Internet recommendation method, system, device and computer readable storage medium

Abstract

The application discloses an Internet recommendation method, system and device and a computer readable storage medium, and relates to the technical field of computers. First, current search information input by a client is acquired, and then a first node corresponding to the current search information in a tree structure information chain is determined. In a server end, historical search and storage information input by other clients are also stored, and a second node corresponding to the tree structure information chain is stored. The first node is matched with each second node according to a preset matching rule, and a matching result is sent to the client. The range of the primary screening is ensured to be large enough, and the range of the secondary screening is reduced, so that the user can find a target social user more easily.

Description

[0001] This application claims priority to Chinese Patent Application No. 202110375733.3, filed on April 8, 2021, entitled “A Combinatorial Innovation Recommendation Method and System”, the entire contents of which are incorporated herein by reference. Technical Field

[0002] This invention relates to the field of computer technology, and in particular to an internet recommendation method, system, apparatus, and computer-readable storage medium. Background Technology

[0003] The internet has brought endless possibilities for long-distance social interaction. For example, users can enter search information into search engines like Baidu and find target social users that match their search criteria. However, the initial screening results are enormous, requiring users to manually filter them to find those that meet their specific requirements. Alternatively, users can use social media platforms like Facebook or WeChat to find target users, but this requires prior knowledge of the target users' account information, limiting the scope of the initial screening. Especially in innovative fields, social interaction often requires combinations of interdisciplinary talent. The problems, fields, talent, and keywords, and their combinations, in original and cutting-edge innovation, are often imprecise and difficult to define. Typical examples include combinations between investment and finance experts and innovative technology experts, or interdisciplinary combinations of innovative technology experts in fringe sciences. The expressed social purpose is often vague, and the system needs to help users transition from vague input to precisely defined matches. Therefore, it is essential to achieve both the largest possible initial matching range and a significant reduction in the workload of secondary manual screening. Summary of the Invention

[0004] The purpose of this invention is to provide an internet recommendation method, system, device, and computer-readable storage medium that can ensure a sufficiently large initial screening range and reduce the range of secondary screening when users engage in internet social networking, making it easier for users to find target social users.

[0005] To address the aforementioned technical problems, this invention provides an internet recommendation method applied to the server side, the method comprising:

[0006] Get the current search information entered by the client;

[0007] The first node corresponding to the current search information is determined in the tree structure information chain pre-stored in the server. The tree structure information chain includes multiple nodes in a tree structure and node information corresponding to each node.

[0008] According to the preset matching rules, the first node is matched with each second node corresponding to the historical search and storage information of other clients stored in the server and the matching results are obtained.

[0009] The matching result is sent to the client.

[0010] Preferably, according to a preset matching rule, the first node is matched with the second node corresponding to the historical search and storage information of other clients stored in the server, and a matching result is obtained, including:

[0011] Based on the tree-structured information chain, the distances between the first node and each of the second nodes are obtained respectively;

[0012] Arrange the distances sequentially from nearest to farthest to obtain the first distance sequence;

[0013] Based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the second node sequence is obtained;

[0014] The matching result is obtained based on the correspondence between the second node sequence and the historical search and storage information.

[0015] Preferably, when there are multiple second nodes that are all equidistant from the first node, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes:

[0016] Based on the tree structure information chain, the relationship between each second node that is equidistant from the first node and the first node is determined. The relationship between the second node and the first node includes the second node being a child node of the first node, the second node being a sibling node of the first node, and the second node being a parent node of the first node.

[0017] Arrange the second nodes in the second node sequence that are equidistant from the first node in the following order: the second node is a child node of the first node, the second node is a parent node of the first node, and the second node is a sibling node of the first node.

[0018] Preferably, when multiple identical distances exist in the first distance sequence, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes:

[0019] Based on the storage time of each second node, the second nodes in the second node sequence that are equidistant from the first node are arranged in order from latest to earliest storage time.

[0020] Preferably, the current search information input by the client is obtained, including:

[0021] The system obtains the current search information selected by the client from the preset menu bar, wherein the structure of the preset menu bar is consistent with the structure of the tree structure information chain or with the structure of any level in the tree structure information chain.

