CN111552792A - Information query method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses an information query method, an information query device, electronic equipment and a storage medium. Determining an intermediate data object set corresponding to a descriptive language according to the descriptive language and data objects of named entities of a tag dictionary, screening a target data object set from the intermediate data object set according to field information in the descriptive language, generating a relation path set according to a relation path between any two target data objects in the target data object set, generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement. The method achieves the purposes of covering all field information in the query conditions, adapting to diversified and uncertain query conditions, improving the reusability and flexibility of the target data object and improving the information query efficiency.
Description
Technical Field
The embodiment of the invention relates to computer technology, in particular to an information query method, an information query device, electronic equipment and a storage medium.
Background
With the rapid development of e-government affairs, e-commerce and Enterprise ERP (Enterprise Resource Planning), the problems of data collection, transmission, display, interaction and the like become more and more important. In order to facilitate a manager to comprehensively know the operation condition of the network learning system, system operation personnel need to provide a system operation index report at irregular intervals, and the system operation report is an important component of an enterprise information system as an information organization and display mode and is a powerful tool for information browsing, analyzing and printing.
Because the system operation report has a certain requirement on the system background data storage and the understanding degree of the association relationship, the system operator generally has difficulty in independently providing report data. At present, a mode for acquiring system operation reports is to manually query by developers, and the method slows down the working progress of the developers in an iteration period and occupies manpower cost; the other acquisition mode is a method for generating a report by using an independently developed Query webpage by system operators, and the report data is acquired by using a Structured Query Language (SQL) written in a background and called by combining Query conditions in a fixed range on a page.
Therefore, the labor cost for acquiring the system operation report in the prior art is high and needs to be improved.
Disclosure of Invention
The embodiment of the invention provides an information query method, an information query device, electronic equipment and a storage medium, which are used for improving reusability and flexibility of query conditions of system operation reports and reducing labor cost.
In a first aspect, an embodiment of the present invention provides an information query method, including:
acquiring a descriptive language input from the outside, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
according to field information in a descriptive language, screening a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, and generating a target data object set;
determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
and generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
In a second aspect, an embodiment of the present invention further provides an information query method, including:
acquiring a descriptive language input from the outside, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
according to field information in a descriptive language, screening a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, and generating a target data object set;
determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
and generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
In a third aspect, an embodiment of the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor, when executing the computer program, implements the information query method according to any one of the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor implement the information query method according to any one of the first aspect.
According to the technical scheme provided by the embodiment, an intermediate data object set corresponding to a descriptive language is determined according to the descriptive language and data objects of named entities of a tag dictionary, a target data object set is screened from the intermediate data object set according to field information in the descriptive language, a relationship path set is generated according to a relationship path between any two target data objects in the target data object set, a query statement is generated based on the target data object set and the relationship path set, and information query is performed based on the query statement. The problems that in the prior art, due to the fact that the query combination conditions are difficult to meet the requirements of diversified and uncertain screening conditions, the labor cost is high, and the reusability and flexibility of the queryable conditions are poor are solved, the purposes that all field information in the query conditions is covered, diversified and uncertain query conditions can be adapted through a mode of flexibly combining target data objects are achieved, the purposes of improving the reusability and flexibility of the target data objects are achieved, and the effect of improving the information query efficiency is achieved.
Drawings
Fig. 1 is a schematic flowchart of an information query method according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of an information query method according to a second embodiment of the present invention;
fig. 3 is a schematic flowchart of an information query method according to a third embodiment of the present invention;
fig. 4 is an operation flowchart of a network learning system according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of an information query apparatus according to a fourth embodiment of the present invention;
fig. 6 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a schematic flow diagram of an information query method according to an embodiment of the present invention, where this embodiment is applicable to generating a query statement according to a relationship path and a target data object set and performing information query under the condition of generating the target data object set and the relationship path, and has the advantages of combining target data objects according to different descriptive languages and improving reusability and flexibility of the target data objects. The method may be performed by an information querying device, wherein the device may be implemented by software and/or hardware and is generally integrated in a terminal or an electronic device. Referring specifically to fig. 1, the method may include the steps of:
s110, acquiring the descriptive language of the external input, and determining the named entity included in the descriptive language.
The descriptive language is a language for describing the state of an object or the beginning and the end of the object in detail, and the number of words is large. Named entities refer to entities in the text that have a particular meaning or strong reference, and may include names of people, places, organizations, dates and times, proper nouns, and the like. It should be noted that each named entity of the descriptive language corresponds to unique field information.
