Searching method and device, computer device and storage medium

Abstract

The application provides a retrieval method and device, computer equipment and a storage medium, which can simultaneously consider the breadth and accuracy of patent document retrieval. The method comprises the following steps: receiving a search operation instruction input by a user, the search operation instruction being associated with attention data; determining a first patent data set according to the search operation instruction; performing retrieval grouping on the first patent data set according to a template file to obtain a plurality of tree data structure subgroups, the tree data structure subgroup comprising one or more tree data structure nodes, the template file being a tree data structure retrieval grouping file, each of the plurality of tree data structure subgroups corresponding to a group of tree data structure retrieval formulas in the template file; determining a patent data set corresponding to the tree data structure subgroup, the patent data set being a data set arranged according to a list data structure; and performing semantic analysis on the patent data set to obtain a plurality of semantic groups.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of retrieval, and particularly relates to a retrieval method and device, a computer device and a storage medium.

BACKGROUND

[0002] In order to make enterprises clear about the dynamics of world patents and avoid repeated development and waste of funds, due to the large number of patents in the world and the priority feature, no one can guarantee that their ideas are unique in the world, so any individual or enterprise should carefully search before applying for a patent - whether their ideas have been realized by others, whether the patent has appeared in the databases of major patent offices around the world without knowing it.

[0003] Current retrieval is mainly divided into field retrieval and IPC classification retrieval. Field retrieval is provided with several retrieval fields by the system, and the user can select from several retrieval entries according to known conditions, and can perform single field retrieval or multi-field limited retrieval. Each retrieval field can be fuzzy searched with % (must use half-angle format), representing an arbitrary letter, number or word; multiple fuzzy characters can be used, and can be input at any position of the search string, and the first position can be omitted. IPC classification navigation retrieval is to query the interested class by using each part, major class and minor class in the IPC classification table, and click the class name to get the patent retrieval result under the class.

[0004] However, the current retrieval method is only suitable for simple retrieval and cannot be applied to large quantities of retrieval grouping.

SUMMARY

[0005] The present application provides a retrieval method, device and storage medium, which can not only perform large quantities of patent document retrieval, but also consider the breadth and accuracy of patent retrieval when retrieving patent documents.

[0006] The first aspect of the present application provides a retrieval method, comprising:

[0007] receiving a search operation instruction input by a user, the search operation instruction being associated with attention data;

[0008] determining a first patent data set corresponding to the attention data according to the search operation instruction;

[0009] grouping the first patent data set according to a template file to obtain a plurality of tree data structure subgroups, wherein the tree data structure subgroup comprises one or more tree data structure nodes, the template file is a tree data structure grouping file, and each tree data structure subgroup in the plurality of tree data structure subgroups corresponds to a group of tree data structure retrieval formulas in the template file;

[0010] determining a patent data set corresponding to the tree data structure sub-group, the patent data set being a data set arranged in a list data structure;

[0011] performing semantic analysis on the patent data set to obtain a plurality of semantic groups.

[0012] The second aspect of the present application provides a retrieval device, comprising:

[0013] a receiving unit configured to receive a search operation instruction input by a user, the search operation instruction being associated with attention data;

[0014] a first determining unit configured to determine, according to the search operation instruction, a first patent data set corresponding to the attention data;

[0015] a retrieval grouping unit configured to perform retrieval grouping on the first patent data set according to a template file to obtain a plurality of tree data structure sub-groups, wherein the tree data structure sub-group comprises one or more tree data structure nodes, the template file is a tree data structure retrieval grouping file, and each of the plurality of tree data structure sub-groups corresponds to a group of tree data structure retrieval formulas in the template file;

[0016] a second determining unit configured to determine a patent data set corresponding to the tree data structure sub-group, the patent data set being a data set arranged in a list data structure;

[0017] a semantic grouping unit configured to perform semantic analysis on the patent data set to obtain a plurality of semantic groups.

[0018] The third aspect of the embodiments of the present application provides a computer device comprising at least one connected processor, a memory and a transceiver, wherein the memory is configured to store program code, and the processor is configured to invoke the program code in the memory to execute the steps of the retrieval method of the first aspect described above.

[0019] The fourth aspect of the embodiments of the present application provides a computer storage medium comprising instructions, which, when executed on a computer, cause the computer to perform the steps of the retrieval method of any of the aspects described above.