[0022] Preferably, obtaining the current search information input by the client also includes:

[0023] Obtain the current custom search information input by the client;

[0024] Determining the first node in the tree-structured information chain pre-stored on the server that corresponds to the current search information includes:

[0025] Determine the first node in the tree-structured information chain that corresponds to the current search information and / or the current custom search information selected by the client from the preset menu bar.

[0026] To solve the above-mentioned technical problems, the present invention also provides an Internet recommendation system, comprising:

[0027] The search information acquisition unit is used to acquire search information input by the client.

[0028] The first node determination unit is used to determine the first node in the tree structure information chain pre-stored in the server that corresponds to the search information;

[0029] The matching unit is used to match the first node with each second node corresponding to the historical search and storage information of other clients stored in the server according to a preset matching rule and obtain the matching result;

[0030] A sending unit is used to send the matching result to the client.

[0031] To solve the above-mentioned technical problems, the present invention also provides an Internet recommendation device, comprising:

[0032] Memory, used to store computer programs;

[0033] A processor is used to implement the steps of the above-described Internet recommendation method when executing the computer program.

[0034] To address the aforementioned technical problems, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned Internet recommendation method.

[0035] In summary, this invention discloses an internet recommendation method, system, device, and computer-readable storage medium. First, it obtains the current search information input by the client, and then determines the first node in a tree-structured information chain corresponding to the current search information. The server also stores second nodes corresponding to other client-input search information in the tree-structured information chain. The first node is matched with each of the second nodes according to preset matching rules, and the matching results are sent to the client. This ensures a sufficiently large initial screening range while reducing the range of secondary screening, making it easier for users to find target social users. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the prior art and embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A flowchart of an Internet recommendation method provided by the present invention;

[0038] Figure 2 This is a schematic diagram of the tree-structured information chain in an internet recommendation method provided by the present invention;

[0039] Figure 3 This is a schematic diagram of a two-sided structure for an internet recommendation method provided by the present invention. Detailed Implementation

[0040] The core of this invention is to provide an internet recommendation method, system, device, and computer-readable storage medium that can ensure a sufficiently large initial screening range and reduce the range of secondary screening when users engage in internet social networking, making it easier for users to find target social users.

[0041] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Please refer to Figure 1 , Figure 1 A flowchart of an internet recommendation method provided by the present invention, which is applied on the server side, includes:

[0043] S1. Obtain the current search information input by the client;

[0044] S2. Determine the first node in the tree structure information chain pre-stored on the server that corresponds to the current search information. The tree structure information chain includes multiple nodes in a tree structure and node information that corresponds one-to-one with each node.

[0045] S3. According to the preset matching rules, match the first node with each second node corresponding to the historical search and storage information of other clients stored on the server and obtain the matching results;

[0046] S4. Send the matching results to the client.

[0047] Given that current technologies generate a large number of search results when searching for target social media users via internet search engines, a significant amount of time is required for manual secondary filtering of these initial results. Existing technologies also utilize social media platforms like WeChat to search for target users, but this method requires prior knowledge of the target user's social media account, resulting in a very limited initial search scope.

[0048] To address the aforementioned technical problems, this application provides an internet recommendation algorithm. When a user inputs current search information through a client, the server retrieves this search information and then obtains the first node corresponding to the current search information based on a tree-structured information chain. This tree-structured information chain is a multi-level tree structure, with one or more nodes at each level, and each node has corresponding node information. After obtaining the first node, it is matched with various second nodes stored on the server according to preset matching rules. This narrows down the initial screening range and ensures search accuracy. The matching results are then sent to the client to achieve the goal of finding the target social users.

[0049] Furthermore, the historical search and storage information in this application includes search information input by other clients in the past, as well as storage information input by other clients that is pre-stored on the server. The search information input by other clients in the past and the storage information pre-stored on the server correspond to the node information in the tree structure information chain, so as to obtain the corresponding second node and matching result.

[0050] It should also be noted that if a second node corresponding to historical search and stored information contains a node identical to the first node, then the client currently searching for the target social user will be matched with other clients corresponding to that second node first. Please refer to [link / reference]. Figure 2 , Figure 2 This is a schematic diagram of the tree-structured information chain in an internet recommendation method provided by the present invention. Figure 2 It is a special case abstracted from the World Intellectual Property Organization's IPC classification system, assuming Figure 2 If the first node corresponding to the client searching for the target social user is node S, and node S' is the same node as node S, then other clients corresponding to node S' are matched with the client corresponding to the first node first.