For example, for a certain network learning system, an administrator needs to comprehensively know the operation condition of the system, and a system operator occasionally inquires a system operation report and inputs a descriptive language into the network learning system. For example, the descriptive language is "name of the middle court course learned in xiaoming 2019, learning time, learning duration and obtained score", and the network learning system determines named entities of the descriptive language according to the descriptive language, which may include "xiaoming", "2019", "middle court", "course", "learning time", "learning duration", "score", and the like, and each named entity corresponds to unique field information.
S120, determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary.
Where a tag dictionary refers to a collection of words related to tags. For example, if the tag is the above-mentioned web learning system, the tag dictionary may be a data set that bi-directionally associates a system operation and maintenance index name, which is common to the web learning system, with a corresponding data object, where the system operation and maintenance index name may include a user name, a course name, a score, a class hour, and the like, and the data object may include a data table or a view, and the like.
Optionally, the intermediate data object set determining method may be: and calculating the matching degree between the descriptive language and the data objects corresponding to the named entities in the label dictionary, and generating the intermediate data object set according to all the data objects corresponding to the named entities in the label dictionary exceeding the set matching value.
S130, according to the field information in the descriptive language, screening target data objects from at least one intermediate data object and associated data objects of the intermediate data objects in the intermediate data object set, and generating a target data object set.
The field information in the descriptive language may include field information corresponding to each named entity of the descriptive language. The associated data object may be understood as a data object that has an association relationship with the intermediate data object and exists in the tag dictionary. For example, the intermediate data object is a timetable, and the associated data object may include any teacher data table, a performance data table, and the like. Optionally, the set of target data objects includes at least one target data object, and the field information in the at least one target data object includes the field information in the descriptive language.
In this embodiment, after the intermediate data object set is determined, the association relationship of the intermediate data objects in the intermediate data object set may be optimized. Specifically, at least one intermediate data object including all field information of the descriptive language may be screened from each intermediate data object set as a target data object according to the field information of the descriptive language, the obtained target data object is added to the target data object set, and a query statement is generated according to the target data object in the target data object set. The operation has the advantages that query statements are not required to be generated according to all the intermediate data objects in the intermediate data object set, the association complexity among the data objects can be reduced, and the information query efficiency is further improved.
S140, determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set.
The relationship path between any two target data objects can be understood as a relationship expression between the target data objects, and the association path can be determined according to the association degree between any two target data objects. Optionally, an association relationship between any two target data objects may be determined according to the field information of the target data objects, an association degree value between any two target data objects may be determined according to the association relationship, a relationship path between any two target data objects may be calculated according to the association degree value, and the relationship paths may be combined to obtain a relationship path set.
S150, generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
It can be understood that, by determining the target data object set and the relationship path set through the foregoing S130 and S140, that is, determining the basic constituent elements of the query statement, the query statement may be generated by combining the target data objects according to the relationship paths in the relationship path set in a specific combination manner, and information query may be performed according to the generated query statement.
It should be noted that, in this embodiment, the target data object set may be determined according to different information query conditions (i.e., descriptive languages), each relationship path in the target data object set may be determined, and the target data objects may be combined according to each relationship path, so as to obtain the query statement and perform information query according to the query statement. Compared with the mode of carrying out information query by a compiled complex query language in the prior art, the target data object set can cover all field information in the query conditions, and the target data object set can adapt to diversified and uncertain query conditions by flexibly combining the target data objects, so that the reusability and flexibility of the target data object and the information query efficiency can be improved.
According to the technical scheme provided by the embodiment, the intermediate data object set corresponding to the descriptive language is determined according to the descriptive language and the data object of the named entity of the tag dictionary, the target data object set is screened from the intermediate data object set according to the field information in the descriptive language, the purpose of determining the target data object set according to different information query conditions can be achieved, the relationship path set is generated according to the relationship path between any two target data objects in the target data object set, the query statement is generated based on the target data object set and the relationship path set, and the purposes of combining the target data objects according to the relationship paths and performing information query based on the query statement can be achieved. The problems that in the prior art, due to the fact that the query combination conditions are difficult to meet the requirements of diversified and uncertain screening conditions, the labor cost is high, and the reusability and flexibility of the queryable conditions are poor are solved, the purposes that all field information in the query conditions is covered, diversified and uncertain query conditions can be adapted through a mode of flexibly combining target data objects are achieved, the purposes of improving the reusability and flexibility of the target data objects are achieved, and the effect of improving the information query efficiency is achieved.