[0020] Compared with the related art, in the embodiment provided in the present application, the retrieval device can first acquire the first patent data set retrieved by the user according to the search instruction of the user, then perform retrieval grouping on the first patent data through the template file constructed in advance to obtain a plurality of subgroups, and then perform semantic grouping on the patent data sets corresponding to the plurality of subgroups to obtain a plurality of semantic groups. In this way, not only can a large amount of patent literature retrieval be performed, but also the breadth and precision of patent retrieval can be taken into account at the same time when the patent literature is retrieved. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1 A flowchart of a retrieval method provided in the embodiment of the present application is shown in the figure.

[0022] Figure 2 An interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0023] Figure 3A Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0024] Figure 3B Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0025] Figure 4 Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0026] Figure 5A Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0027] Figure 5B Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0028] Figure 6 Another interface diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0029] Figure 7 A virtual structure diagram of the retrieval device provided in the embodiment of the present application is shown in the figure.

[0030] Figure 8 A hardware structure diagram of the server provided in the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application.

[0032] The retrieval method is described below from the perspective of a retrieval device, which can be a server or a service unit in a server, without limitation.

[0033] Please refer to Figure 1 , Figure 1 The flowchart of the retrieval method provided in the embodiment of the application includes:

[0034] 101. Receive a search operation instruction input by a user.

[0035] In the embodiment, the retrieval device can receive a search operation instruction input by a user, which is associated with the concerned data. The search operation instruction can exist in the form of a retrieval formula or in the form of a file, for example, a txt file containing the content or a list of patent numbers that the user wants to retrieve.

[0036] It should be noted that the retrieval method will be described in detail below in combination with Figure 2 .

[0037] Please refer to Figure 2 , Figure 2 A schematic diagram of the retrieval interface provided in the embodiment of the application includes a toolbar 201, a database selection bar 202, a retrieval window 203, and a retrieval result presentation window 204. The retrieval device can receive a search operation instruction input by a user in the retrieval window 203, which is associated with the concerned data set. That is, the user wants to search for patents in which aspects, that is, the search operation instruction can be input in the retrieval window 203. For example, the search operation instruction can be “B / (automatic driving OR unmanned driving OR intelligent driving OR autonomous driving OR unmanned driving OR unmanned vehicle OR unmanned vehicle) AND DB / cnapp”. The search operation instruction can also be “B / (automatic driving or unmanned driving or intelligent driving)”. Of course, other search instructions can also be used, for example, “ann / baidu and db / cnapp”, without limitation.

[0038] 102. Determine a first patent data set corresponding to the concerned data according to the search operation instruction.

[0039] In the embodiment, after receiving the search operation instruction input by the user, the retrieval device can determine a first patent data set corresponding to the concerned data according to the search operation instruction, as shown in Figure 2 After receiving the search operation instruction input by the user, the corresponding database can be selected in the database selection bar 202. Then, the patent data corresponding to the concerned data can be searched from the selected database, and a first patent data set is obtained, which is displayed in the retrieval result presentation window 204, as shown inFigure 2 As shown, the first patent data set contains 149980 results, i.e. 149980 patent data.

[0040] In an embodiment, the operation of generating the search operation instruction at least includes one of a gesture operation, a sliding operation, a clicking operation and a voice control operation. For example, when the user performs a clicking operation on the selection box, the retrieval device can receive the clicking operation. At this time, the clicking operation generates the search operation instruction. That is, the search operation instruction can be defined in advance. For example, the sliding operation is defined in advance as a trigger operation for determining the first patent data set corresponding to the focus data (such as left sliding operation, right sliding operation, up sliding operation and down sliding operation, etc.). Or, the clicking operation is defined as a trigger operation for determining the first patent data set corresponding to the focus data (such as single-click operation or double-click operation, etc.). Or, the gesture operation is defined as a trigger operation for determining the first patent data set corresponding to the focus data (such as left wrist or arm swing, right wrist or arm swing, such as four-finger contraction operation or three-finger up sliding operation, etc.). Or, the voice control operation is defined as a trigger operation for determining the first patent data set corresponding to the focus data (such as receiving the entry of the patent data corresponding to the focus data and the specific search formula). The above is only an example for illustration and does not represent a limitation on the operation of generating the search operation instruction.

[0041] 103. Retrieving and grouping the first patent data set according to the template file to obtain a plurality of tree data structure subgroups.

