CN111552792B - 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. The method comprises the steps of 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 relationship path set according to a relationship 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 relationship path set, and performing information query based on the query statement. The method and the device achieve the aims of covering all field information in the query conditions, adapting to diversified and uncertain query conditions, improving the reusability and flexibility of target data objects 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, e-commerce and enterprise ERP (Enterprise Resource Planning ), the problems of data collection, transmission, display, interaction and the like are becoming more and more important. In order to facilitate the comprehensive understanding of the network learning system operation status by the manager, the system operator needs to provide a system operation index report at an irregular period, and the system operation report is an important component of the enterprise information system as an information organization and display mode, and is a powerful tool for information browsing, analysis and printing.
Because the system operation report forms have certain requirements on the background data storage of the system and the knowledge degree of the association relation of the system operation report forms, the system operation personnel generally have difficulty in independently providing report form data. At present, one acquisition mode of the system operation report is that a developer inquires manually, and the method slows down the working progress of the developer in the iterative period, so that the labor cost is occupied; another acquisition mode is a method for generating a report by using a separately developed query webpage by a system operator, and acquiring report data by calling a background written SQL (Structured Query Language ) through a query condition in a fixed range on a combined webpage, wherein the report data which can be covered by the scheme is limited, and the query combined condition lacks a supporting algorithm for intelligently operating the system report data.
Therefore, the labor cost for acquiring the system operation report in the prior art is high, and the improvement is needed.
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 the reusability and flexibility of query conditions of a system operation report and reducing the labor cost.
In a first aspect, an embodiment of the present invention provides an information query method, including:
acquiring a descriptive language of external input, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the tag dictionary;
screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, 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 carrying out 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 of external input, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the tag dictionary;
screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, 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 carrying out 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 implements the information query method according to any one of the first aspects when executing the computer program.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer-executable instructions which, when executed by a computer processor, implement the information query method of any of the first aspects.
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 objects of the named entities 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 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 information query is performed based on the query statement. The method solves the problems of high labor cost, poor reusability and flexibility of the inquireable conditions caused by the difficulty in meeting the requirements of diversified and uncertainty screening conditions of the inquired combined conditions in the prior art, achieves the purposes of covering all field information in the inquired conditions, adapting to the diversified and uncertainty inquired conditions by flexibly combining the target data objects, and achieves the purposes of improving the reusability and flexibility of the target data objects and improving the information inquiry efficiency.
Drawings
Fig. 1 is a flow chart of an information query method according to a first embodiment of the present invention;
fig. 2 is a flow chart of an information query method according to a second embodiment of the present invention;
fig. 3 is a flow chart of an information query method according to a third embodiment of the present invention;
fig. 4 is an operation flow chart 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 invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flow chart of an information query method provided in a first embodiment of the present invention, where the embodiment is applicable to generating a query statement and performing information query according to a relationship path and a target data object set under the condition of generating the target data object set and the relationship path, and is beneficial to 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 in software and/or hardware and is typically integrated in a terminal or electronic equipment. 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 refers to a language for describing the state of things or the beginning and ending of things in detail, and the number of words is more. Named entities refer to entities in text that have a specific meaning or are highly descriptive and may include person names, place names, organization names, date and time, proper nouns, etc. It should be noted that each named entity in the descriptive language corresponds to unique field information.
For a network learning system, an administrator needs to comprehensively know the operation condition of the system, and a system operator queries a system operation report periodically to input a descriptive language to the network learning system. For example, the descriptive language is "the name, learning time, learning duration, and obtained score of the middle court course learned in 2019 of the query xiaoming", and the network learning system determines the named entity 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 descriptive language and the data objects corresponding to the named entities in the tag dictionary.
Where a tag dictionary refers to a collection of words associated with a tag. For example, if the tag is the above-mentioned network learning system, the tag dictionary may be a data set that bi-directionally associates a system operation index name common to the network learning system with a corresponding data object, where the system operation index name may include a user name, a course name, a score, a time of day, and the like, and the data object may include a data table or view, and the like.
