CN115952350A - Information query method, electronic device, storage medium and computer program product - Google Patents
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Abstract
The present disclosure provides a method for querying information, which may include: extracting a core word of a query instruction, wherein the core word is a part used for indicating entity data in the query instruction; determining entity data corresponding to the query instruction according to the core words; and extracting a plurality of candidate information corresponding to the entity data in an information database as target information, wherein the target information comprises strong related information and medium related information. The present disclosure also provides an electronic device, a storage medium, and a computer program product.
Description
Technical Field
The present disclosure relates to a method for querying information, an electronic device, a storage medium, and a computer program product.
Background
In the process of searching and querying information, related intention understanding is usually carried out on a query instruction of a user, and then information with a name completely matched with the query instruction is extracted from a database to serve as a query result, so that the query result is accurately presented. Taking the query scenario in the real estate field as an example, when the user inputs "fifth oak bay", the related art will extract and display the on-sale building trays named "fifth oak bay", so as to complete the response to the query instruction and the pushing of the accurate query result.
However, in the related art, only information with a name completely matched with the query instruction can be pushed as a query result, the query result is not subjected to related expansion, and the richness of the information in the query result pushed to the user is insufficient. Especially in the case of few or no hits on the material, the query experience of the user may be reduced. Or taking the query scenario in the real estate field as an example, when the user queries the sold building discs in the "fifth oak bay", if no sold building disc exists in the "fifth oak bay", the query result fed back to the user is "none", and the user cannot obtain effective information in the current search query. Of course, the related art will feed back the same query result for the same query instruction, and will not perform personalized ranking.
Disclosure of Invention
The disclosure provides an information query method, an electronic device, a storage medium and a computer program product.
According to one aspect of the present disclosure, a method for querying information is provided, which may include: extracting a core word of a query instruction, wherein the core word is a part used for indicating entity data in the query instruction; determining entity data corresponding to the query instruction according to the core words; and extracting a plurality of candidate information corresponding to the entity data in an information database as target information, wherein the target information comprises strong related information and medium related information.
In some embodiments, the extracting the core word of the query instruction includes: and judging whether the query instruction has a public suffix by using a regular matching module, and removing the public suffix in response to the judgment result that the query instruction has the public suffix so as to extract the core word from the query instruction.
In some embodiments, the extracting the core word of the query instruction includes: and screening candidate information matched with the query instruction in a core word database, and taking the core word of the candidate information as the core word of the query instruction.
In some embodiments, after the extracting, as the target information, a plurality of candidate information corresponding to the entity data in the information database, the method includes: and judging the matching degree between each target information and the query instruction, and classifying the target information according to the matching degree.
In some embodiments, the determining a matching degree between each of the target information and the query instruction, and classifying the target information according to the matching degree includes: taking the target information as the strongly relevant information in response to a judgment result that the target information is completely matched with the query instruction; and/or in response to a judgment result that the target information is not completely matched with the query instruction, taking the target information as the related information.
In some embodiments, after the determining a matching degree between each of the target information and the query instruction, and classifying the target information according to the matching degree, the method further includes: and sequencing the target information to obtain a target information sequence, wherein the strong correlation information is positioned before the middle correlation information in the target information sequence.
In some embodiments, the sorting the plurality of target information to obtain the target information sequence includes: determining the click characteristics of the query subject according to the historical click data of the query subject of the query instruction; calculating the similarity of the click characteristics and each target information, and respectively sequencing the strong relevant information and the middle relevant information according to the descending order of the similarity to obtain a strong relevant information sequence and a middle relevant information sequence; and arranging the strong relevant information sequence before the middle relevant information sequence to form the target information sequence.
According to another aspect of the present disclosure, there is provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for querying information according to any of the embodiments.
According to yet another aspect of the present disclosure, a readable storage medium is provided, which stores a computer program, the computer program being suitable for being loaded by a processor to execute the method for querying information according to any of the above embodiments.
According to yet another aspect of the present disclosure, there is provided a computer program product comprising a computer program/instructions, which when executed by a processor, implement the method for querying information according to any of the above embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the disclosure and together with the description serve to explain the principles of the disclosure.
Fig. 1 is a flowchart of an information query method according to an exemplary embodiment of the present disclosure.
Fig. 2 is a schematic diagram of a target information sequence according to an exemplary embodiment of the present disclosure.