[0042] In this embodiment, after determining the first patent data set, the retrieval device can import the first patent data set into a grouping interface and retrieve and group the first patent data set based on the template file in the grouping interface to obtain a plurality of tree data structure subgroups. Each tree data structure subgroup in the plurality of tree data structure subgroups corresponds to a group of tree data structure search formulas in the template file.

[0043] In one embodiment, the retrieval device receives template construction instructions of the user, and constructs a template file according to the template construction instructions, and stores the template file into a template database, wherein the template database stores a plurality of template files. That is, the retrieval device can construct a template file required by the user in advance according to the instructions of the user, and store the template file into the template database, so that when the user wants to use it, it can be directly extracted from the template database, in addition, it is also convenient for the database to be reused, that is, the plurality of template texts in the template database can be shared, modified, shared, copied, and of course some other operations can be performed, for example, the user can send the template file written according to his own construction instructions to other users for use. In order to facilitate understanding, the following will be explained with specific examples of template files:

[0044] The template file can be constructed as follows:

[0045] # autonomous driving

[0046] a / ((recognition or perception) and environment) # recognition technology

[0047] a / computer vision # computer vision

[0048] a / color and marking # color marker

[0049] a / camera # camera

[0050] a / (double head or binocular or double camera) # double head camera

[0051] a / (single head or monocular or single camera) # single head camera

[0052] a / (multiocular or multiocular stereo or multiocular stereo camera) # multiocular stereo camera

[0053] a / look around # look around camera

[0054] a / photograph # camera

[0055] a / (red light or green light) # traffic light

[0056] a / lanemarking # lane marking

[0057] a / object detection # object detection

[0058] a / object tracking # object tracking

[0059] a / scene segmentation # scene segmentation

[0060] a / millimeter wave radar # millimeter wave technology

[0061] a / laser radar # laser radar

[0062] a / 3D # 3D

[0063] a / overtake # overtake

[0064] a / lanes # lane

[0065] a / obstacle or avoid # obstacle avoidance

[0066] a / ultrasound or sonar # ultrasonic sensor

[0067] b / night or dark # night environment

[0068] a / tachometer # tachometer

[0069] a / IMU # inertial navigation

[0070] a / (accelerometer or Accelermeters) # accelerometer

[0071] a / (gyroscope or Gyroscope) # gyroscope

[0072] a / (magnetometer or Magnetometers) # magnetometer

[0073] a / (high-precision map or high-definition map or high-definition map or high-resolution map) # high-precision map

[0074] a / AI or artificial intelligence # artificial intelligence

[0075] a / (fatigue and (monitor or detect)) # fatigue monitoring

[0076] a / facial recognition # facial recognition

[0077] a / 3D # 3D sensing

[0078] a / positioning # positioning system

[0079] a / (satellite nwn positioning) # satellite positioning

[0080] a / GPS # GPS positioning system

[0081] a / GNSS # GNSS positioning system

[0082] a / Beidou # Beidou positioning system

[0083] a / (communication or communication) # communication technology

[0084] a / vehicle networking # vehicle networking

[0085] a / real-time interaction # real-time interaction

[0086] a / (v2x or v2v or v2r or v2i or v2p or v2m or v2t)#V2X

[0087] a / v2v#V2V

[0088] a / v2i#V2I

[0089] a / v2p#V2P

[0090] end-to-end #end-to-end

[0091] a / Cloud #Cloud to Car

[0092] a / (WebSocket or instant messaging)#Communication process

[0093] a / Path Planning#Path Planning

[0094] a / Vehicle and Dispatch#Vehicle Dispatch

[0095] a / (algorithm or program)#Path Algorithm

[0096] a / a*#A*Search

[0097] a / Shortest Path Planning#Shortest Path Planning

[0098] a / dijkstra#dijkstra algorithm

[0099] a / Secondary Programming#Secondary Programming

[0100] a / (Control or tracking control or execution control or drive-by-wire)#Control System