Example two
Fig. 2 is a schematic flow chart of an information query method according to a second embodiment of the present invention. The technical scheme of the embodiment is refined on the basis of the embodiment. Optionally, the determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set includes: determining an incidence relation between each target data object in the target data object set;
and calculating the shortest relation path between any two target data objects according to the incidence relation, and generating the relation path set. In the method, reference is made to the above-described embodiments for those parts which are not described in detail. Referring specifically to fig. 2, the method may include the steps of:
s210, acquiring the descriptive language of the external input, and determining the named entity included in the descriptive language.
S220, determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary.
And S230, screening the target data object from at least one intermediate data object and the associated data object of the intermediate data object in the intermediate data object set according to the field information in the descriptive language, and generating a target data object set.
Optionally, before generating the target data object set, further comprising: and sequentially judging whether each intermediate data object in the intermediate data object set has an associated data object, if the intermediate data object has the associated data object, adding the associated data object into the intermediate data object set until all the intermediate data objects in the intermediate data object set do not have the associated data object, namely, the newly generated intermediate data object set comprises the intermediate data object and the associated data object associated with the intermediate data object.
Alternatively, the set of target data objects may be implemented as follows:
step a: determining at least one intermediate data object included in the intermediate data object set and the number of fields included in each data object in the associated data objects of the intermediate data objects;
step b: determining the data object with the maximum field number in the intermediate data object and the associated data object as a target data object, and adding the target data object into a target data object set;
step c: and when the field information included by each target data object in the target data object set does not include all the field information in the descriptive language, determining the data objects with the next field quantity which are sequentially sorted in a descending manner according to the field quantity as the target data objects, and adding the target data object set until the field information included by each target data object in the target data object set includes all the field information in the descriptive language.
Specifically explained, a set comprising only intermediate data objects is defined as a setK, initializing and defining the target data object set as a set K' according to the intermediate data object d in the set KiEach intermediate data object d is judged according to the field information ofiIf there is an associated data object, if there is an association relationship, it will be associated with the intermediate data object diDetermining the data objects with the association relationship as associated data objects, and adding the associated data objects into the intermediate data object set K; and, each intermediate data object d is sequentially reduced according to the number of fieldsiSorting the associated data to obtain intermediate data object diDetermining the data object with the largest field number in the associated data object as a target data object mi, adding the target data object mi into an initialized target data object set K ', and judging whether field information of the target data object mi in the target data object set K' comprises all field information in a descriptive language; if the field information included in each target data object in the target data object set K 'does not include all the field information in the descriptive language, it indicates that the target data object set K' including all the field information in all the descriptive languages is not found temporarily, and determines the data object with the next field number of the target data objects sorted in sequence in a descending order according to the field number as the target data object mi, and adds the newly determined target data object mi into the target data object set K 'until the field information included in each target data object mi in the target data object set K' includes all the field information in the descriptive languages. The method has the advantages that the data objects comprising all the field information of the descriptive language can be found, the association complexity among the data objects can be reduced, and the subsequent information query efficiency can be improved.
S240, determining the incidence relation among the target data objects in the target data object set.
It is understood that the association relationship between the target data objects may be determined according to the source of the target data objects. Optionally, the field information of each target data object may be analyzed to determine the source of each target data object, and the association relationship between each target data object may be determined according to the source of each target data object.
And S250, calculating the shortest relation path between any two target data objects according to the association relation, and generating a relation path set.
It is understood that the shortest relational path in the present embodiment may be understood as a relational expression between two data objects, or may be understood as an optimal combination form between two data objects. In this embodiment, a dijkstra method may be adopted to calculate a shortest relationship path between two data objects, any one data object may be used as a node, the nodes are connected, any one node is used as an initial node, a node having a shortest path with the initial node is traversed until all nodes are traversed, a shortest relationship path is obtained, and a relationship path set is generated according to all shortest relationship paths.
And S260, generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
Optionally, the query statement generating method of this embodiment may be: and calling a basic query statement, inputting the target data object in the target data object set and each relationship path in the relationship path set into a preset field of the basic query statement, and generating the query statement. The basic query statement may be a basic component of the query statement in the above embodiment, and the preset field may include each relationship path and a combination manner of each relationship path, that is, each relationship path and a corresponding target data object may be combined by invoking the basic query statement, so as to generate the query statement.