Alternatively, the intermediate data object set determination method may be: and calculating the matching degree between the descriptive language and the data objects corresponding to each named entity in the tag dictionary, and generating the intermediate data object set according to all the data objects corresponding to each named entity in the tag dictionary exceeding the set matching value.
S130, screening target data objects from at least one intermediate data object and associated data objects of the intermediate data objects included in the intermediate data object set according to field information in the descriptive language, and generating a target data object set.
The field information in the descriptive language may include field information corresponding to each named entity in the descriptive language. The association data object may be understood as a data object that has an association relationship with the intermediate data object and that exists in the tag dictionary. For example, the intermediate data object is a class time table, and the associated data object may include a class 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 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 can be selected from each intermediate data object set according to the field information of the descriptive language as a target data object, the obtained target data object is added into the target data object set, and a query statement is generated according to the target data object in the target data object set. The method has the advantages that query sentences are not required to be generated according to all the intermediate data objects in the intermediate data object set, the association complexity between the data objects can be reduced, and the information query efficiency is further improved.
S140, determining a relation path between any two target data objects in the target data object set, and generating a relation 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, the association relationship between any two target data objects can be determined according to the field information of the target data objects, the association degree value between any two target data objects is determined according to the association relationship, the relationship path between any two target data objects is calculated according to the association degree value, and the relationship paths are combined to obtain the relationship path set.
S150, 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.
It can be understood that, through the foregoing determination of the target data object set and the relationship path set in S130 and S140, that is, the basic component elements of the query statement are determined, each target data object may be combined according to each relationship path in the relationship path set, so as to generate the query statement, and the information query is performed according to the generated query statement.
It should be noted that, in this embodiment, a target data object set may be determined according to different information query conditions (i.e., descriptive language), and 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 a query statement and perform information query according to the query statement. Compared with the prior art that information inquiry is carried out through a written complex inquiry language, the target data object set can cover all field information in inquiry conditions, and can adapt to diversified and uncertain inquiry conditions through a flexible combination mode of target data objects, so that the reusability and flexibility of the target data objects and the information inquiry efficiency can be improved.
According to the technical scheme provided by the embodiment, the object of determining the target data object set according to different information query conditions can be achieved by determining the intermediate data object set corresponding to the descriptive language according to the descriptive language and the data objects of the named entities of the tag dictionary, and screening the target data object set from the intermediate data object set according to the field information in the descriptive language, the relationship path set is generated according to the relationship path between any two target data objects in the target data object set, and the query statement is generated based on the target data object set and the relationship path set, so that the object data objects can be combined according to each relationship path, and the information query is performed based on the query statement. The method solves the problems of high labor cost, poor reusability and flexibility of the inquireable conditions caused by the difficulty in meeting the requirements of diversified and uncertainty screening conditions of the inquired combined conditions in the prior art, achieves the purposes of covering all field information in the inquired conditions, adapting to the diversified and uncertainty inquired conditions by flexibly combining the target data objects, and achieves the purposes of improving the reusability and flexibility of the target data objects and improving the information inquiry efficiency.
Example two
Fig. 2 is a 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, generating a relationship path set includes: determining 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 association relation, and generating the relation path set. For parts which are not described in detail in this method embodiment, reference is made to the above-described embodiments. 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 descriptive language and the data objects corresponding to the named entities in the tag dictionary.
S230, screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, and generating a target data object set.
Optionally, before generating the target data object set, further comprising: and judging whether each intermediate data object in the intermediate data object set has an associated data object in sequence, and 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 have no 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 target data object set may be implemented as follows:
step a: determining at least one intermediate data object included in the set of intermediate data objects and a number of fields included in each of the associated data objects of the intermediate data objects;
step b: determining the data object with the largest field number in the intermediate data object and the associated data object as a target data object, and adding the target data object set;
step c: and when the field information included in each target data object in the target data object set does not include all the field information in the descriptive language, determining the data object of the next field number which is orderly and progressively ordered according to the field number as the target data object, and adding the target data object set until the field information included in each target data object in the target data object set includes all the field information in the descriptive language.
