Intelligent information recommendation method and device based on big data analysis

Abstract

The present invention discloses an intelligent information recommendation method and device based on big data analysis, and relates to the technical field of intelligent information recommendation methods; in order to improve the push effect during active retrieval; the method is implemented based on an intelligent information recommendation system, and the system includes: an information receiving module, which is used to receive information transmitted by users, including search information and upload information; an information extraction module, which is used to extract information transmitted by users; the device is a server protection device of the above-mentioned intelligent information recommendation system, and the device includes: a fixed component, which is used to be fixed on both sides of the device; a folding belt, and the two ends of the folding belt are fixed between the two fixed components. The method of the present invention can extract and classify corresponding keywords according to the information transmitted by the user, generate user portraits, and continuously improve them to achieve intelligent information push, with good push effect, and the information in the user portrait is timely, which further guarantees the push effect.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent information recommendation methods, and in particular to an intelligent information recommendation method and device based on big data analysis. Background Art

[0002] The so-called information push is a new technology that uses certain technical standards or protocols to regularly transmit information that users need on the Internet. Push technology reduces the time spent on searching on the Internet by transmitting information to users. It searches and filters information based on user interests and pushes it to users regularly to help users discover valuable information efficiently. Although information push can actively provide users with information that they may need, it cannot display information more accurately when users actively search. Therefore, it still needs to be improved.

[0003] After searching, the Chinese patent application number CN201611004298.9 discloses an information push method and information push platform; the method includes: the terminal information collection system obtains the terminal identification information of the mobile terminal user and sends it to the information processing system; the information push configuration system generates the information to be pushed and the information push area according to the merchant information submitted by the merchant user, and sends the information to be pushed and the information push area to the information processing system; the information processing system determines the current geographical location of the mobile terminal user according to the received terminal identification information, and pushes the information to be pushed to the mobile terminal user when the current geographical location belongs to the information push area. The information push method in the above patent has the following shortcomings: although active information push is realized, it cannot display information more accurately according to the user's personal preferences and characteristics when the user actively searches. Summary of the invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent information recommendation method and device based on big data analysis.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent information recommendation method based on big data analysis is implemented based on an intelligent information recommendation system, the system comprising:

[0007] An information receiving module is used to receive information transmitted by users, including search information and upload information;

[0008] An information extraction module, used to extract information transmitted by users;

[0009] The user portrait generation module generates and updates user portraits based on the user's search information;

[0010] Information completion module: The information completion module completes the extracted search information based on the user portrait;

[0011] An information retrieval module performs information retrieval based on the completed information;

[0012] A classification module is used to classify information according to the information extracted by the extraction module;

[0013] Repository module, used to store users' uploaded information.

[0014] Preferably, the intelligent information recommendation method comprises the following steps:

[0015] S1: The user submits search information;

[0016] S2: The information receiving module receives the information;

[0017] S3: The information extraction module extracts keywords from the received information;

[0018] S4: The information completion module completes the extracted search information based on the user portrait;

[0019] S5: The information retrieval module performs information retrieval based on the completed information;

[0020] S6: Push the search results to the user end.

[0021] Further: when the user portrait has not been formed, the information completion step of the information completion module is skipped, and the information retrieval module directly performs retrieval based on keywords.

[0022] Further preferably, the method for generating the user portrait comprises the following steps:

[0023] S11: The user terminal submits search information or uploads information;

[0024] S12: The information receiving module receives the information;

[0025] S13: The information extraction module extracts keywords from the received information;

[0026] S14: The category classification module classifies the information according to the extracted keywords, and stores the classified information in the storage module; at the same time, a category tag is given to the user end;

[0027] S15: When the number of tags of the same category on the user side is greater than 5, a user portrait is generated, and the keywords corresponding to the category are written into the user portrait.

[0028] As a preferred embodiment of the present invention: the content in the user portrait is updated in real time, and whenever the number of a category mark is greater than 5, the keywords corresponding to the category are written into the user portrait, and the content in the user portrait is valid for 7 to 14 days;

[0029] In the process of completing the extracted search information based on the user portrait, the information completion module selects keywords similar to the search information for completion.

[0030] Further: when transmitting information, the user terminal also uploads user ID information, which includes user identity information, user portrait information and category tag information; let the user identity information be Dx, the user portrait information be H, and the category tag information be respectively as follows:

[0031] AN1, where N1 is the number of A-category tags (i.e. A1, A2, ... AN);

[0032] BN2, where N2 is the number of B category tags (i.e. B1, B2…B5);

[0033] …

[0034] MN a , at this time N a is the number of M category labels (i.e., M1, M2, …, M5);

[0035] When N a >5, mark the corresponding category as MN a Included in user profile information X;

[0036] At this time, the ID information uploaded by the user is: DxH(MN a ), (N a >5);

[0037] When recommending information, the information retrieval module is based on DxH (MN a ) a Recommend information to the corresponding Dx user terminal.