The technical solution provided by this embodiment determines a target data object set including all field information in a descriptive language by determining the number of fields included in each data object in an intermediate data object and associated data objects of the intermediate data object, the aim of accurately determining the target data object set can be achieved, and by determining the incidence relation among the target data objects in the target data object set, calculating the shortest relation path between any two target data objects according to the incidence relation, calling a basic query statement, combining the target data objects in the target data object set, and each relationship path in the relationship path set is input into a preset field of the basic query statement, the query sentences are generated, so that the complexity of each query sentence can be reduced, and the information query efficiency is improved.
EXAMPLE III
Fig. 3 is a flowchart illustrating an information query method according to a second embodiment of the present invention. The technical scheme of the embodiment is refined on the basis of the embodiment. Optionally, the determining, based on the data object corresponding to each named entity in the descriptive language and the tag dictionary, an intermediate data object set corresponding to the descriptive language includes: converting the descriptive language into a first sentence vector by adopting a sentence vector generation method; and determining the intermediate data object from the data objects corresponding to the named entities in the label dictionary according to the similarity between the first sentence vector and the second sentence vector of the descriptive language of the data object corresponding to the named entity in the label dictionary, and generating the intermediate data object set. In the method, reference is made to the above-described embodiments for those parts which are not described in detail. Referring specifically to fig. 3, the method may include the steps of:
s310, acquiring the descriptive language of the external input, and determining the named entity included in the descriptive language.
Alternatively, the named entity may be determined by: performing word segmentation operation on the descriptive language to obtain keywords of the descriptive language; and carrying out named entity recognition on the keywords according to a label dictionary to obtain named entities of the descriptive language and field information corresponding to the named entities.
In this implementation, a dictionary-based word segmentation algorithm may be used to identify the descriptive language, perform word segmentation operation on the descriptive language according to the identification result, determine the keyword, match the keyword with the named entity in the tag dictionary in a forward maximum matching method, a reverse maximum matching method, a bidirectional matching method, and the like, identify and extract the named entity of the descriptive language by combining with a named entity identification method, and determine corresponding field information of the named entity of the descriptive language.
S320, converting the descriptive language into a first sentence vector by adopting a sentence vector generation method.
It will be appreciated that the first sentence vector may reflect the descriptive language context characteristics and the system requires the generation of a query sentence from the sentence vector corresponding to the descriptive language. Therefore, by converting the descriptive language into the first sentence vector by using a sentence vector generation method (BERT), it is convenient to obtain the first sentence vector reflecting the context characteristics, and make the system execute the subsequent step of determining the intermediate data object set according to the first sentence vector.
S330, according to the similarity between the first sentence vector and the second sentence vector of the descriptive language of the data object corresponding to each named entity in the label dictionary, determining an intermediate data object from the data objects corresponding to each named entity in the label dictionary, and generating an intermediate data object set.
Similar to the foregoing steps, a sentence vector generation method may be employed to convert the descriptive language of the data objects corresponding to each named entity in the tag dictionary into a second sentence vector, and determine the intermediate data object in the data objects corresponding to each named entity in the tag dictionary by calculating the similarity between the first sentence vector and the second sentence vector.
Optionally, the method for determining the intermediate data object may include: calculating cosine similarity between the first sentence vector and each second sentence vector, and taking the cosine similarity as the similarity; comparing each cosine similarity with a set threshold; and determining the data object corresponding to the cosine similarity larger than the set threshold value as the intermediate data object.
It can be understood that the larger the cosine similarity between the first sentence vector and each second sentence vector is, the higher the similarity between the first sentence vector and each second sentence vector is, that is, the higher the similarity between the data object of the named entity in the descriptive language and the data object of the named entity in the tag dictionary is, the data object corresponding to the cosine similarity greater than the set threshold in the tag dictionary can be determined as the intermediate data object.
Optionally, the euclidean distance between the first sentence vector and each second sentence vector, the mahalanobis distance, and the chebyshev distance formula may also be calculated to determine the similarity between the first sentence vector and each second sentence vector, and further determine the intermediate data object according to the similarity, and the specific calculation manner is not specifically explained.
S340, according to the field information in the descriptive language, screening the target data object from at least one intermediate data object and the associated data object of the intermediate data object in the intermediate data object set, and generating a target data object set.
S350, determining a relation path between any two target data objects in the target data object set, and generating a relation path set.