[0101] a / (wired or electronic control)#Wired control device

[0102] a / Drive-by-wire throttle#Drive-by-wire throttle

[0103] a / Drive-by-wire#Drive-by-wire

[0104] a / Steering-by-wire#Steering-by-wire

[0105] a / Steering wheel#Steering wheel

[0106] a / Attitude Control#Attitude Control

[0107] a / Position Control#Position Control

[0108] a / Lane Keeping#Lane Keeping

[0109] a / Auto Follow #Auto Follow

[0110] a / Curve driving #Curve driving

[0111] a / Planning Control # Planning Control

[0112] a / Execution Control # Execution Control

[0113] a / Redundancy Control # Redundancy Control

[0114] a / (Behavior Stability or Behavior Safety) # Behavior Stability

[0115] a / (Human Machine Interaction or User Interface or Human Machine Interface) # Human Machine Interaction Technology

[0116] a / (Touch or Touch Control) # Touch Screen

[0117] a / Virtual Reality # Virtual Reality

[0118] a / Enhanced Reality # Augmented Reality

[0119] a / (Driver Assistance or adas or l1) # L1 Driver Assistance

[0120] a / (Anti-lock or ABS) # Anti-lock Braking Technology

[0121] a / (Electronic Stability or ESC or Dynamic Stability) # Driving Stability

[0122] a / Lane Departure # Lane Departure

[0123] a / (Assisted Parking or Assist Parking) # Assist Parking

[0124] a / Collision Warning # Collision Warning

[0125] a / Tracing or Anti-slip # Anti-slip Control

[0126] a / Blind Spot # Blind Spot

[0127] a / (Partially Automated Driving or l2) # L2 Partially Automated Driving

[0128] a / (ACC or Cruise) # Cruise

[0129] a / Lane Departure # Lane Departure

[0130] a / (Automatic Parking or Auto Parking) # Auto Parking

[0131] a / LKA # LKA

[0132] a / (Conditional Automated Driving or l3) # L3 Conditional Automated Driving

[0133] a / Sensing # Sensing Technology

[0134] a / Road Condition # Road Condition

[0135] a / (Highly Autonomous Driving) or L4#L4 Highly Autonomous Driving

[0136] a / (Autonomous Steering)#Autonomous Steering

[0137] a / (Autonomous Parking or Autonomous Parking)#Autonomous Parking

[0138] a / (Fully autonomous driving) or L5#L5 fully autonomous driving

[0139] a / (Remote Nwn Driving)#Remote Automated Driving

[0140] a / Automation#Fully automated.

[0141] Here, `a / ` is a Boolean search command that searches within the title, abstract, and claims. `nwn` represents the appearance of two keywords in the same sentence. The search query and its description are separated by `#`. Each search query is preceded by a tab indicating a hierarchical structure within the tree-like structure.

[0142] The following is combined Figure 3A and Figure 3B Please refer to the following for explanations of the search groupings. Figure 3A and Figure 3B , Figure 3A and Figure 3B Here are two schematic diagrams of another interface of the retrieval device provided in this application:

[0143] The retrieval device imports a pre-built template file according to the user's instructions. Figure 3A Pop-up window 301 is the window for importing the template file. By triggering the "Call Template" control in pop-up window 301, the pre-built template file can be imported, and the first patent dataset can be searched and grouped according to the template file, resulting in multiple subgroups. Each subgroup corresponds to a set of stump search expressions in the template file, and each subgroup includes multiple patent documents. For example... Figure 3B As shown, the first patent dataset is divided into 12 subgroups using template files. Each subgroup contains several subgroups, and each subgroup can further include nodes or patent documents depending on the template file, such as... Figure 3B The "Identification Technology" subgroup includes multiple groups such as computer vision, color markers, cameras, and cameras. The "Camera" group includes multiple nodes such as dual-head cameras, single-head cameras, multi-view cameras, and surround-view cameras. Each node includes several patent documents. The "Camera" group directly divides into several patent documents. Thus, the first patent dataset can be converted into a tree-structured grouping based on the template file.

[0144] It should be noted that each of the plurality of subgroups corresponds to a group of tree search expressions in the template file, for example, the "recognition technology" subgroup corresponds to "a / ((recognition or perception) and environment) #recognition technology" in the template file.