Fig. 3 is a block diagram of an information query device according to an exemplary embodiment of the present disclosure.
Description of the reference numerals
1000. Information inquiry device
1002. Core word extraction module
1004. Entity data determination module
1006. Target information screening module
1100. Bus line
1200. Processor with a memory having a plurality of memory cells
1300. Memory device
1400. Other circuits.
Detailed Description
The present disclosure will be described in further detail with reference to the drawings and embodiments. It is to be understood that the specific embodiments described herein are for purposes of illustration only and are not to be construed as limitations of the present disclosure. It should be further noted that, for the convenience of description, only the portions relevant to the present disclosure are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. Technical solutions of the present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
Unless otherwise indicated, the illustrated exemplary embodiments/examples are to be understood as providing exemplary features of various details of some ways in which the technical concepts of the present disclosure may be practiced. Accordingly, unless otherwise indicated, features of the various embodiments may be additionally combined, separated, interchanged, and/or rearranged without departing from the technical concept of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Furthermore, when the terms "comprises" and/or "comprising" and variations thereof are used in this specification, the presence of stated features, integers, steps, operations, elements, components and/or groups thereof are stated but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof. It is also noted that, as used herein, the terms "substantially," "about," and other similar terms are used as approximate terms and not as degree terms, and as such, are used to interpret inherent deviations in measured values, calculated values, and/or provided values that would be recognized by one of ordinary skill in the art.
Fig. 1 is a flowchart of an information query method according to an exemplary embodiment of the present disclosure. The information query method S100 will be explained with reference to fig. 1.
And step S102, extracting core words of the query instruction.
The query instruction is an instruction sent by the query subject to query the desired information, and the query instruction may be, for example, "fifth oak bay", and then the desired information of the query subject is related information named "fifth oak bay".
The core word is a portion of the query instruction that indicates entity data. Taking the query command as "oak bay five," for example, the core word may be "oak bay.
And step S104, determining entity data corresponding to the query instruction according to the core words.
The entity data is used for representing the attribute of the expected information corresponding to the query instruction. When the query instruction is a cell name, the entity data is used for representing the geographic attributes of the cell name, including the cell name, the area name, the city name, the country name and the like.
Taking the query instruction as a "happy cell" as an example, the core word is "happy", and the entity data is a cell name, that is, a cell including the core word "happy" in the representation name; it is also possible to name the area, i.e. to characterize all cells in the "happy" area.
The query process can adopt an Elastic Search (ES) index which is good for mass data storage, data analysis and full-text retrieval query and can fully query target information with the same entity data.
Step S106, a plurality of candidate information corresponding to the entity data are extracted from the information database as target information.
The information database is a database for storing a large amount of candidate information, and can be a building information database, and a large amount of information of the building in sale can be stored in the information database. The information database can be updated in real time through a network.
The candidate information is information which is stored in an information database in advance and corresponds to entity data, when the information database is a building information database, the candidate information can be information of selling buildings, and each information of selling buildings corresponds to entity data such as a cell name, an area name, a city name and a country name. Taking the candidate information named "fifth oak bay" as an example, the entity data corresponding to "fifth oak bay" is: "Oak Bay" cells.
The target information is candidate information in the information database with the same entity data as the query instruction. Taking the query command "oak bay five-phase" as an example, the entity data is: "oak bay" cell, the target information may be all cells named "oak bay," such as "oak bay first phase," oak bay second phase, "" oak bay third phase, "" oak bay fourth phase, "and" shenyang oak bay.
The target information is divided into strong related information and middle related information according to the matching degree of the target information and the query instruction. The strongly related information refers to target information which is completely matched with the query instruction, namely target information with a name completely consistent with the query instruction; for example, the query instruction is "fifth oak bay", then the strongly relevant information is "fifth oak bay". The related information refers to target information which is not completely matched with the query instruction but is matched with the core words; for example, if the query command is "fifth oak bay", the core word is "oak bay", and the name of the target information is "first oak bay", the target information is the related information.
Generally, the strong relevant information is expected information of the query instruction, and the purpose of the relevant information in the screening is to enrich the query result and avoid the condition of poor query experience caused by the small quantity or no quantity of the strong relevant information.