And S360, generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
In order to ensure the normal operation of the information query system, the system needs to perform fault tolerance or protection processing before generating query statements, so as to avoid generating invalid query languages. In this embodiment, with reference to the operation flowchart of the network learning system shown in fig. 4, before generating a query statement based on the target data object set and the relationship path set, fault tolerance/protection processing needs to be performed, that is, filtering unauthorized database operation statements in the descriptive language, where the unauthorized database operation statements include: add statements and/or delete statements.
Illustratively, in the operation stage, the network learning system only allows query operation for the data table or the view, that is, the authorized database operation statements of the network learning system only include query statements, it is necessary to filter the addition statements and/or the deletion statements, to ensure that correct information query results are output, and to improve the stability of the operation of the network learning system.
As shown in fig. 4, after the query statement is generated, the system performs information query, and generates log records and report data according to the query result. Optionally, the format of the report data corresponding to the query result may be a data table format, a compressed packet format, a text format, and the like.
It can be understood that after the information query result or the report data is output, the system can display the information query result to the webpage end, the webpage end receives the downloading operation input by the user, and the system performs anti-theft link processing on the downloading operation, so that only users within an authorized range have downloading authority, and the security of the information query result can be ensured. Optionally, the downloading operation of the information query result may be performed as follows: receiving a downloading operation aiming at an information inquiry result, and determining user information corresponding to the downloading operation of the information inquiry result; judging whether the user information has a downloading authority or not according to the anti-theft link processing rule; and if the user information has the downloading authority, executing the downloading operation of the information inquiry result. Optionally, the user information is transferred in a token form, whether the current role of the user has the corresponding downloading right or not can be acquired according to the token information of the user, only a designated referrer (quote) webpage is allowed to perform downloading operation according to the anti-theft chain processing rule, and if the user information is determined to have the downloading right, the operation of downloading the information query result of the referrer (quote) webpage is executed.
It can be understood that the webpage side can also receive sharing operation for the information query result, and the system can share the information query result to other users according to the sharing operation. Optionally, the sharing operation of the information query result may be determined to be performed in the following manner: responding to the sharing operation of the information query result, and encrypting and compressing the information query result; and if a decryption password corresponding to the information inquiry result is received, executing decryption operation on the encrypted and compressed information inquiry result according to the decryption password. The advantage of this arrangement is that the security of the information query result can be improved.
According to the technical scheme provided by the embodiment, the keywords of the descriptive language are obtained by performing word segmentation operation on the descriptive language; performing named entity recognition on the keyword according to a label dictionary to obtain a named entity of the descriptive language and field information corresponding to the named entity, calculating cosine similarity between the first sentence vector and each second sentence vector, taking the cosine similarity as the similarity, comparing each cosine similarity with a set threshold, determining a data object corresponding to the cosine similarity larger than the set threshold as an intermediate data object, and accurately determining the intermediate data object; by filtering unauthorized database operation statements in the descriptive language, performing anti-theft chain processing on downloading operation, performing encryption compression on shared information query results and the like, the safety of the system can be improved, and the safety of the information query results can be ensured.
Example four
Fig. 5 is a schematic structural diagram of an information query apparatus according to a third embodiment of the present invention. Referring to fig. 5, the system includes: a named entity determining module 41, an intermediate data object set extracting module 42, a target data object set generating module 43, a relationship path set generating module 44 and an information query module 45.
The named entity determining module 41 is configured to obtain a descriptive language input from the outside, and determine a named entity included in the descriptive language;
an intermediate data object set extraction module 42, configured to determine, based on the data objects corresponding to the named entities in the descriptive language and the tag dictionary, an intermediate data object set corresponding to the descriptive language;
a target data object set generating module 43, configured to screen a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object according to field information in a descriptive language, and generate a target data object set;
a relationship path set generating module 44, configured to determine a relationship path between any two target data objects in the target data object set, and generate a relationship path set;
and the information query module 45 is configured to generate a query statement based on the target data object set and the relationship path set, and perform information query based on the query statement.
On the basis of the above technical solutions, the target data object set includes at least one target data object, and the field information in the at least one target data object includes the field information in the descriptive language.