[0051] Taking the IPC patent classification number as an example, it consists of a vertical section, major categories, minor categories, major groups, subgroups, and dotted subgroups. When a user wants to search for a target social media user to understand their expertise and needs related to patents, due to the numerous patent classifications, it is difficult for the user to accurately find the target social media user using existing methods. Based on the patent classification number, which can be categorized according to the vertical section, major categories, minor categories, major groups, subgroups, and dotted subgroups, this application sets up a tree-structured information chain on the server side. This tree-structured information chain includes six levels of nodes corresponding to the vertical section, major categories, minor categories, major groups, subgroups, and dotted subgroups. When a user wants to search for a target social media user to understand patent-related information, the server corresponds the user's current search information to a first node in the tree-structured information chain. Then, according to preset matching rules, the first node is matched with each second node stored on the server side, and finally the matching result is fed back to the client. This tree-structured information chain is also applicable to the Nice Classification of Goods and Services, the National Economic Classification, the Occupational Classification of Labour, etc.

[0052] In summary, this invention discloses an internet recommendation method, system, device, and computer-readable storage medium. First, it acquires the current search information input by the client, and then determines the first node in a tree-structured information chain corresponding to the current search information. The server also stores second nodes corresponding to other client-input search information in the tree-structured information chain. The first node is matched with each of the second nodes according to preset matching rules, and the matching results are sent to the client. This ensures a sufficiently large initial screening range while reducing the range of secondary screening, making it easier for users to find target social users.

[0053] Based on the above embodiments:

[0054] As one embodiment, according to preset matching rules, the first node is matched with the second node corresponding to the historical search and stored information of other clients stored on the server, and the matching result is obtained, including:

[0055] Based on the tree-structured information chain, the distances between the first node and each of the second nodes are obtained respectively;

[0056] Arrange the distances sequentially from nearest to farthest to obtain the first distance sequence;

[0057] Based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the second node sequence is obtained;

[0058] The matching results are obtained based on the correspondence between the second node sequence and the historical search and stored information.

[0059] In this embodiment, the distances between the first node and each of the second nodes stored on the server are first obtained based on a tree-structured information chain. In the tree-structured information chain, the closer the distance, the stronger the correlation between the first and second nodes, and thus the closer they are to the target social user the user wants to search for. Therefore, the distances are arranged sequentially from closest to furthest to obtain a first distance sequence. Then, based on the correspondence between each distance in the first distance sequence and the second nodes, a second node sequence is obtained, completing the matching between the first node and each of the second nodes. Finally, the matching result is obtained based on the correspondence between the second node sequence and historical search and stored information, achieving the goal of a small initial screening range and precise search when the user searches for a target social user.

[0060] It should be noted that the first distance sequence and the second node sequence in this application are intermediate data generated by the server to obtain the matching result. The first distance sequence and the second node sequence are not sent to the client. Only the final matching result is sent to the client for display.

[0061] Please refer to Figure 2 , Figure 2 This is a schematic diagram of the tree-structured information chain in an internet recommendation method provided by the present invention. Figure 2 Taking node S as an example, the distance between node M and node S is closer than the distance between node G and node S, so the matching degree between node M and node S is higher than that between node G and node S.

[0062] In a preferred embodiment, when multiple second nodes have the same distance from the first node, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes:

[0063] Based on the tree structure information chain, determine the relationship between each second node that is equidistant from the first node and the first node. The relationship between the second node and the first node includes the second node being a child node of the first node, the second node being a sibling node of the first node, and the second node being a parent node of the first node.

[0064] Arrange the second nodes in the second node sequence that are equidistant from the first node in the following order: second node is a child node of the first node, second node is a parent node of the first node, and second node is a sibling node of the first node.

[0065] In this embodiment, considering that there may be multiple second nodes with the same distance from the first node on the server side, but the nodes at each level in the tree structure information chain are divided from coarse to fine, and the information of the child nodes is more accurate, it is necessary to determine the relationship between each second node with the same distance from the first node and the first node, and then arrange each second node with the same distance from the first node in the second node sequence in the order of second node being a child node of the first node, second node being a parent node of the first node, and second node being a sibling node of the first node.