[0145] a / computer vision #computer vision

[0146] a / color and marker #color marker

[0147] a / camera #camera

[0148] a / (double or binocular or dual camera) #dual camera

[0149] a / (single or monocular or single camera) #single camera

[0150] a / (multi or multi stereo or multi stereo camera) #multi stereo camera

[0151] a / look around #look around camera

[0152] a / photograph #camera

[0153] a / (red light or green light) #red light

[0154] a / lane line #lane line

[0155] a / object detection #object detection

[0156] a / object tracking #object tracking

[0157] a / scene segmentation #scene segmentation

[0158] a / millimeter wave radar #millimeter wave technology

[0159] a / laser radar #laser radar

[0160] a / 3D #3D

[0161] a / overtaking #overtaking

[0162] a / laneshift #lane shift

[0163] a / barrier or obstacle avoidance #obstacle avoidance

[0164] a / ultrasonic or sonar #ultrasonic sensor

[0165] b / night or night #night environment

[0166] a / wheel speed meter #wheel speed meter

[0167] a / IMU #inertial navigation

[0168] a / (accelerometer or Accelermeters) #accelerometer

[0169] a / (gyroscope or Gyroscope) #gyroscope

[0170] a / (magnetometer or Magnetometers) #magnetometer

[0171] a / (high-precision map or high-definition map or high-definition map or high-resolution map) #high-precision map tree search formula.

[0172] It should be noted that the above tree search formula is only for illustration, and other search formulas can also be constructed, and the specific implementation is not limited.

[0173] 104, determine the patent data set corresponding to the tree data structure sub-grouping.

[0174] In this embodiment, after the retrieval device groups the first patent data set to obtain a plurality of tree data structure sub-groupings, it can determine the patent data set corresponding to the plurality of tree data structure sub-groupings. Specifically, recursively traverse each tree data structure node in the plurality of tree data structure sub-groupings to obtain a tree data structure search result set corresponding to the plurality of tree data structure sub-groupings; and perform an association operation on the tree data structure search result set, wherein the association operation is used to convert the tree data structure search result set into a list data structure data set. That is, the retrieval device can extract all patent literature sets included in each tree data structure node in the plurality of tree data structure sub-groupings, and integrate them into a list data structure patent data set.

[0175] In one embodiment, the retrieval device can also receive user adjustment operation instructions, and adjust the template file according to the adjustment operation instructions, and group the first patent data set according to the adjusted template file to obtain a plurality of sub-groupings corresponding to the adjusted template file.

[0176] 105, perform semantic analysis on the patent data set to obtain a plurality of semantic groupings.

[0177] In this embodiment, the retrieval device can perform semantic analysis on the patent data set to obtain a plurality of semantic groupings.

[0178] The following will be combined Figure 4 The association operation of the tree search result set and the semantic analysis will be described below. Please refer to Figure 4 , Figure 4Another interface diagram of the retrieval device provided in the application is shown in FIG. 4, wherein 401 is a plurality of semantic groups obtained after semantic analysis, and each semantic group includes a plurality of patent documents, for example, the plurality of patent document data included in the semantic group of "trajectory tracking, navigation algorithm, lidar data and global path". Thus, a plurality of semantic groups corresponding to the first patent data set can be obtained.

[0179] In one embodiment, the retrieval device can further filter the patent data set, specifically as follows:

[0180] receiving a second filtering operation instruction of the user;

[0181] filtering the target semantic group according to a target sub-group, wherein the target sub-group is any one of the plurality of tree-shaped data structure sub-groups, the target semantic group is any one of the plurality of semantic groups, and N is an integer greater than or equal to 1.

[0182] In this embodiment, the retrieval device can further receive a second filtering operation instruction of the user, and filter the target semantic group according to a second target sub-group, wherein the second target sub-group is any one of the plurality of sub-groups, the target semantic group is any one of the plurality of semantic groups, and N is an integer greater than or equal to 1. That is, the retrieval device can filter each group in the semantic group according to the patent documents in the sub-group through the instruction of the user, so as to further filter the patents. The following will be described in combination with Figure 5A and Figure 5B .

[0183] Please refer to Figure 5A and Figure 5B , Figure 5A and Figure 5B respectively as another interface diagram of the retrieval device provided in the application, wherein the "artificial intelligence" sub-group is taken as the second target sub-group 501, and the "matching algorithm | fusion method | fusion algorithm | point feature" is taken as the target semantic group 502. Then, all the patent documents in the target semantic group 502 "matching algorithm | fusion method | fusion algorithm | point feature" are filtered by the second target sub-group 501 "artificial intelligence", so as to obtain the patent documents meeting both the first target sub-group 501 and the target semantic group 502, and also obtain the group label meeting the target sub-group 501, such as the "3D sensing" group shown in 503. That is, Figure 5B the two patent documents under the "3D sensing" group shown in 503.