Specifically explaining, defining a set including only intermediate data objects as set K, initializing a set of target data objects as set K', and based on intermediate data objects d in set K i Judging each intermediate data object d by field information i Whether there is an associated data object, if there is an association, it will be associated with the intermediate data object d i The data object with the association relationship is determined to be an association data object, and the association data object is added into an intermediate data object set K; and, each intermediate data object d is divided according to the order of decreasing field number i Ordering the intermediate data object d with the associated data i The data object with the largest field number in the associated data object is determined to be a target data object mi, the target data object mi is added into the initialized target data object set K ', and whether field information of the target data object mi in the target data object set K' comprises all field information in the descriptive language is judged; 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, the target data object set K' which includes all the field information in all the descriptive language is temporarily not found, and the targets are sequentially and progressively ordered according to the field number The data object of the next field number of the target data object is determined as a target data object mi, and the newly determined target data object mi is added to 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 language. The method has the advantages that the method can find the data objects comprising all field information of the descriptive language, reduce the association complexity between the data objects and facilitate the improvement of the subsequent information query efficiency.
S240, determining the association relation among all 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 each target data object. Optionally, the field information of each target data object may be parsed, the source of each target data object is determined, and the association relationship between each target data object is determined according to the source of each target data object.
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 relationship path in this embodiment may be understood as a relationship 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 used to calculate a shortest relationship path between two data objects, any one data object may be used as a node, each node may be connected, any one node may be used as a starting node, a node with the shortest path with the starting node may be traversed, until all nodes are traversed, a shortest relationship path is obtained, and a relationship path set is generated according to all the shortest relationship paths.
S260, 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.
Alternatively, the query sentence generation method of the present embodiment may be: and calling a basic query statement, inputting the target data object in the target data object set and each relation path in the relation 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 foregoing embodiment, and the preset field may include each relationship path and a combination manner of each relationship path, that is, by calling the basic query statement, each relationship path may be combined with a corresponding target data object to generate the query statement.
According to the technical scheme provided by the embodiment, the target data object set comprising all field information in descriptive language is determined by determining the number of fields included in each data object in the intermediate data object and the associated data object of the intermediate data object, so that the aim of accurately determining the target data object set can be fulfilled, the shortest relation path between any two target data objects is calculated according to the association relation by determining the association relation between each target data object in the target data object set, a basic query statement is called, the target data objects in the target data object set and each relation path in the relation path set are input into a preset field of the basic query statement, and the query statement is generated, so that the complexity of each query statement can be reduced, and the information query efficiency is improved.
Example III
Fig. 3 is a 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, based on the descriptive language and the data object corresponding to each named entity in the tag dictionary, the 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 tag 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 entities in the tag dictionary, and generating the intermediate data object set. For parts which are not described in detail in this method embodiment, reference is made to the above-described embodiments. 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: word segmentation operation is carried out on the descriptive language, so that keywords of the descriptive language are obtained; and carrying out named entity recognition on the keywords according to the tag 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 manner of a forward maximum matching method, a reverse maximum matching method, a bi-directional matching word segmentation method, and the like, and identify and extract the named entity of the descriptive language in combination 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 that the system needs to generate a query sentence from the sentence vector corresponding to the descriptive language. Thus, by converting the descriptive language into a first sentence vector using a sentence vector generation method (BidirectionalEncoder Representations from Transformer, simply BERT), it is convenient to obtain a first sentence vector reflecting the contextual characteristics and to have the system perform the subsequent step of determining the set of intermediate data objects from the first sentence vector.
S330, determining an intermediate data object from the data objects corresponding to the named entities in the tag 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 entities in the tag dictionary, and generating an intermediate data object set.
Similar to the above steps, the method of generating sentence vectors may be used to convert the descriptive language of the data object corresponding to each named entity in the tag dictionary into the second sentence vector, and determine the intermediate data object by calculating the similarity between the first sentence vector and the second sentence vector in the data object corresponding to each named entity in the tag dictionary.
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 as the intermediate data object.