In some embodiments, the specific extraction manner of the core words in step S102 may be: and judging whether the query instruction has a public suffix by using a regular matching module, and removing the public suffix in response to the judgment result that the query instruction has the public suffix so as to extract the core word in the query instruction.
The regular matching module is a virtual module for executing the regular expression and is used for judging whether the public suffix exists in the input query instruction according to a preset public suffix rule. The regular expression is a mode for screening texts conforming to a certain predetermined rule, is a conventional screening mode, and is not described in detail.
Common suffixes are common name suffixes of candidate information that are not capable of characterizing attributes of the desired information, such as "first-term", "second-term", "north yard", "south park", "north area", and "south area", among others.
When the query instruction is 'fifth oak bay', the query instruction can be queried to have a common suffix by using a regular matching module, and the common suffix is 'fifth bay'; further, the common suffix was removed to obtain the core word "oak bay".
Of course, when the query instruction does not have the common suffix, the common suffix is not removed, and the query instruction is directly used as the core word.
In some embodiments, the specific extraction manner of the core words in step S102 may also be: and screening candidate information matched with the query instruction in the core word database, and taking the core word of the candidate information as the core word of the query instruction.
The core word database contains a large amount of candidate information extracted by the core words and can be used as data support for executing offline mining. Extracting core words from the input query instruction through an offline mining logic so as to screen candidate information matched with the query instruction in a core word database, wherein the core words are used as the core words of the query instruction as the corresponding core words exist in the candidate information.
For example, when the query instruction is "Guanghua \22546court", then since it does not have an obvious public suffix or the public suffix is not included by the regular matching module, candidate information named "Guanghua \22546court" may be searched in the core word database, and its core word "Guanghua \22546court" is the core word of the query instruction.
In some embodiments, after step S106, the method further includes: and judging the matching degree between each target information and the query instruction, and classifying the target information according to the matching degree.
Since the target information is obtained by the core word in the query instruction, there is a case where the name of part of the target information coincides with the query instruction, and the name of the other part of the target information has only the core word but is different from the query instruction. At this time, the matching degree between the target information and the query instruction needs to be judged, and the target information with the name completely consistent with the query instruction is used as strong relevant information, which is expected information. The other target information is the relevant information.
Specifically, in response to a judgment result that the target information is completely matched with the query instruction, the target information is taken as strongly-relevant information; and/or taking the target information as the related information in response to the judgment result that the target information is not completely matched with the query instruction.
For example, if the query command is "fifth oak bay", the strongly related information is "fifth oak bay", and the strongly related information is "first oak bay", "second oak bay", "third oak bay", and "fourth oak bay", etc.
Through the classification of the target information, the target information can be displayed according to the correlation degree when being presented to the query main body at the later time, and the query experience of the query main body is further improved.
In some embodiments, after determining a matching degree between each target information and the query instruction, and classifying the target information according to the matching degree, the method further includes: and sequencing the plurality of target information to obtain a target information sequence.
The target information sequence is a target information list which is displayed to the query main body according to the matching degree of each target information, the query instruction and the query main body, the target information is arranged according to the matching degree in a descending order, the matching degree of the target information positioned at the first position of the target information sequence is the highest, and the matching degree of the target information positioned at the last position of the target information sequence is the lowest. Based on this, strong relevant information precedes middle relevant information in the target information sequence.
Specifically, according to historical click data of a query main body of a query instruction, click characteristics of the query main body are determined; calculating the similarity of the click characteristics and each target information, and respectively sequencing the plurality of strong relevant information and the plurality of middle relevant information according to the descending order of the similarity to obtain a strong relevant information sequence and a middle relevant information sequence; and arranging the strong relevant information sequence before the middle relevant information sequence to form a target information sequence.
The historical click data reflects the click condition of the query main body on various information in the historical query process.
Because different query subjects have different information interest degrees (different click characteristics), when target information is displayed, a plurality of target information belonging to the same matching degree should be individually sorted so as to match the query requirements of different query subjects.
For example, based on historical click data, click features of a query subject are low-price buildings
And a disc that sorts each of the pieces of related information 5 in ascending price order such that the sequence of the pieces of related information is in ascending price order while the sorting of the pieces of related information is in progress.
Fig. 2 is a schematic diagram 100 of a target information sequence according to an exemplary embodiment of the present disclosure.