[0038] A device for an intelligent information recommendation method based on big data analysis, the device is a server protection device of the above-mentioned intelligent information recommendation system, and the device comprises:

[0039] A fixing component, which is used to be fixed on both sides of the device;

[0040] A corrugated belt, with both ends of the corrugated belt fixed between two fixed components;

[0041] Wherein, the fixing component comprises:

[0042] A fixing plate, wherein an outer wall of one side of the fixing plate is provided with a mounting groove;

[0043] The suction cup is detachably installed in the installation groove.

[0044] As a further solution of the present invention: a fixing cylinder is provided on the outer wall of one side of the fixing plate, a through hole is opened on the corrugated belt, an elastic rope is passed through the through hole, and both ends of the elastic rope pass through the through holes of the corrugated belt and are installed in the fixing cylinders of the two fixing plates; a top screw for fixing the elastic rope is connected to the inner wall of one side of the fixing cylinder through a thread.

[0045] Based on the above scheme: a plug hole is opened on the top outer wall of the fixing plate, and a plug rod is detachably installed on the bottom outer wall of the fixing plate through threads; one fixing plate is detachably installed in the plug hole of another fixing plate through the plug rod.

[0046] Based on the above scheme, preferably: a fixing frame is fixed to an outer wall of one side of the fixing plate, a threaded seat is arranged on the fixing frame, a fixing knob is threadedly connected inside the threaded seat, and a fixing disk is fixed to one end of the fixing knob.

[0047] The beneficial effects of the present invention are:

[0048] 1. The method of the present invention can extract and classify corresponding keywords according to the information transmitted by the user, generate a user portrait, and continuously improve it to achieve intelligent information push with good push effect. The information in the user portrait is timely, which further guarantees the push effect.

[0049] 2. The device of the present invention can install two fixing components on both sides of the equipment, so as to effectively protect the equipment with the corrugated belt; in addition, the corrugated belt can better adapt to equipment of different sizes, thereby improving the flexibility of use.

[0050] 3. The device of the present invention can utilize elastic ropes to reliably support the folding belts, thereby improving the protective effect. The tightness and effective length of the elastic ropes can be adjusted according to actual conditions, thereby improving the flexibility of use. In addition, multiple fixed plates and folding belts can be spliced ​​and used, thereby increasing the protective area and ensuring the protective effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a schematic diagram of the structure of a device for an intelligent information recommendation method based on big data analysis proposed by the present invention;

[0052] Figure 2 A schematic diagram of the structure of a portion of a device for an intelligent information recommendation method based on big data analysis proposed by the present invention;

[0053] Figure 3 This is a schematic diagram of the structure of fixed components in a device of an intelligent information recommendation method based on big data analysis proposed by the present invention;

[0054] Figure 4 This is a structural schematic diagram of the splitting of fixed components in a device of an intelligent information recommendation method based on big data analysis proposed by the present invention;

[0055] Figure 5 A flowchart of an intelligent information recommendation method in an intelligent information recommendation method based on big data analysis proposed by the present invention;

[0056] Figure 6 The present invention is a flowchart of a method for generating user portraits in an intelligent information recommendation method based on big data analysis.

[0057] In the figure: 1 fixing plate, 2 fixing knob, 3 elastic rope, 4 folding belt, 5 fixing tube, 6 insertion hole, 7 fixing frame, 8 top screw, 9 suction cup, 10 installation groove, 11 insertion rod, 12 fixing plate, 13 threaded seat. DETAILED DESCRIPTION

[0058] The technical solution of this patent is further described in detail below in conjunction with specific implementation methods.

[0059] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0060] In the description of this patent, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this patent and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this patent.

[0061] In the description of this patent, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", and "set" should be understood in a broad sense, for example, it can be fixedly connected or set, or it can be detachably connected or set, or connected or set in one piece. For ordinary technicians in this field, the specific meanings of the above terms in this patent can be understood according to specific circumstances.

[0062] Embodiment 1:

[0063] An intelligent information recommendation method based on big data analysis is implemented based on an intelligent information recommendation system, the system comprising:

[0064] An information receiving module is used to receive information transmitted by users, including search information and upload information;

[0065] An information extraction module, used to extract information transmitted by users;

[0066] The user portrait generation module generates and updates user portraits based on the user's search information;

[0067] Information completion module: The information completion module completes the extracted search information based on the user portrait;

[0068] An information retrieval module performs information retrieval based on the completed information;

[0069] A classification module is used to classify information according to the information extracted by the extraction module;

[0070] Repository module, used to store users' uploaded information.

