge and obtain the user's preferred content. Compared with the independent software retrieval method, it can effectively avoid the inaccurate preference judgment caused by the limitations of the software retrieval mode and database. At the same time, it can also replace the inefficient behavior mode of the user manually retrieving multiple software by himself. In the prior art, for different software, there are differences in the retrieval mode, retrieval concept, and total database that can be retrieved provided by the manufacturers. Therefore, when the user uses the retrieval system of a software to retrieve hotspot content, due to the limitations of the system itself, the efficiency of the retrieval results meeting the user's expectations is relatively low. Even during the user's browsing and selection process, due to the inability to match appropriate preference keywords, the retrieval target direction is lost. In daily life, when we conduct content retrieval, in order to obtain more content that meets our needs, we may use multiple software for retrieval and select and accept the content. Since the data between software cannot be shared, the actual efficiency and effect are relatively poor. To solve this technical problem, the technical solution provided in this application is as follows: when the user retrieves and browses hotspot information in a certain software, the retrieval preference is judged according to the push and the content feedback of the user's browsing, so as to obtain the user's retrieval preference tree (i.e., the correlation between retrieval associated words and keywords) within a certain period of time. If the system detects that the user switches software during the continuous period, it indicates that the user may need to retrieve the content again through the retrieval system of other retrieval software to supplement the effective content that the current software fails to push to him. Therefore, at this time, the current system can export the preference retrieval tree and split it out of the software in the form of shared mounting, so that multiple software participating in the retrieval can synchronously share and update it. At this time, the preferences established by the user's retrieval and browsing feedback in multiple software will be synchronized. Because the databases provided by different software and the retrieval push logics of the retrieval systems are different, this will enable the preference retrieval trees generated by multiple software to be synchronized and complementarily updated within the shared mounting, and further accurately judge and determine the user's preferences and needs, optimizing the sniffing retrieval and promotion effect of hotspot data. For the content with low popularity in software A that cannot be effectively pushed, after complementary updating by software B and C, effective sniffing and retrieval can be achieved to meet the user's retrieval needs.

[0052] As another preferred embodiment of the present invention, the shared mount correspondingly includes permission groups, and identity identification codes are correspondingly provided for the permission groups to distinguish multiple different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software;

[0053] When a feedback signal triggers the generation of a shared mount, obtain the shared permissions of the software started by subsequent switching to match the permission group shared with the current software, and copy the preference retrieval tree in the shared mount to push and update it in real time among multiple retrieval systems.

[0054] In this embodiment, a setting scheme for permission groups is supplemented for the shared mount. The purpose of setting permission groups is to group several different types of software in the user device based on requirements and manage information permissions at the same time. For example, when a user retrieves short video type content and information type information, the software used is definitely different. How the shared mount is triggered and who can read it need to be defined and restricted. Therefore, the user can set according to their daily usage habits. For example, ABC software are all short video type software, and the user habitually uses the three software for collaborative retrieval, then they can be set in the same permission group. However, at the same time, because there may be some information security issues with B software, the user does not set the shared permissions for B software, which can limit the access of B software to the data in the shared mount. That is, for this permission group, its shared permission list includes AC software. That is, when AC software is switched, it will trigger and establish a shared mount and update the content of both parties in real time; Here, the step of copying the preference retrieval tree is also supplemented. This setting is applicable when the same software exists in multiple permission groups at the same time. For example, A also exists in another group with DF software. When it switches to C software, if the original preference retrieval tree in the shared mount is directly synchronized and updated, the following situation may occur: the user switches to D software again, but at this time, the preference retrieval tree in the shared mount is already the content updated by C software, but DF software cannot share the user preference content of C software. Therefore, the original preference retrieval tree can be retained by copying to adapt to complex application scenarios.

[0055] As another preferred embodiment of the present invention, it further includes a weight evaluation step, specifically including:

[0056] Basic weight evaluation step: Obtain the popularity data of several hot keywords in the preference retrieval tree in the cloud, assign values to the hot keywords based on the popularity data, and select the hot keyword with the highest popularity as the current core weight object;

[0057] The characteristic weight evaluation step is to obtain the user's browsing feedback in real time, perform statistics based on the user's browsing feedback, obtain the browsing times statistics of different hot keywords by the user and the corresponding content browsing completion rate, and assign values to the browsing times statistics and content browsing completion rate according to the preset weights to obtain the characteristic weights. The characteristic weights are used to weaken the basic weights at a rated ratio and improve the weight relationship of multiple hot keywords.