It may be understood that the greater the cosine similarity between the first sentence vector and each second sentence vector, the higher the similarity between the first sentence vector and each second sentence vector, 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, the data object corresponding to the cosine similarity in the tag dictionary greater than the set threshold may be determined as the intermediate data object.
Optionally, the euclidean distance, the mahalanobis distance and the chebyshev distance between the first sentence vector and each second sentence vector may 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, where the specific calculation mode is not specifically explained.
S340, selecting target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, 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.
S360, 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.
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 sentences, so as to avoid generating invalid query languages. In this embodiment, in conjunction with the operation flowchart of the network learning system shown in fig. 4, before generating the query statement based on the target data object set and the relationship path set, fault tolerance/protection processing is further required, that is, an unauthorized database operation statement in the descriptive language is filtered, where the unauthorized database operation statement includes: adding statements and/or deleting statements.
In an operation stage, the network learning system only allows query operations to be performed on the data table or view, that is, the database operation sentences authorized by the network learning system only include query sentences, and then filtering of added sentences and/or deleted sentences is required to ensure that correct information query results are output and stability of operation of the network learning system is improved.
As shown in fig. 4, after generating the query statement, the system performs information query, and generates a log and report data according to the query result. Optionally, the report data corresponding to the query result may be in a data table format, a compressed package format, a text format, and the like.
It can be understood that after outputting the information query result or report data, the system can display the information query result to the web page end, the web page end receives the downloading operation input by the user, and the system performs the anti-theft processing on the downloading operation, so that only the user in the authorized range has the downloading authority, and the security of the information query result can be ensured. Alternatively, 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 downloading permission according to the anti-theft chain processing rule; and if the user information has downloading authority, executing the downloading operation of the information inquiry result. Optionally, the user information is transferred in token form, whether the current role of the user has corresponding downloading authority can be obtained according to the token information of the user, only the designated reference webpage is allowed to be downloaded according to the anti-theft processing rule, and if the user information is determined to have the downloading authority, the information query result downloading operation of the reference webpage is executed.
It can be understood that the web page end can also receive the 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 by: responding to the sharing operation of the information inquiry result, and encrypting and compressing the information inquiry result; and if a decryption password corresponding to the information inquiry result is received, executing the decryption operation of 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 results can be improved.
According to the technical scheme provided by the embodiment, keywords of the descriptive language are obtained by performing word segmentation operation on the descriptive language; carrying out named entity recognition on the keywords according to a tag dictionary to obtain named entities of the descriptive language and field information corresponding to the named entities, calculating cosine similarity between the first sentence vector and each second sentence vector, using the cosine similarity as the similarity, comparing each cosine similarity with a set threshold, and determining a data object corresponding to the cosine similarity larger than the set threshold as the intermediate data object, so that the intermediate data object can be accurately determined; by filtering unauthorized database operation sentences in the descriptive language, carrying out anti-theft processing on downloading operation, carrying out encryption compression on shared information inquiry results and the like, the security of the system can be improved, and the security of the information inquiry results can be ensured.
Example IV
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 determination module 41, an intermediate data object set extraction module 42, a target data object set generation module 43, a relationship path set generation 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 an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to the named entities in the tag dictionary;
a target data object set generating module 43, configured to screen, according to field information in the descriptive language, target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data object, 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 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.
On the basis of the technical solutions, the target data object set includes at least one target data object, and field information in the at least one target data object includes 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 largest field number in the intermediate data object and the associated data object as a target data object, and adding the target data object set;
and when the field information included in each target data object in the target data object set does not include all the field information in the descriptive language, determining the data object of the next field number which is orderly and progressively ordered according to the field number as the target data object, and adding the target data object set until the field information included in each target data object in the target data object set includes all the field information in the descriptive language.
On the basis of the above technical solutions, the relationship path set generating module 44 is further configured to determine an association relationship between each of 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 association 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 word segmentation on the descriptive language to obtain keywords of the descriptive language;
and carrying out named entity recognition on the keywords according to the tag 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 adopting a sentence vector generation method;
and determining the intermediate data object from the data objects corresponding to the named entities in the tag 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 entities in the tag dictionary, and generating the intermediate data object set.