As shown in fig. 2, when the query command is "oak bay five phase", the first target information of the target information sequence is "oak bay five phase", and key data of the target information is shown,
in order to query the subject. The rest of the related information, such as "second Law of oak tree", "fourth Law of oak tree 0", "third Law of oak tree" and "first Law of oak tree" is based on the historical number of clicks of the query subject
According to the click characteristics, the personalized sorting is carried out, and the information is positioned in the strong related information of 'acorn bay fifth period'
And then.
The information query method of the disclosure utilizes entity data to match a plurality of objects for a query instruction
The target information enriches the types of the target information, and avoids the condition that the query experience of the query subject is reduced under the condition 5 that the target information is little or not. In addition, for calendars based on query subject
History clicking data is used for sequencing target information, different query subjects correspond to different target information sequences, the personalized display mode is convenient for the query subjects to query the expected information, and the query experience of the query subjects is further improved.
Fig. 3 is a block diagram of an information query device according to an exemplary embodiment of the present disclosure.
As shown in fig. 3, there is provided an apparatus 1000 for querying information according to an aspect of the present disclosure, which may include: the core word extracting module 1002 is configured to extract a core word of the query instruction, where the core word is a portion of the query instruction used for indicating entity data. And an entity data determining module 1004, configured to determine, according to the core word, entity data corresponding to the query instruction. Object information
The filtering module 1006 extracts 5 a plurality of candidate information corresponding to the entity data in the information database as target information, wherein the target information includes strong related information and medium related information.
The information query device 1000 is configured to implement the information query method, and each module of the information query device is configured to execute each step of the information query method, and specific implementation manners and principles may be referred to above and are not described again.
The apparatus 1000 may include a corresponding module 0 that performs each or several of the steps in the above-described flow diagrams. Thus, each step or several steps in the above-described flow charts may be performed by a respective module, and the apparatus may comprise one or more of these modules. The modules may be one or more hardware modules specifically configured to perform the respective steps, or implemented by a processor configured to perform the respective steps, or stored within a computer-readable medium for implementation by a processor, or by some combination.
The hardware architecture may be implemented with a bus architecture. The bus architecture may include any number of interconnecting buses and bridges depending on the specific application of the hardware and the overall design constraints. The bus 1100 couples various circuits including the one or more processors 1200, the memory 1300, and/or the hardware modules together. The bus 1100 may also connect various other circuits 1400 such as peripherals, voltage regulators, power management circuits, external antennas, and the like.
The bus 1100 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one connection line is shown, but this does not indicate only one bus or one type of bus.
According to the information query device, the entity data are used for matching the query instruction with the plurality of target information, the types of the target information are enriched, and the condition that the query experience of the query main body is reduced under the condition that the target information is little or none is avoided. In addition, the target information is sequenced according to the historical click data of the query subject, different query subjects correspond to different target information sequences, the personalized display mode is more convenient for the query subject to query the expected information, and the query experience of the query subject is further improved.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present disclosure includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the implementations of the present disclosure. The processor performs the various methods and processes described above. For example, method embodiments in the present disclosure may be implemented as a software program tangibly embodied in a machine-readable medium, such as a memory. In some embodiments, some or all of the software program may be loaded and/or installed via memory and/or a communication interface. When the software program is loaded into memory and executed by a processor, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the processor may be configured to perform one of the methods described above in any other suitable manner (e.g., by means of firmware).
The logic and/or steps represented in the flowcharts or otherwise described herein may be embodied in any readable storage medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
For the purposes of this description, a "readable storage medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the readable storage medium include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM). In addition, the readable storage medium may even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in the memory.
It should be understood that portions of the present disclosure may be implemented in hardware, software, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps of the method implementing the above embodiments may be implemented by hardware that is instructed to implement by a program, which may be stored in a readable storage medium, and when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present disclosure may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a separate product, may also be stored in a readable storage medium. The storage medium may be a read-only memory, a magnetic or optical disk, or the like.
The present disclosure also provides an electronic device, including: a memory storing execution instructions; and a processor or other hardware module that executes the execution instructions stored by the memory, causing the processor or other hardware module to perform the above-described methods.
The present disclosure also provides a readable storage medium having stored therein execution instructions, the execution instructions being executed by a processor to implement a method of querying information, the method may include: extracting a core word of the query instruction, wherein the core word is a part used for indicating entity data in the query instruction; determining entity data corresponding to the query instruction according to the core words; and extracting a plurality of candidate information of the corresponding entity data in the information database as target information, wherein the target information comprises strong related information and medium related information.