[0184] In one embodiment, the retrieval device can also perform individual semantic analysis on any one of the plurality of tree data structure subgroups, as follows:

[0185] Receive a first filtering operation instruction of the user;

[0186] Determine a first target subgroup according to the first filtering operation instruction, the first target subgroup being any one of the plurality of tree data structure subgroups;

[0187] Perform semantic analysis on the patent data set corresponding to the first target subgroup to obtain a plurality of first target semantic subgroups.

[0188] In this embodiment, the retrieval device can first select a first target subgroup from the plurality of tree structure subgroups according to the first filtering operation instruction of the user, and then perform semantic analysis on the patent documents in the first target subgroup to obtain a plurality of first target semantic groups, each first target semantic group including a number of patent documents. The following will be described in combination with Figure 6 :

[0189] Figure 6 Another interface diagram of the retrieval device provided in the present application is shown, wherein the retrieval device performs semantic analysis on the "artificial intelligence" subgroup as the first target subgroup 601 according to the first filtering operation instruction, and can further obtain a plurality of first target semantic subgroups corresponding to the first target subgroup 601, such as the "multi-band | vertical cavity surface emitting laser | laser array | photonic device", "fusion algorithm | particle filter | pose estimation | pose estimation", "unmanned vehicle | obstacle detection | radar detection | dynamic target", and "exploration route" four semantic subgroups shown in 602, each semantic subgroup including a number of patent documents.

[0190] It should be noted that the way of generating the template construction instruction, the adjustment operation instruction, and the filtering instruction is similar to the way of generating the search operation instruction, and the above has described in detail the way of generating the search operation instruction, which will not be described here.

[0191] As described above, in the embodiments provided in the present application, the retrieval device can first obtain a first patent data set retrieved by the user according to the search instruction of the user, and then perform retrieval grouping on the first patent data through the template file constructed in advance to obtain a plurality of subgroups, and then perform semantic grouping on the patent data sets corresponding to the plurality of subgroups to obtain a plurality of semantic groups. Thus, when retrieving patent documents, not only the breadth of the patent can be retrieved, but also the depth of the patent can be retrieved.

[0192] The above describes the present application from the perspective of the retrieval method, and the following describes the present application from the perspective of the retrieval device.

[0193] Please refer to Figure 7 , Figure 7 A virtual structure schematic diagram of a retrieval device provided by an embodiment of the present application is shown in FIG. 7. The retrieval device 700 includes:

[0194] A receiving unit 701 is configured to receive a search operation instruction input by a user, the search operation instruction being associated with attention data;

[0195] A first determining unit 702 is configured to determine, according to the search operation instruction, a first patent data set corresponding to the attention data;

[0196] A retrieval grouping unit 703 is configured to perform retrieval grouping on the first patent data set according to a template file to obtain a plurality of tree data structure subgroups, wherein the tree data structure subgroups include one or more tree data structure nodes, the template file is a tree data structure retrieval grouping file, and each of the plurality of tree data structure subgroups corresponds to a group of tree data structure retrieval formulas in the template file;

[0197] A second determining unit 704 is configured to determine a patent data set corresponding to the tree data structure subgroups, the patent data set being a data set arranged in a list data structure;

[0198] A semantic grouping unit 705 is configured to perform semantic analysis on the patent data set to obtain a plurality of semantic groups.

[0199] In a possible design, the second determining unit 704 is specifically configured to:

[0200] recursively traverse each tree data structure node in the plurality of tree data structure subgroups to obtain a tree data structure retrieval result set corresponding to the plurality of tree data structure subgroups;

[0201] perform an association operation on the tree data structure retrieval result set to obtain the patent data set, wherein the association operation is used to convert a data set in a tree data structure into a data set in a list data structure.

[0202] In a possible design,

[0203] The receiving unit 701 is further configured to receive a first filtering operation instruction of the user;

[0204] The second determining unit 704 is further configured to determine, according to the first filtering operation instruction, a first target sub-group, the first target sub-group being any one of the plurality of tree data structure subgroups;

[0205] The retrieval and grouping unit 703 is further configured to perform semantic analysis on the patent data set corresponding to the first target sub-grouping to obtain a plurality of first target semantic sub-groupings.

[0206] In a possible design,

[0207] The receiving unit 701 is further configured to receive a second filtering operation instruction of the user.