Based on the above technical solutions, the intermediate data object set extraction module 42 is further configured to calculate a cosine similarity between the first sentence vector and each of the second sentence vectors, and use 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 as the intermediate data object.
Based on the above technical solutions, the information query module 45 is further configured to invoke a basic query statement, input a 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 technical schemes, the device further comprises: a filtration module; the filtering module is configured to filter an unauthorized database operation statement in the descriptive language, where the unauthorized database operation statement includes: adding statements and/or deleting statements.
On the basis of the technical schemes, the device further comprises: an anti-theft chain processing module; the anti-theft chain processing module is used for receiving the downloading operation aiming at the information inquiry result and determining the user information corresponding to the downloading operation of the information inquiry result;
Judging whether the user information has downloading permission according to the anti-theft chain processing rule;
and if the user information has downloading authority, executing the downloading operation of the information inquiry result.
On the basis of the technical schemes, the device further comprises: a sharing module; the sharing module is used for responding to the sharing operation of the information inquiry result and encrypting and compressing the information inquiry result;
and if a decryption password corresponding to the information inquiry result is received, executing the decryption operation of the encrypted and compressed information inquiry result according to the decryption password.
According to the technical scheme provided by the embodiment, the object of determining the target data object set according to different information query conditions can be achieved by determining the intermediate data object set corresponding to the descriptive language according to the descriptive language and the data objects of the named entities of the tag dictionary, and screening the target data object set from the intermediate data object set according to the field information in the descriptive language, the relationship path set is generated according to the relationship path between any two target data objects in the target data object set, and the query statement is generated based on the target data object set and the relationship path set, so that the object data objects can be combined according to each relationship path, and the information query is performed based on the query statement. The method solves the problems of high labor cost, poor reusability and flexibility of the inquireable conditions caused by the difficulty in meeting the requirements of diversified and uncertainty screening conditions of the inquired combined conditions in the prior art, achieves the purposes of covering all field information in the inquired conditions, adapting to the diversified and uncertainty inquired conditions by flexibly combining the target data objects, and achieves the purposes of improving the reusability and flexibility of the target data objects and improving the information inquiry efficiency.
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 merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 6, the electronic device 12 is in the form of a general purpose computing device. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
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 or write to non-removable, nonvolatile magnetic media (not shown in FIG. 6, commonly referred to as a "hard disk drive"). Although not shown in fig. 6, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. Memory 28 may include at least one program product having a set of program modules (e.g., a named entity determination module 41, an intermediate data object set extraction module 42, a target data object set generation module 43, a relationship path set generation module 44, and an information query module 45 of an information query device) configured to perform the functions of embodiments of the present invention.
A program/utility 44 having a set of program modules 46 (e.g., a named entity determination module 41, an intermediate data object set extraction module 42, a target data object set generation module 43, a relationship path set generation module 44, and an information query module 45) may be stored in, for example, the 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 include an implementation of a network environment. Program modules 46 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, for example, to implement an information query method provided in an embodiment of the present invention, including:
acquiring a descriptive language of external input, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the tag dictionary;
screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, 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 carrying out information query based on the query statement.
The processing unit 16 executes various functional applications and data processing by running 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, it will be understood by those skilled in the art that the processor may 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 having a computer program stored thereon, where the program when executed by a processor implements an information query method as provided by the embodiment of the present invention, including:
acquiring a descriptive language of external input, and determining a named entity included in the descriptive language;
determining an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the tag dictionary;
screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in the descriptive language, 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 carrying out information query based on the query statement.
Of course, the computer readable storage medium provided by the embodiments of the present invention, on which the computer program stored is not limited to the above method operations, but may also perform the related operations in an information query method provided by any embodiment of the present invention.
The computer storage media of embodiments of the invention may take the form of 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. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, or device, or a combination of any 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 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.