On the basis of the above technical solutions, the target data object set generating module 43 is further configured to determine at least one intermediate data object included in the intermediate data object set and the number of fields included in each data object in the associated data objects of the intermediate data object;
determining the data object with the maximum field number in the intermediate data object and the associated data object as a target data object, and adding the target data object into the target data object set;
when the field information included by each target data object in the target data object set does not include all the field information in the descriptive language, determining the data objects with the next field quantity sequentially sorted in a descending order according to the field quantity as the target data objects, and adding the target data object set until the field information included by each target data object in the target data object set includes all the field information in the descriptive language.
On the basis of the foregoing technical solutions, the relationship path set generating module 44 is further configured to determine an association relationship between the target data objects in the target data object set;
and calculating the shortest relation path between any two target data objects according to the incidence relation, and generating the relation path set.
On the basis of the above technical solutions, the named entity determining module 41 is further configured to perform a word segmentation operation on the descriptive language to obtain a keyword of the descriptive language;
and carrying out named entity recognition on the keywords according to a label dictionary to obtain named entities of the descriptive language and field information corresponding to the named entities.
On the basis of the above technical solutions, the intermediate data object set extraction module 42 is further configured to convert the descriptive language into a first sentence vector by using a sentence vector generation method;
and determining the intermediate data object from the data objects corresponding to the named entities in the label dictionary according to the similarity between the first sentence vector and the second sentence vector of the descriptive language of the data object corresponding to the named entity in the label dictionary, and generating the intermediate data object set.
On the basis of the above technical solutions, the intermediate data object set extraction module 42 is further configured to calculate cosine similarities between the first sentence vectors and the second sentence vectors, and use the cosine similarities as the similarities;
comparing each cosine similarity with a set threshold;
and determining the data object corresponding to the cosine similarity larger than the set threshold value as the intermediate data object.
On the basis of the above technical solutions, the information query module 45 is further configured to invoke a basic query statement, input the target data object in the target data object set and each relationship path in the relationship path set into a preset field of the basic query statement, and generate the query statement.
On the basis of the above technical solutions, the apparatus further includes: a filtration module; the filtering module is configured to filter unauthorized database operation statements in the descriptive language, where the unauthorized database operation statements include: add statements and/or delete statements.
On the basis of the above technical solutions, the apparatus further includes: a hotlink processing module; the anti-theft link processing module is used for receiving downloading operation aiming at the information query result and determining user information corresponding to the downloading operation of the information query result;
judging whether the user information has a downloading authority or not according to the anti-theft link processing rule;
and if the user information has the downloading authority, executing the downloading operation of the information inquiry result.
On the basis of the above technical solutions, the apparatus further includes: a sharing module; the sharing module is used for responding to the sharing operation of the information query result and encrypting and compressing the information query result;
and if a decryption password corresponding to the information inquiry result is received, executing decryption operation on the encrypted and compressed information inquiry result according to the decryption password.
According to the technical scheme provided by the embodiment, the intermediate data object set corresponding to the descriptive language is determined according to the descriptive language and the data object of the named entity of the tag dictionary, the target data object set is screened from the intermediate data object set according to the field information in the descriptive language, the purpose of determining the target data object set according to different information query conditions can be achieved, the relationship path set is generated according to the relationship path between any two target data objects in the target data object set, the query statement is generated based on the target data object set and the relationship path set, and the purposes of combining the target data objects according to the relationship paths and performing information query based on the query statement can be achieved. The problems that in the prior art, due to the fact that the query combination conditions are difficult to meet the requirements of diversified and uncertain screening conditions, the labor cost is high, and the reusability and flexibility of the queryable conditions are poor are solved, the purposes that all field information in the query conditions is covered, diversified and uncertain query conditions can be adapted through a mode of flexibly combining target data objects are achieved, the purposes of improving the reusability and flexibility of the target data objects are achieved, and the effect of improving the information query efficiency is achieved.
EXAMPLE five
Fig. 6 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. FIG. 6 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 6 is only an example and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.
As shown in FIG. 6, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, and commonly referred to as a "hard drive"). Although not shown in FIG. 6, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set of program modules (e.g., named entity determination module 41, intermediate data object set extraction module 42, target data object set generation module 43, relationship path set generation module 44, and information query module 45 of the information query device) that are configured to perform the functions of embodiments of the present invention.
A program/utility 44 having a set of program modules 46 (e.g., named entity determination module 41, intermediate data object set extraction module 42, target data object set generation module 43, relationship path set generation module 44, and information query module 45 of the information query device) may be stored, for example, in memory 28, such program modules 46 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may comprise an implementation of a network environment. Program modules 46 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing an information query method provided by an embodiment of the present invention, including:
acquiring a descriptive language input from the outside, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
according to field information in a descriptive language, screening a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, and generating a target data object set;
determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
and generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, to implement an information query method provided by an embodiment of the present invention.