The present disclosure also provides a computer program product comprising a computer program/instructions which, when executed by a processor, implement the method of querying information of any one of the embodiments of the present disclosure.
In the description of the present specification, reference to the description of "one embodiment/implementation", "some embodiments/implementations", "specific examples", or "some examples", etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment/implementation or example is included in at least one embodiment/implementation or example of the present disclosure. In this specification, the schematic representations of the terms described above are not necessarily the same embodiment/mode or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments/modes or examples. Furthermore, the various embodiments/aspects or examples and features of the various embodiments/aspects or examples described in this specification can be combined and combined by one skilled in the art without conflicting therewith.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or to implicitly indicate the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present disclosure, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise.
It will be understood by those skilled in the art that the foregoing embodiments are merely for clarity of illustration of the disclosure and are not intended to limit the scope of the disclosure. Other variations or modifications may occur to those skilled in the art, based on the foregoing disclosure, and are still within the scope of the present disclosure.
Claims (10)
1. A method for querying information, comprising:
extracting a core word of a query instruction, wherein the core word is a part used for indicating entity data in the query instruction;
determining entity data corresponding to the query instruction according to the core words; and
and extracting a plurality of candidate information corresponding to the entity data from an information database to serve as target information, wherein the target information comprises strong related information and middle related information.
2. The method for querying information according to claim 1, wherein the extracting a core word of the query instruction comprises:
and judging whether the query instruction has a public suffix by using a regular matching module, and removing the public suffix in response to the judgment result that the query instruction has the public suffix so as to extract the core word from the query instruction.
3. The method for querying information according to claim 1, wherein the extracting a core word of the query instruction comprises:
and screening candidate information matched with the query instruction in a core word database, and taking the core word of the candidate information as the core word of the query instruction.
4. The method for querying information according to claim 1, after extracting a plurality of candidate information corresponding to the entity data in an information database as target information, comprising:
and judging the matching degree between each piece of target information and the query instruction, and classifying the target information according to the matching degree.
5. The method according to claim 4, wherein the determining a matching degree between each of the target information and the query instruction, and classifying the target information according to the matching degree comprises:
taking the target information as the strongly relevant information in response to a judgment result that the target information is completely matched with the query instruction; and/or
And in response to a judgment result that the target information is not completely matched with the query instruction, taking the target information as the related information.
6. The method according to claim 5, wherein after said determining a matching degree between each of the target information and the query instruction, and classifying the target information according to the matching degree, the method further comprises:
and sequencing the target information to obtain a target information sequence, wherein the strong correlation information is positioned before the middle correlation information in the target information sequence.
7. The method for querying information according to claim 6, wherein said sorting the plurality of target information to obtain a target information sequence comprises:
determining the click characteristics of the query subject according to the historical click data of the query subject of the query instruction;
calculating the similarity of the click characteristics and each target information, and respectively sequencing the strong relevant information and the middle relevant information according to the descending order of the similarity to obtain a strong relevant information sequence and a middle relevant information sequence; and
and setting the strong relevant information sequence before the middle relevant information sequence to form the target information sequence.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of querying information according to any one of claims 1 to 7.
9. A readable storage medium, characterized in that it stores a computer program adapted to be loaded by a processor to execute the method of querying information according to any one of claims 1 to 7.
10. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the method of querying information of any one of claims 1 to 7.
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| WO2008143407A1 (en) * | 2007-05-18 | 2008-11-27 | Nhn Corporation | Method and system for providing keyword ranking using common affix |
| CN108345702A (en) * | 2018-04-10 | 2018-07-31 | 北京百度网讯科技有限公司 | Entity recommends method and apparatus |
| CN111984749A (en) * | 2019-05-23 | 2020-11-24 | 北京搜狗科技发展有限公司 | Method and device for ordering interest points |
| CN112100529A (en) * | 2020-11-17 | 2020-12-18 | 北京三快在线科技有限公司 | Search content ordering method and device, storage medium and electronic equipment |
| CN113434767A (en) * | 2021-07-07 | 2021-09-24 | 携程旅游信息技术（上海）有限公司 | UGC text content mining method, system, device and storage medium |
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