The computer readable signal medium may be embodied in a named entity, a data object, a collection of intermediate data objects, or the like, having computer readable program code embodied therein. Such propagated named entities, data objects, sets of intermediate data objects, 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 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 ++ and 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 kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected 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, each module included is only divided according to the functional logic, but not limited to the above division, so long as the corresponding function can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. 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, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (13)
1. An information query method, comprising:
acquiring a descriptive language of external input, and determining a named entity included in the descriptive language;
Determining an intermediate data object set corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the tag dictionary;
screening target data objects from at least one intermediate data object included in the intermediate data object set and associated data objects of the intermediate data objects according to field information in a descriptive language, and generating a target data object set, including:
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 object of the intermediate data object;
determining the data object with the largest field number in the intermediate data object and the associated data object as a target data object, and adding the target data object set;
when the field information included in each target data object in the target data object set does not include all the field information in the descriptive language, determining the data object of the next field number which is orderly and progressively reduced according to the field number as a target data object, and adding the target data object set until the field information included in each target data object in the target data object set includes all the field information in the descriptive language;
Determining a relationship path between any two target data objects in the target data object set, and generating a relationship path set;
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;
wherein the set of intermediate data objects includes intermediate data objects and associated data objects associated with the intermediate data objects.
2. The method of claim 1, wherein the set of target data objects comprises at least one target data object, and wherein field information in the at least one target data object comprises field information in the descriptive language.
3. The method of claim 1, wherein the determining a relationship path between any two of the set of target data objects, generating a set of relationship paths, comprises:
determining 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 association relation, and generating the relation path set.
4. The method of claim 1, wherein said determining a named entity included in the descriptive language comprises:
Word segmentation operation is carried out on the descriptive language, so that keywords of the descriptive language are obtained;
and carrying out named entity recognition on the keywords according to the tag dictionary to obtain named entities of the descriptive language and field information corresponding to the named entities.
5. The method of claim 1, wherein the determining the set of intermediate data objects corresponding to the descriptive language based on the descriptive language and the data objects corresponding to each named entity in the 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 tag 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 entities in the tag dictionary, and generating the intermediate data object set.
6. The method of claim 5, wherein determining the intermediate data object from the data objects corresponding to named entities in the tag dictionary based on a similarity between the first sentence vector and a second sentence vector of a descriptive language of the data object corresponding to named entities 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 as the intermediate data object.
7. The method of claim 1, wherein the 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 relation path in the relation path set into a preset field of the basic query statement, and generating the query statement.
8. The method of claim 7, 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 sentences in the descriptive language, wherein the unauthorized database operation sentences comprise: adding statements and/or deleting statements.
9. The method as recited in 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 downloading permission according to the anti-theft chain processing rule;
and if the user information has downloading authority, executing the downloading operation of the information inquiry result.
10. The method as recited in claim 1, further comprising:
responding to the sharing operation of the information inquiry result, and encrypting and compressing the information inquiry result;
and if a decryption password corresponding to the information inquiry result is received, executing the decryption operation of the encrypted and compressed information inquiry result according to the decryption password.
11. An information inquiry apparatus, characterized by comprising:
the named entity determining module is used for acquiring the descriptive language input from the outside and determining named entities 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 descriptive language and the data objects corresponding to each named entity in the tag dictionary;
the target data object set generating module is used for screening target data objects from at least one intermediate data object included 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 relationship path set generating module, configured to determine a relationship path between any two target data objects in the target data object set, and generate a relationship path set;
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;
the target data object set generating module 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 largest field number in the intermediate data object and the associated data object as a target data object, and adding the target data object set;
when the field information included in each target data object in the target data object set does not include all the field information in the descriptive language, determining the data object of the next field number which is orderly and progressively reduced according to the field number as a target data object, and adding the target data object set until the field information included in each target data object in the target data object set includes all the field information in the descriptive language;
Wherein the set of intermediate data objects includes intermediate data objects and associated data objects associated with the intermediate data objects.
12. 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 of any of claims 1-10 when the computer program is executed by the processor.
13. A storage medium containing computer executable instructions which when executed by a computer processor implement the information query method of any of claims 1-10.
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