[0208] The retrieval and grouping unit 703 is further configured to filter the target semantic grouping according to a second target sub-grouping to obtain N patent data sets, the second target sub-grouping being any one of the plurality of tree data structure sub-groupings, and the target semantic grouping being any one of the plurality of semantic groupings, where N is an integer greater than or equal to 1.

[0209] In a possible design,

[0210] The receiving unit 701 is further configured to receive an adjustment operation instruction of the user.

[0211] The first determining unit 702 is configured to adjust the template file according to the adjustment operation instruction.

[0212] The retrieval and grouping unit 703 is further configured to perform retrieval and grouping on the first patent data set according to the adjusted template file to obtain a tree data structure sub-grouping corresponding to the adjusted template file.

[0213] In a possible design,

[0214] The receiving unit 701 is further configured to receive a template construction instruction of the user.

[0215] The first determining unit 702 is further configured to construct the template file according to the template construction instruction, and store the template file in a template database, the template database storing a plurality of template texts.

[0216] Figure 8 A structural diagram of a server of the present application is shown in FIG. 1. Figure 8As shown, the server 800 of the embodiment includes at least one processor 801, at least one network interface 804 or other user interface 803, a memory 805, and at least one communication bus 802. The server 800 can optionally contain a user interface 803, including a display, a keyboard or a pointing device. The memory 805 can contain a high-speed RAM memory, and can also include a non-volatile memory, such as at least one disk memory. The memory 805 stores execution instructions, and when the server 800 is running, the processor 801 communicates with the memory 805, and the processor 801 calls the instructions stored in the memory 805 to execute the above-mentioned retrieval method. The operating system 806 contains various programs for implementing various basic services and processing tasks according to hardware.

[0217] The server provided by the embodiments of the present application can execute the technical solutions of the above-mentioned embodiments of the retrieval method, and the implementation principles and technical effects are similar, which will not be described here.

[0218] The embodiments of the present application also provide a computer readable storage medium, which stores a computer program. When the computer program is executed by a computer, the method flow related to the retrieval device in any of the above-mentioned method embodiments is implemented. Correspondingly, the computer can be the above-mentioned retrieval device.

[0219] The embodiments of the present application also provide a computer program or a computer program product including a computer program. When the computer program is executed on a computer, the computer will implement the method flow related to the retrieval device in any of the above-mentioned method embodiments. Correspondingly, the computer can be the above-mentioned retrieval device.

[0220] In the above Figure 1 In the embodiments shown, all or part can be realized by software, hardware, firmware or any combination thereof. When realized by software, all or part can be realized in the form of a computer program product.

[0221] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center through wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) mode. The computer readable storage medium can be any available medium that the computer can store or be integrated into a data storage device such as a server, data center, etc. containing one or more available media sets. The available media can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)) and the like.

[0222] It should be understood that the processor mentioned in the present application can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), ready programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0223] It should also be understood that the number of processors in the present application can be one or more, which can be adjusted according to the actual application scene, which is only exemplary and is not limited. The number of memories in the embodiments of the present application can be one or more, which can be adjusted according to the actual application scene, which is only exemplary and is not limited.

[0224] It should also be noted that when the retrieval device includes a processor (or processing unit) and a memory, the processor in the present application can be integrated with the memory, or the processor and the memory can be connected through an interface, which can be adjusted according to the actual application scene and is not limited.

[0225] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system, device and unit described above can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

[0226] In several embodiments provided in the present application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interface, device or unit, and can be electrical, mechanical or other forms.

[0227] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or can be distributed on a plurality of network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0228] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0229] When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part of the prior art that makes a contribution or the whole or part of the technical solutions can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server, or other equipment, etc.) to execute the methods of the present application. Figure 1 All or part of the steps of the search method.

[0230] It should be understood that the storage medium or memory mentioned in the present application can include volatile memory or non-volatile memory, or can include both volatile and non-volatile memory. Among them, the non-volatile memory can be Read-Only Memory (ROM), Programmable ROM (PROM), Erasable Programmable ROM (EPROM), Electrically EPROM (EEPROM) or flash memory. The volatile memory can be Random Access Memory (RAM) used as an external cache. By way of example but not limitation, many forms of RAM can be used, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM) and Direct Rambus RAM (DR RAM).