Of course, those skilled in the art can understand that the processor can also implement the technical solution of the information query method provided in any embodiment of the present invention.
EXAMPLE six
The fifth embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements an information query method provided in the fifth embodiment of the present invention, where the computer program includes:
acquiring a descriptive language input from the outside, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
according to field information in a descriptive language, screening a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, and generating a target data object set;
determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
and generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
Of course, the computer program stored on the computer-readable storage medium provided by the embodiments of the present invention is not limited to the above method operations, and may also perform related operations in an information query method provided by any embodiments of the present invention.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, or device.
A computer readable signal medium may be embodied in a named entity, a data object, a collection of intermediate data objects, etc., and carries computer readable program code therein. Such propagated named entities, data objects, intermediate data object collections, and the like. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It should be noted that, in the embodiment of the information query apparatus, the modules included in the embodiment are only divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (14)
1. An information query method, comprising:
acquiring a descriptive language input from the outside, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
according to field information in a descriptive language, screening a target data object from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, and generating a target data object set;
determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
and generating a query statement based on the target data object set and the relation path set, and performing information query based on the query statement.
2. The method of claim 1, wherein the set of target data objects comprises at least one target data object, and wherein the field information in the at least one target data object comprises field information in the descriptive language.
3. The method according to claim 1 or 2, wherein the selecting a target data object from at least one intermediate data object included in the set of intermediate data objects and associated data objects of the intermediate data object according to field information in the descriptive language, and generating a set of target data objects comprises:
determining at least one intermediate data object included in the set of intermediate data objects and the number of fields included in each data object in the associated data objects of the intermediate data objects;
determining the data object with the maximum field number in the intermediate data object and the associated data object as a target data object, and adding the target data object into the target data object set;
when the field information included by each target data object in the target data object set does not include all the field information in the descriptive language, determining the data objects with the next field quantity sequentially sorted in a descending order according to the field quantity as the target data objects, and adding the target data object set until the field information included by each target data object in the target data object set includes all the field information in the descriptive language.
4. The method of claim 1, wherein determining a relationship path between any two target data objects in the set of target data objects, generating a set of relationship paths, comprises:
determining an incidence relation between each target data object in the target data object set;
and calculating the shortest relation path between any two target data objects according to the incidence relation, and generating the relation path set.
5. The method of claim 1, wherein said determining named entities included in said descriptive language comprises:
performing word segmentation operation on the descriptive language to obtain keywords of the descriptive language;
and carrying out named entity recognition on the keywords according to a label dictionary to obtain named entities of the descriptive language and field information corresponding to the named entities.
6. The method of claim 1, wherein determining the set of intermediate data objects corresponding to the descriptive language based on the data objects corresponding to each named entity in the descriptive language and tag dictionary comprises:
converting the descriptive language into a first sentence vector by adopting a sentence vector generation method;
and determining the intermediate data object from the data objects corresponding to the named entities in the label dictionary according to the similarity between the first sentence vector and the second sentence vector of the descriptive language of the data object corresponding to the named entity in the label dictionary, and generating the intermediate data object set.
7. The method of claim 6, wherein determining the intermediate data object from the data objects corresponding to each named entity in the tag dictionary based on a similarity between the first sentence vector and a second sentence vector of the descriptive language of the data object corresponding to each named entity in the tag dictionary comprises:
calculating cosine similarity between the first sentence vector and each second sentence vector, and taking the cosine similarity as the similarity;
comparing each cosine similarity with a set threshold;
and determining the data object corresponding to the cosine similarity larger than the set threshold value as the intermediate data object.
8. The method of claim 1, wherein generating a query statement based on the set of target data objects and the set of relationship paths comprises:
and calling a basic query statement, inputting the target data object in the target data object set and each relationship path in the relationship path set into a preset field of the basic query statement, and generating the query statement.
9. The method of claim 8, further comprising, prior to generating a query statement based on the set of target data objects and the set of relationship paths:
filtering unauthorized database operation statements in the descriptive language, wherein the unauthorized database operation statements comprise: add statements and/or delete statements.