[0058] In this embodiment, the weight evaluation step is supplemented. The process of obtaining the user's preference retrieval tree and weight keywords is a step-by-step judgment process. Therefore, when performing the initial push, there are two types. One is that when the user does not perform keyword retrieval, the push is based on the hot information. The other is that when the user performs keyword retrieval, the push is based on the hot content that matches or is relatively consistent with the keyword, that is, the process of assigning values to different keywords according to the popularity; based on the initial push, the user's browsing behavior for each pushed content can be used to judge their interest level. The judgment can be based on the browsing times of each keyword, the browsing completion rate of the content corresponding to the keyword (the proportion of the content browsed by the user in the whole content of a pushed content), etc. For the keywords that the user is more interested in, characteristic weights are assigned to them, so that in subsequent retrievals, more relevant content can be retrieved.

[0059] As another preferred embodiment of the present invention, it further includes a local association step:

[0060] Based on the high-weight hot keywords corresponding to the preference retrieval tree, an associated retrieval is performed on the input system, and multiple associated phrases with the hot keywords are obtained through the user's historical retrieval preferences. The associated phrases are used to represent the similar phrases in the user's frequently used vocabulary that are similar to the hot keywords;

[0061] The preference retrieval tree is updated through the associated phrases, and at the same time, the matching and pushing of hot information are performed. The associated retrieval acts on multiple corresponding software with sharing permissions based on the current permission group.

[0062] In this embodiment, when in another software, if the user has never performed relevant content retrieval, the first retrieval of the system may be relatively slow for the user's preference judgment and requires a training process. Therefore, in order to facilitate the realization of the purpose of efficient retrieval matching, the software can obtain the associated keyword vocabulary by sending a record request to the local tool software. For example, the user's text input software can record the user's historical output vocabulary and sentence content, so that similar keywords can be matched and screened by the user.

[0063] As Figure 2 shown, as another preferred embodiment of the present invention, it further includes steps:

[0064] S51. When the user performs software switching, the software corresponding retrieval system retrieves through cloud hot-spot information and user preference information within the software to generate a personalized push list, and the personalized push list is used to represent the basic push content of the software.

[0065] S52. Generate a promotion replacement data link based on the hot-spot information obtained from the preference retrieval tree. The promotion replacement data link is juxtaposed with the basic push content and is in an independent user space. The user preference browsing behavior generated based on the promotion replacement data link does not act on the user preference record of the software itself.

[0066] S53. Obtain the selection signal of the user for the promotion replacement data link, and perform selective push on the personalized push list or hot-spot information based on the selection signal.

[0067] In this embodiment, relevant content is further optimized and supplemented based on a common usage scenario. The specific scenario is as follows: When the user switches software within the permission group, it is not for the auxiliary retrieval of multiple software, but just for daily software usage switching. Therefore, a differentiation process is set here. The software can provide two sets of push content, namely, the basic push content based on the software's own network hot-spot information and user preferences, and the retrieval content based on shared mounts (i.e., promotion replacement data). When the user needs to perform collaborative hot-spot preference sniffing retrieval of multiple software, it is triggered through the promotion replacement data link.

[0068] As Figure 3 shown, the present invention also provides a network hot-spot sniffing system based on user preferences, which includes:

[0069] A preference rating module 100, which is used to obtain the historical preferences of the user in the current retrieval system to match hot-spot information, and perform preference matching on the hot-spot information through the user browsing feedback to obtain the user's current preference retrieval tree. The preference retrieval tree is used to represent the relevance of recording hot-keywords and hot-related words.

[0070] A shared mount module 200, which is used to detect software switching of the user. When a switching feedback signal is triggered, a shared mount is generated based on the preference retrieval tree. The shared mount is used to record and update the preference retrieval tree, and the shared mount is independent of the software and the retrieval system.

[0071] A complementary matching module 300, which is used to synchronize the preference retrieval tree through the shared mount and perform hot-spot information matching based on the new retrieval system to obtain hot-spot information complementary to the previous retrieval system, and perform preference matching through the user browsing feedback, and update the shared mount based on the preference matching result.

[0072] An update synchronization module 400, which is used to, when the shared mount is updated, rematch the popularity information of multiple retrieval systems based on the updated preference retrieval tree, perform a difference set operation based on the matching result and the corresponding historical push record of the current shared mount, generate updated popularity information according to the operation result, and push it.

[0073] As another preferred embodiment of the present invention, the shared mount correspondingly includes permission groups, and each permission group is correspondingly provided with an identification code for distinguishing multiple different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software. It also includes a cloning grouping unit;

[0074] The cloning grouping unit is used to, when a feedback signal is triggered to generate a shared mount, obtain the shared permissions of the software started by subsequent switching, match the permission groups shared with the current software, and copy the preference retrieval tree in the shared mount to push and update it in real time among multiple retrieval systems.