[0071] In order to better recommend information, the intelligent information recommendation method includes the following steps:

[0072] S1: The user submits search information;

[0073] S2: The information receiving module receives the information;

[0074] S3: The information extraction module extracts keywords from the received information;

[0075] S4: The information completion module completes the extracted search information based on the user portrait;

[0076] S5: The information retrieval module performs information retrieval based on the completed information;

[0077] S6: Push the search results to the user end.

[0078] Among them, when the user portrait has not been formed, the information completion step of the information completion module is skipped, and the information retrieval module directly searches according to keywords.

[0079] The method for generating the user portrait comprises the following steps:

[0080] S11: The user terminal submits search information or uploads information;

[0081] S12: The information receiving module receives the information;

[0082] S13: The information extraction module extracts keywords from the received information;

[0083] S14: The category classification module classifies the information according to the extracted keywords, and stores the classified information in the storage module; at the same time, a category tag is given to the user end;

[0084] S15: When the number of tags of the same category on the user side is greater than 5, a user portrait is generated, and the keywords corresponding to the category are written into the user portrait.

[0085] The content in the user portrait is updated in real time. Whenever the number of category tags is greater than 5, the keywords corresponding to the category are written into the user portrait, and the content in the user portrait is valid for 7 to 14 days.

[0086] In the process of completing the extracted search information based on the user portrait, the information completion module selects keywords similar to the search information for completion;

[0087] Specifically, in order to better recommend information, the user terminal uploads user ID information when transmitting information. The user ID information includes user identity information, user portrait information and category tag information. Let the user identity information be Dx, the user portrait information be H, and the category tag information be respectively as follows:

[0088] AN1, where N1 is the number of A-category tags (i.e. A1, A2, ... AN);

[0089] BN2, where N2 is the number of B category tags (i.e. B1, B2…B5);

[0090] …

[0091] MN a , at this time N a is the number of M category labels (i.e., M1, M2, …, M5);

[0092] When N a >5, mark the corresponding category as MN a Included in user profile information X;

[0093] At this time, the ID information uploaded by the user is: DxH(MN a ), (N a >5);

[0094] When recommending information, the information retrieval module is based on DxH (MN a ) a Recommend information to the corresponding Dx user terminal.

[0095] Embodiment 2:

[0096] A device for intelligent information recommendation method based on big data analysis, such as Figure 1-4As shown, in order to facilitate the protection of the device, the device is a server protection device of the above-mentioned intelligent information recommendation system, and the device includes:

[0097] A fixing component, which is used to be fixed on both sides of the device;

[0098] A corrugated belt 4, both ends of which are bonded between two fixed components;

[0099] Wherein, the fixing component comprises:

[0100] A fixing plate 1, wherein an outer wall of one side of the fixing plate 1 is provided with a mounting groove 10;

[0101] A suction cup 9, which is detachably mounted in the mounting groove 10;

[0102] By providing a fixing component and a folding belt 4, the two fixing components can be installed on both sides of the device, so that the folding belt 4 can be used to effectively protect the device; in addition, the folding belt 4 can better adapt to devices of different sizes, thereby improving the flexibility of use.

[0103] A fixing cylinder 5 is integrally provided on the outer wall of one side of the fixing plate 1, and a through hole is provided on the folding belt 4, and an elastic cord 3 is passed through the through hole. Both ends of the elastic cord 3 pass through the through holes of the folding belt 4 and are installed in the fixing cylinders 5 of the two fixing plates 1; a top screw 8 for fixing the elastic cord 3 is connected to the inner wall of one side of the fixing cylinder 5 by a thread;

[0104] By providing structures such as the fixing tube 5 and the elastic rope 3, the elastic rope 3 can be used to reliably support the folding belt 4, thereby improving the protective effect. In addition, the tightness and effective length of the elastic rope 3 can be adjusted according to actual conditions, thereby improving the flexibility of use.

[0105] The top outer wall of the fixing plate 1 is provided with an insertion hole 6, and the bottom outer wall of the fixing plate 1 is detachably mounted with an insertion rod 11 through a thread; one fixing plate 1 is detachably mounted in the insertion hole 6 of another fixing plate 1 through the insertion rod 11;

[0106] By providing the insertion holes 6 and the insertion rods 11, a plurality of fixing plates 1 and folding belts 4 can be spliced ​​and used, thereby increasing the protection area and ensuring the protection effect.