[0066] Please refer to Figure 2 , Figure 2 This is a schematic diagram of the tree-structured information chain in an internet recommendation method provided by the present invention. Figure 2 Nodes M, R, T, X, Y, and Z are all equidistant from node S. However, node M is the parent node of node S, nodes R and T are sibling nodes of node S, and nodes X, Y, and Z are child nodes of node S. Therefore, the order is: node X, node Y, node Z, node M, node R, and node T.

[0067] In a preferred embodiment, when multiple identical distances exist in the first distance sequence, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes:

[0068] Based on the storage time of each second node, the second nodes in the second node sequence that are equidistant from the first node are arranged in order of storage time from latest to earliest.

[0069] In this embodiment, considering that there may be multiple second nodes on the server side that are equidistant from the first node, but the second node with a later storage time indicates that the corresponding client's online time is closer to the client's current search time, and is more likely to successfully interact with the client, this embodiment also needs to arrange the second nodes in the second node sequence that are equidistant from the first node in order of their storage time from latest to earliest, based on their storage time.

[0070] by Figure 3 For example, Figure 3 This is a schematic diagram of a two-sided structure of an Internet recommendation method provided by the present invention. Figure 3In this diagram, S1, S2, S3, S4, S5, and S6 represent clients, while D1, D2, D3, D4, D5, and D6 represent other clients, with D3 having a later storage time than D5. Client S2's current search information matches node M, client S3's matches node S, and client S4's matches node Y. The historical search information of other clients D2 matches node Y, D3, and D5 matches node S. Following the order of child nodes, parent nodes, and sibling nodes, and from latest to earliest storage time, the matching results for client S2 are D3, D5, and D2; for client S3, D3, and D5; and for client S4, D2, D3, and D5.

[0071] As a preferred embodiment, obtaining the current search information input by the client includes:

[0072] Obtain the current search information selected by the client from the preset menu bar. The structure of the preset menu bar is consistent with the structure of the tree structure information chain or with the structure of any level in the tree structure information chain.

[0073] In this embodiment, considering that when the client searches autonomously, the current search information may not be accurate due to a lack of understanding of the relevant field, the client can be set to select the current search information through a preset menu bar. The structure of the preset menu bar is consistent with the structure of the tree structure information chain or with the structure of any level in the tree structure information chain. Each node in the tree structure information chain can be a node up to the current level or a node pointing to a child level. This application does not make any special limitations on this.

[0074] If the structure of the preset menu bar is consistent with the structure of the lowest node in the tree-structured information chain, the scope of secondary filtering can be effectively reduced, which helps to reduce uncertainty when users input information.

[0075] As a preferred embodiment, obtaining the current search information input by the client further includes:

[0076] Get the current custom search information input by the client;

[0077] Determine the first node in the pre-stored tree-structured information chain on the server that corresponds to the current search information, including:

[0078] Determine the first node in the tree-structured information chain that corresponds to the current search information and / or the current custom search information selected by the client from the preset menu bar.

[0079] In this embodiment, the user can either select the current search information from the preset menu bar or input custom search information through the search box. The process of obtaining the first node by combining the current search information selected from the preset menu bar and the custom search information input through the search box can be either an "AND" relationship for more accurate matching results or an "OR" relationship for a wider matching range.

[0080] To solve the above-mentioned technical problems, the present invention also provides an Internet recommendation system, comprising:

[0081] The search information acquisition unit is used to acquire search information input by the client.

[0082] The first node determination unit is used to determine the first node corresponding to the search information in the tree structure information chain pre-stored in the server.

[0083] The matching unit is used to match the first node with each second node corresponding to the historical search and stored information of other clients stored in the server according to the preset matching rules and to obtain the matching result;

[0084] The sending unit is used to send the matching results to the client.

[0085] For a detailed description of the Internet recommendation system provided by this invention, please refer to the embodiments of the Internet recommendation method described above, which will not be repeated here.

[0086] To solve the above-mentioned technical problems, the present invention also provides an Internet recommendation device, comprising:

[0087] Memory, used to store computer programs;

[0088] A processor is used to implement the steps of the above-described Internet recommendation method when executing a computer program.