[0075] As another preferred embodiment of the present invention, it further includes a weight evaluation module, specifically including:

[0076] A basic weight evaluation unit, which is used to obtain the popularity data of several hot keywords in the preference retrieval tree in the cloud, assign values to the hot keywords based on the popularity data, and select the hot keyword with the highest popularity as the current core weight object;

[0077] A characteristic weight evaluation unit, which is used to obtain the user browsing feedback in real time, perform statistics based on the user browsing feedback, obtain the browsing times statistics of different hot keywords by the user and the corresponding content browsing completion rate, and assign values to the browsing times statistics and the content browsing completion rate according to the preset weight to obtain the characteristic weight. The characteristic weight is used to weaken the basic weight at a rated ratio and improve the weight relationship of multiple hot keywords.

[0078] As another preferred embodiment of the present invention, it further includes a local association optimization module, specifically including:

[0079] An input retrieval matching unit, which is used to perform an associated retrieval on the input system based on the high-weight hot keywords corresponding to the preference retrieval tree, and obtain multiple associated phrases with the hot keywords through the user's historical retrieval preferences. The associated phrases are used to represent the similar phrases to the hot keywords in the user's high-frequency used vocabulary;

[0080] An input feature update unit, which is used to update the preference retrieval tree through the associated phrases, and synchronously perform the matching and pushing of hot information. The associated retrieval acts on multiple corresponding software with shared permissions based on the current permission group.

[0081] As another preferred embodiment of the present invention, it further includes a promotion switching management module, specifically including:

[0082] A basic retrieval unit, which is used for when a user performs software switching, the software corresponding retrieval system retrieves through cloud hot-spot information and user preference information within the software to generate a personalized push list, and the personalized push list is used to represent the basic push content of the software;

[0083] An interactive retrieval unit, which is used to generate a promotion replacement data link based on the hot-spot information obtained from the preference retrieval tree. The promotion replacement data link is juxtaposed with the basic push content and is in an independent user space. The user preference browsing behavior generated based on the promotion replacement data link does not act on the user preference record of the software itself;

[0084] A retrieval output unit, which is used to obtain the selection signal of the user for the promotion replacement data link, and perform selective push on the personalized push list or hot-spot information based on the selection signal.

[0085] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. 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 methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of 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 (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0086] Other embodiments of the present disclosure will be readily apparent to those skilled in the art after considering the disclosure in the specification and the embodiments. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include known common general knowledge or conventional technical means in the technical field not disclosed in the present disclosure. The specification and the embodiments are only regarded as exemplary, and the true scope and spirit of the present disclosure are pointed out by the claims.

[0087] It should be understood that the present disclosure is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present disclosure is only limited by the appended claims.

Claims

1. A network hotspot sniffing method based on user preference, characterized in that: Include: In the current search system, the user's historical preferences are obtained to match the hot information, and the hot information is matched with preferences through the user's browsing feedback to obtain the user's current preference search tree, which is used to characterize the relevance of the hot keywords and hot related words; Perform software switching detection on the user, and when a switching feedback signal is triggered, generate a shared mount based on the preference search tree, the shared mount is used to record and update the preference search tree, and the shared mount is independent of the software and the search system; Synchronize the preference search tree through shared mounts and match hot information based on the new search system to obtain hot information that complements the previous search system, perform preference matching through user browsing feedback, and update the shared mount based on the preference matching results; When the shared mount is updated, the heat information of multiple retrieval systems is re-matched based on the updated preference retrieval tree, a difference operation is performed based on the matching results and the corresponding historical push records of the current shared mount, and updated heat information is generated and pushed according to the operation results.

2. According to the method for sniffing network hotspots based on user preference according to claim 1, it is characterized in that: The shared mount corresponds to a permission group, and the permission group corresponds to an identity identification code for distinguishing a plurality of different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software; When a feedback signal is triggered to generate a shared mount, the shared permissions of the software that is subsequently switched and started are obtained to match the permission group shared with the current software, and the preference search tree in the shared mount is copied to be pushed and updated in real time between multiple search systems.

3. A network hotspot sniffing method based on user preference according to claim 2, characterized in that: It also includes a weight evaluation step, including: A basic weight evaluation step, obtaining the heat data of several hot keywords in the preference search tree in the cloud, assigning values ​​to the hot keywords based on the heat data, and selecting the hot keyword with the highest heat as the current core weight object; The characterization weight evaluation step obtains user browsing feedback in real time, performs statistics based on the user browsing feedback, obtains the user's browsing statistics for different hot keywords and the corresponding content browsing completion rate, and assigns the browsing statistics and content browsing completion rate according to the preset weight ratio to obtain the characterization weight. The characterization weight is used to weaken the basic weight at a rated ratio and improve the weight relationship of multiple hot keywords.