[0107] In order to facilitate installation and fixing in different ways; a fixing frame 7 is fixed to the outer wall of one side of the fixing plate 1 by screws, and a threaded seat 13 is integrally provided on the fixing frame 7, and a fixing knob 2 is connected to the threaded seat 13 by threads, and a fixing plate 12 is fixed to one end of the fixing knob 2 by screws;

[0108] By providing the fixing knob 2 and the fixing disk 12, the fixing knob 2 can be turned to bring the fixing disk 12 closer to the fixing plate 1, and the fixing disk 12 and the fixing plate 1 can be used to achieve a clamping and fixing effect, thereby meeting the use requirements in different situations.

[0109] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent information recommendation method based on big data analysis, characterized in that: It is implemented based on an intelligent information recommendation system, and the system includes: An information receiving module is used to receive information transmitted by users, including search information and upload information; An information extraction module, used to extract information transmitted by users; The user portrait generation module generates and updates user portraits based on the user's search information; Information completion module: The information completion module completes the extracted search information based on the user portrait; An information retrieval module performs information retrieval based on the completed information; A classification module is used to classify information according to the information extracted by the extraction module; Repository module, used to store users' uploaded information; The server protection device of the intelligent information recommendation system includes: A fixing component, which is used to be fixed on both sides of the device; A folding belt (4), with both ends of the folding belt (4) being fixed between two fixing components; Wherein, the fixing component comprises: A fixing plate (1), wherein an outer wall of one side of the fixing plate (1) is provided with a mounting groove (10); A suction cup (9), the suction cup (9) being detachably mounted in the mounting groove (10); A fixing cylinder (5) is arranged on the outer wall of one side of the fixing plate (1); a through hole is opened on the folding belt (4), and an elastic rope (3) is inserted into the through hole; both ends of the elastic rope (3) pass through the through holes of the folding belt (4) and are installed in the fixing cylinders (5) of the two fixing plates (1); a top screw (8) for fixing the elastic rope (3) is connected to the inner wall of one side of the fixing cylinder (5) through a thread; The top outer wall of the fixing plate (1) is provided with an insertion hole (6), and the bottom outer wall of the fixing plate (1) is detachably mounted with an insertion rod (11) via a thread; one fixing plate (1) is detachably mounted in the insertion hole (6) of another fixing plate (1) via the insertion rod (11); A fixing frame (7) is fixed to an outer wall of one side of the fixing plate (1), a threaded seat (13) is provided on the fixing frame (7), a fixing knob (2) is connected to the threaded seat (13) via threads, and a fixing plate (12) is fixed to one end of the fixing knob (2).

2. The intelligent information recommendation method based on big data analysis according to claim 1 is characterized in that: The intelligent information recommendation method comprises the following steps: S1: The user submits search information; S2: The information receiving module receives the information; S3: The information extraction module extracts keywords from the received information; S4: The information completion module completes the extracted search information based on the user portrait; S5: The information retrieval module performs information retrieval based on the completed information; S6: Push the search results to the user end.

3. The intelligent information recommendation method based on big data analysis according to claim 2 is characterized in that: When the user portrait has not been formed, the information completion step of the information completion module is skipped, and the information retrieval module directly performs retrieval based on keywords.

4. The intelligent information recommendation method based on big data analysis according to claim 2 is characterized in that: The method for generating the user portrait comprises the following steps: S11: The user terminal submits search information or uploads information; S12: The information receiving module receives the information; S13: The information extraction module extracts keywords from the received information; S14: The category classification module classifies the information according to the extracted keywords, and stores the classified information in the storage module; at the same time, a category tag is given to the user end; S15: When the number of tags of the same category on the user side is greater than 5, a user portrait is generated, and the keywords corresponding to the category are written into the user portrait.

5. The intelligent information recommendation method based on big data analysis according to claim 4 is characterized in that: The content in the user portrait is updated in real time. Whenever the number of category tags is greater than 5, the keywords corresponding to the category are written into the user portrait, and the content in the user portrait is valid for 7 to 14 days; In the process of completing the extracted search information based on the user portrait, the information completion module selects keywords similar to the search information for completion.

6. The intelligent information recommendation method based on big data analysis according to claim 5, characterized in that: When transmitting information, the user terminal also uploads user ID information, which includes user identity information, user portrait information and category tag information; let the user identity information be Dx, the user portrait information be H, and the category tag information be respectively as follows: AN1, where N1 is the number of A-category tags, i.e. A1, A2, ... AN; BN2, where N2 is the number of B category tags, i.e. B1, B2…B5; …… MN a , at this time N a is the number of M category labels, i.e., M1, M2, ..., M5; When N a >5, mark the corresponding category as MN a Included in user profile information X; The ID information uploaded by the user at this time is: DxH-MN a , N a >5; When recommending information, the information retrieval module is based on DxH-MN a MN a Recommend information to the corresponding Dx user terminal.

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