[0089] For a detailed description of the Internet recommendation device provided by this invention, please refer to the embodiments of the Internet recommendation method described above, which will not be repeated here.

[0090] To address the aforementioned technical problems, the present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned Internet recommendation method.

[0091] For a detailed description of the computer-readable storage medium provided by this invention, please refer to the embodiments of the methods recommended on the Internet mentioned above, which will not be repeated here.

[0092] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0093] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An internet recommendation method, characterized in that, Applied to the server side, the Internet recommendation method includes: Get the current search information entered by the client; The first node corresponding to the current search information is determined in the tree structure information chain pre-stored in the server. The tree structure information chain includes multiple nodes in a tree structure and node information corresponding to each node. Based on the tree-structured information chain, the distances between the first node and each of the second nodes are obtained respectively; Arrange the distances sequentially from nearest to farthest to obtain the first distance sequence; Based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the second node sequence is obtained; The matching result is obtained based on the correspondence between the second node sequence and historical search and stored information; The matching result is sent to the client; Wherein, when there is a node in the second node that is the same as the first node, the other clients corresponding to the second node that is the same as the first node are the other clients with the highest priority for matching; Where multiple second nodes are at the same distance from the first node, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes: Based on the tree structure information chain, the relationship between each second node that is equidistant from the first node and the first node is determined. The relationship between the second node and the first node includes the second node being a child node of the first node, the second node being a sibling node of the first node, and the second node being a parent node of the first node. Arrange the second nodes in the second node sequence that are equidistant from the first node in the following order: the second node is a child node of the first node, the second node is a parent node of the first node, and the second node is a sibling node of the first node.

2. The internet recommendation method as described in claim 1, characterized in that, When multiple identical distances exist in the first distance sequence, after obtaining the second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each second node, the method further includes: Based on the storage time of each second node, the second nodes in the second node sequence that are equidistant from the first node are arranged in order from latest to earliest storage time.

3. The internet recommendation method as described in claim 1, characterized in that, Retrieve the current search information input by the client, including: Obtain the current search information selected by the client from the preset menu bar, wherein the structure of the preset menu bar is consistent with the structure of the tree structure information chain or with the structure of any level in the tree structure information chain.

4. The internet recommendation method as described in claim 3, characterized in that, Retrieving the current search information input by the client also includes: Obtain the current custom search information input by the client; Determining the first node in the tree-structured information chain pre-stored on the server that corresponds to the current search information includes: Determine the first node in the tree-structured information chain that corresponds to the current search information and / or the current custom search information selected by the client from the preset menu bar.

5. An internet recommendation system, characterized in that, include: The search information acquisition unit is used to acquire search information input by the client. The first node determination unit is used to determine the first node in the tree structure information chain pre-stored in the server that corresponds to the search information; A matching unit is configured to obtain the distances between the first node and each of the second nodes based on the tree structure information chain; arrange the distances sequentially according to a rule from near to far to obtain a first distance sequence; obtain a second node sequence based on the first distance sequence and the correspondence between each distance in the first distance sequence and each of the second nodes; and obtain a matching result based on the correspondence between the second node sequence and historical search and storage information; wherein, when there is a node in the second node that is the same as the first node, other clients corresponding to the second nodes that are the same as the first node are selected as the other clients with the highest priority for matching; wherein, when there are multiple second nodes with the same distance to the first node, the distances are further matched based on the first distance sequence. After obtaining the second node sequence based on the correspondence between each distance in the first distance sequence and each second node, the method further includes: determining the relationship between each second node with the same distance as the first node and the first node based on the tree structure information chain, wherein the relationship between the second node and the first node includes the second node being a child node of the first node, the second node being a sibling node of the first node, and the second node being a parent node of the first node; arranging the second nodes with the same distance as the first node in the second node sequence in the order of the second node being a child node of the first node, the second node being a parent node of the first node, and the second node being a sibling node of the first node; A sending unit is used to send the matching result to the client.

6. An internet recommendation device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the Internet recommendation method as described in any one of claims 1 to 4 when executing the computer program.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the Internet recommendation method as described in any one of claims 1 to 4.

Images