10. The method of claim 1, further comprising:
receiving a downloading operation aiming at an information inquiry result, and determining user information corresponding to the downloading operation of the information inquiry result;
judging whether the user information has a downloading authority or not according to the anti-theft link processing rule;
and if the user information has the downloading authority, executing the downloading operation of the information inquiry result.
11. The method of claim 1, further comprising:
responding to the sharing operation of the information query result, and encrypting and compressing the information query result;
and if a decryption password corresponding to the information inquiry result is received, executing decryption operation on the encrypted and compressed information inquiry result according to the decryption password.
12. An information inquiry apparatus, comprising:
the system comprises a named entity determining module, a named entity determining module and a data processing module, wherein the named entity determining module is used for acquiring a descriptive language input from outside and determining a named entity included in the descriptive language;
the intermediate data object set extraction module is used for determining an intermediate data object set corresponding to the descriptive language based on the data objects corresponding to the named entities in the descriptive language and the label dictionary;
the target data object set generating module is used for screening target data objects from at least one intermediate data object in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language to generate a target data object set;
a relation path set generation module, configured to determine a relation path between any two target data objects in the target data object set, and generate a relation path set;
and the information query module is used for generating a query statement based on the target data object set and the relation path set and carrying out information query based on the query statement.
13. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the information query method according to any one of claims 1 to 11 when executing the computer program.
14. A storage medium containing computer-executable instructions, which when executed by a computer processor implement the information query method of any one of claims 1-11.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112035581A (en) * | 2020-08-21 | 2020-12-04 | 北京字节跳动网络技术有限公司 | Model-based task processing method, device, equipment and medium |
| CN113609335A (en) * | 2021-08-12 | 2021-11-05 | 北京滴普科技有限公司 | Target object searching method, system, electronic equipment and storage medium |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104050264A (en) * | 2014-06-19 | 2014-09-17 | 华为技术有限公司 | Method and device for generating SQL statement |
| US20170024431A1 (en) * | 2015-07-24 | 2017-01-26 | International Business Machines Corporation | Generating and executing query language statements from natural language |
| CN106933906A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The querying method and device of data multidimensional degree |
| US20180373692A1 (en) * | 2017-06-21 | 2018-12-27 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method for parsing query based on artificial intelligence and computer device |
| CN109739964A (en) * | 2018-12-27 | 2019-05-10 | 北京拓尔思信息技术股份有限公司 | Knowledge data providing method, device, electronic equipment and storage medium |
| CN110275947A (en) * | 2019-05-23 | 2019-09-24 | 中国人民解放军战略支援部队信息工程大学 | Domain-specific knowledge map natural language querying method and device based on name Entity recognition |
| CN110413608A (en) * | 2019-06-17 | 2019-11-05 | 平安普惠企业管理有限公司 | Data query method, apparatus, readable storage medium storing program for executing and program product |
-
2020
- 2020-04-30 CN CN202010366910.7A patent/CN111552792B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104050264A (en) * | 2014-06-19 | 2014-09-17 | 华为技术有限公司 | Method and device for generating SQL statement |
| US20170024431A1 (en) * | 2015-07-24 | 2017-01-26 | International Business Machines Corporation | Generating and executing query language statements from natural language |
| CN106933906A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The querying method and device of data multidimensional degree |
| US20180373692A1 (en) * | 2017-06-21 | 2018-12-27 | Beijing Baidu Netcom Science And Technology Co., Ltd. | Method for parsing query based on artificial intelligence and computer device |
| CN109739964A (en) * | 2018-12-27 | 2019-05-10 | 北京拓尔思信息技术股份有限公司 | Knowledge data providing method, device, electronic equipment and storage medium |
| CN110275947A (en) * | 2019-05-23 | 2019-09-24 | 中国人民解放军战略支援部队信息工程大学 | Domain-specific knowledge map natural language querying method and device based on name Entity recognition |
| CN110413608A (en) * | 2019-06-17 | 2019-11-05 | 平安普惠企业管理有限公司 | Data query method, apparatus, readable storage medium storing program for executing and program product |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112035581A (en) * | 2020-08-21 | 2020-12-04 | 北京字节跳动网络技术有限公司 | Model-based task processing method, device, equipment and medium |
| CN113609335A (en) * | 2021-08-12 | 2021-11-05 | 北京滴普科技有限公司 | Target object searching method, system, electronic equipment and storage medium |
| CN113609335B (en) * | 2021-08-12 | 2023-02-03 | 北京滴普科技有限公司 | Target object searching method, system, electronic equipment and storage medium |
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