4. According to the method of sniffing network hotspots based on user preference according to claim 3, it is characterized in that: A local association step is also included: Based on the high-weight hot keywords corresponding to the preference search tree, an input system is searched for association, and multiple associated phrases with the hot keywords are obtained through the user's historical search preferences, wherein the associated phrases are used to represent phrases similar to the hot keywords in the user's frequently used vocabulary; The preference search tree is updated through the associated phrases, and the hot information is matched and pushed simultaneously. The associated search acts on the corresponding multiple software with sharing permissions based on the current permission group.

5. According to the method for sniffing network hotspots based on user preference according to claim 2, it is characterized in that: Also includes the steps: When the user switches software, the software corresponding retrieval system searches through the cloud hotspot information and the user preference information in the software to generate a personalized push list, which is used to represent the basic push content of the software; Generate a promotion replacement data link based on the hot information obtained from the preference search tree. The promotion replacement data link is parallel to the basic push content and is in an independent user space. The user preference browsing behavior generated based on the promotion replacement data link does not affect the user preference record of the software itself. A selection signal of the user for the promotion replacement data link is obtained, and the personalized push list or hot spot information is selected and pushed based on the selection signal.

6. A network hotspot sniffing system based on user preference, characterized in that: Include: A preference evaluation module is used to obtain the user's historical preferences in the current search system to match hot information, and to perform preference matching on the hot information through user browsing feedback to obtain the user's current preference search tree, which is used to characterize the relevance of hot keywords and hot associated words; A shared mount module, used for detecting software switching of users, and when a switching feedback signal is triggered, generating a shared mount based on the preference search tree, wherein the shared mount is used for recording and updating the preference search tree, and the shared mount is independent of the software and the search system; A complementary matching module is used to synchronize the preference search tree through the shared mount and match the hot information based on the new search system, obtain the hot information that complements the previous search system, perform preference matching through user browsing feedback, and update the shared mount based on the preference matching results; The update synchronization module is used to rematch the heat information of multiple retrieval systems based on the updated preference retrieval tree when the shared mount is updated, perform difference set operations based on the matching results and the corresponding historical push records of the current shared mount, generate and push updated heat information based on the operation results.

7. A network hotspot sniffing system based on user preference according to claim 6, characterized in that: The shared mount includes a permission group, and the permission group is provided with an identity code for distinguishing a plurality of different permission groups. Each permission group corresponds to a different shared permission list, and the shared permission list is used to record the permission ownership status of the software, and also includes a clone grouping unit; The clone grouping unit is used to obtain the sharing permissions of the software that is subsequently switched and started when a feedback signal is triggered to generate a shared mount to match the permission group shared with the current software, and to copy the preference retrieval tree in the shared mount to push and update it in real time between multiple retrieval systems.

8. A network hotspot sniffing system based on user preference according to claim 7, characterized in that: It also includes a weight evaluation module, including: A basic weight evaluation unit, used to obtain the heat data of several hot keywords in the preference search tree in the cloud, assign values ​​to the hot keywords based on the heat data, and select the hot keyword with the highest heat as the current core weight object; The characterization weight evaluation unit is used to obtain user browsing feedback in real time, perform statistics based on user browsing feedback, obtain user browsing statistics for different hot keywords and corresponding content browsing completion rates, and assign values ​​to the browsing statistics and content browsing completion rates according to preset weight ratios to obtain characterization weights. The characterization weights are used to weaken the basic weights at a rated ratio and improve the weight relationship between multiple hot keywords.

9. A network hotspot sniffing system based on user preference according to claim 8, characterized in that: It also includes a local association optimization module, including: An input search matching unit, used to perform an associated search on the input system based on the high-weight hot keywords corresponding to the preference search tree, and obtain multiple associated phrases with the hot keywords through the user's historical search preferences, wherein the associated phrases are used to represent phrases similar to the hot keywords in the user's frequently used vocabulary; The input feature updating unit is used to update the preference search tree through the associated phrases, and simultaneously match and push hot information. The associated search acts on the corresponding multiple software with shared permissions based on the current permission group.

10. A network hotspot sniffing system based on user preference according to claim 7, characterized in that: It also includes a promotion switching management module, including: A basic search unit, which is used for when a user switches software, the software corresponding search system searches through the cloud hot spot information and the user preference information in the software to generate a personalized push list, and the personalized push list is used to represent the basic push content of the software; An interactive retrieval unit, used to generate a promotion replacement data link based on the hot information obtained from the preference retrieval tree, wherein the promotion replacement data link is parallel to the basic push content and is in an independent user space, and the user preference browsing behavior generated based on the promotion replacement data link does not affect the user preference record of the software itself; The retrieval output unit is used to obtain a selection signal of the user for the promotion replacement data link, and select and push the personalized push list or hot spot information based on the selection signal.

Images