[0231] It should be noted that the memory described herein is intended to include, but not limited to, these and any other suitable types of memory.

[0232] The above-described embodiments are only intended to illustrate the technical solutions of the present application, rather than limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A retrieval method characterized by, The method comprises: receiving a search operation instruction input by a user, the search operation instruction being associated with attention data; determining a first patent data set corresponding to the attention data according to the search operation instruction; performing retrieval grouping on the first patent data set according to a template file to obtain a plurality of tree data structure subgroups, wherein the tree data structure subgroups comprise one or more tree data structure nodes, the template file is a tree data structure retrieval grouping file, and each of the plurality of tree data structure subgroups corresponds to a group of tree data structure retrieval formulas in the template file; determining a patent data set corresponding to the tree data structure subgroups, the patent data set being a data set arranged in a list data structure; performing semantic analysis on the patent data set to obtain a plurality of semantic groups.

2. The method of claim 1, wherein, The method further comprises: recursively traversing each tree data structure node in the plurality of tree data structure subgroups to obtain a tree data structure retrieval result set corresponding to the plurality of tree data structure subgroups; performing an association operation on the tree data structure retrieval result set to obtain the patent data set, wherein the association operation is used to convert a data set of a tree data structure into a data set of a list data structure.

3. The method according to claim 1 or 2, characterized in that, The method further comprises: receiving a first filtering operation instruction of the user; determining a first target sub-group according to the first filtering operation instruction, the first target sub-group being any one of the plurality of tree data structure subgroups; performing semantic analysis on a patent data set corresponding to the first target sub-group to obtain a plurality of first target semantic sub-groups.

4. The method according to claim 1 or 2, characterized in that, The method further comprises: receiving a second filtering operation instruction of the user; filtering a target semantic group according to a second target sub-group to obtain N patent data sets, the second target sub-group being any one of the plurality of tree data structure subgroups, the target semantic group being any one of the plurality of semantic groups, and N being an integer greater than or equal to 1.

5. The method according to claim 1 or 2, characterized in that, The method further comprises: receiving an adjustment operation instruction of the user adjusting the template file according to the adjustment operation instruction; performing retrieval grouping on the first patent data set according to the adjusted template file to obtain tree data structure subgroups corresponding to the adjusted template file.

6. The method of claim 1 or 2, wherein, The method further comprises: receiving a template construction instruction of the user; constructing the template file according to the template construction instruction; storing the template file in a template database, the template database storing a plurality of template texts.

7. A retrieval device characterized by, The method comprises: a receiving unit configured to receive a search operation instruction input by a user, the search operation instruction being associated with attention data; a first determining unit configured to determine a first patent data set corresponding to the attention data according to the search operation instruction; The retrieval grouping unit is configured to perform retrieval grouping on the first patent data set according to a template file to obtain a plurality of tree data structure subgroups, wherein the tree data structure subgroup comprises one or more tree data structure nodes, the template file is a tree data structure retrieval grouping file, and each of the plurality of tree data structure subgroups corresponds to a group of tree data structure retrieval formulas in the template file. The second determination unit is configured to determine a patent data set corresponding to the tree data structure subgroup, and the patent data set is a data set arranged in a list data structure. The semantic grouping unit is configured to perform semantic analysis on the patent data set to obtain a plurality of semantic subgroups.

8. The apparatus of claim 7, wherein, The second determination unit is specifically configured to: recursively traverse each tree data structure node in the plurality of tree data structure subgroups to obtain a tree data structure retrieval result set corresponding to the plurality of tree data structure subgroups; and perform an association operation on the tree data structure retrieval result set to obtain the patent data set, wherein the association operation is configured to convert a data set of a tree data structure into a data set of a list data structure.

9. The apparatus of claim 7, wherein: the receiving unit is further configured to receive a filtering operation instruction of the user; the second determination unit is further configured to determine a target subgroup according to the filtering operation instruction, the target subgroup being any one of the plurality of tree data structure subgroups; the retrieval grouping unit is further configured to perform semantic analysis on a patent data set corresponding to the target subgroup to obtain a plurality of target semantic subgroups, the plurality of target semantic subgroups being obtained by performing semantic analysis on the patent data set corresponding to the target subgroup.

10. A computer storage medium, characterized in that, The instructions, when executed on a computer, cause the computer to perform the steps of the retrieval method of any one of claims 1 to 6. ​

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