Multi-dimensional inspection and verification system based on planning result

Abstract

The invention relates to the technical field of planning achievements, and provides a planning achievement-based multi-dimensional inspection and verification system, which comprises a place name matching detection module, a data consistency detection module and a regulation quotation detection module, the place name matching detection module is used for detecting whether a place name in the planning result file accords with a place name matching rule or not, if so, positioning the detected place name and marking the detected place name as a compliant place name, and otherwise, positioning the detected place name and marking the detected place name as a non-compliant place name; the data consistency detection module is used for presetting index keywords and detecting, identifying and positioning inconsistent units and / or numerical values of the index keywords in a planning result file; the regulation quotation detection module is used for detecting, identifying and positioning wrong quotation regulations, non-current abandoned regulations and / or regulations which are not correctly expressed in the planning result file; the system is high in examination quality and high in examination speed.

Description

Technical Field

[0001] The present invention relates to the technical field of planning results, and more specifically, to a multi-dimensional inspection and verification system based on planning results. Background Art

[0002] Planning outcome documents usually refer to a series of formal documents formed after the planning process is completed. These documents record various aspects of the plan, including planning background, goals, strategies, implementation plans, expected results, etc. Planning outcome documents are crucial to the implementation, supervision and evaluation of plans. They are not only the basis for planning decisions, but also an important means of conveying planning information to the public. Different types of planning outcome documents carry different information; for example, national land space planning outcome documents may include planning texts, outcome drawings, modification opinions, review reports, etc. These documents play a key role in the planning approval, review and management process, helping to ensure the compliance of the plan and the effectiveness of its implementation. In addition, there are standards and processes for the organization and storage of planning outcome data, which is very important for the long-term preservation and sharing of planning information.

[0003] In the past, planning results documents mainly relied on manual review during the preparation stage. Different reviewers may have different understandings of the scale of the review standards, resulting in inconsistent review results for similar planning projects in different departments, or some review standards may not be updated in time, which is inconsistent with the latest planning concepts and technical requirements, affecting the scientificity and rationality of the review; and the acceptance of planning results often involves multiple functional departments of Party A, and the internal review procedures may not be perfect, with information blind spots, loopholes or missing links, resulting in the review process and standards not being rigorous and comprehensive, affecting the quality of acceptance; in addition, due to the lack of support from advanced electronic and information means, the manual review method has a long review cycle, which is easy to lead to untimely delivery of review results and feedback. Reviewers have ambiguities during the review process, and need to communicate and confirm repeatedly, which reduces the review efficiency. Planning compilation personnel are unable to modify and improve according to feedback in a timely manner, affecting the modification and optimization of compilation results.

[0004] To sum up, manual review of planning outcome documents has the problems of poor review quality and slow review speed due to the lack of unified review standards, incomplete review and inconvenient review methods. Summary of the invention

[0005] In order to overcome the defects of poor review quality and slow review speed in the above-mentioned prior art, the present invention provides a multi-dimensional inspection and verification system based on planning results with high review quality and fast speed.

[0006] To solve the above technical problems, the system of the present invention comprises: a place name matching detection module, a data consistency detection module and a regulation citation detection module;

[0007] The place name matching detection module is used to detect whether the place names in the planning results file meet the place name matching rules. If so, the detected place names are located and marked as compliant place names. Otherwise, the detected place names are located and marked as non-compliant place names.

[0008] The data consistency detection module is used to preset indicator keywords, detect, identify and locate inconsistent units and / or values ​​of the indicator keywords in the planning results document;

[0009] The regulation citation detection module is used to detect, identify and locate incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in planning outcome documents.

[0010] The present invention also proposes a multi-dimensional inspection and verification method based on planning results. The multi-dimensional inspection and verification system based on planning results is applied. The method comprises the following steps:

[0011] Upload the planning results file that needs to be tested to the multi-dimensional inspection and verification system, and select a detection module to test the planning results file according to the needs;

[0012] When the selected detection module is a place name matching detection module, the place name matching detection module detects whether the place names in the planning outcome file comply with the place name matching rules. If so, the detected place names are located and identified as compliant place names; otherwise, the detected place names are located and identified as non-compliant place names;

[0013] When the selected detection module is a data consistency detection module, an indicator keyword is preset, and the data consistency detection module detects, identifies and locates inconsistent units and / or values ​​of the indicator keyword in the planning outcome document;

[0014] When the selected detection module is a regulation citation detection module, the regulation citation detection module detects, identifies and locates incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in planning outcome documents.

[0015] The present invention also proposes a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the above-mentioned multi-dimensional inspection and verification method based on planning results.

[0016] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0017] The system of the present invention includes a place name matching detection module, a data consistency detection module and a regulation citation detection module, which can automatically perform place name matching detection, data consistency detection and regulation citation detection on the content in the planning results document; it can unify the review standards to make the review more comprehensive, thereby improving the review quality, and can increase the speed of the review. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 This is a schematic diagram of the framework of the multi-dimensional inspection and verification system based on planning results proposed in Example 1;

[0019] Figure 2 This is a partial pseudo code diagram of the place name matching detection module proposed in Example 2;

[0020] Figure 3 This is a partial pseudo code diagram of the data consistency detection module proposed in Example 2;

[0021] Figure 4 This is a partial pseudo code diagram of the regulation reference detection module proposed in Example 2;

[0022] Figure 5 This is a partial pseudo code diagram of the sensitive word detection module proposed in Example 2;

[0023] Figure 6 This is a partial pseudo code diagram of the similarity detection module proposed in Example 2. DETAILED DESCRIPTION

[0024] The accompanying drawings are only used for illustrative purposes and should not be construed as limiting the present embodiment;

[0025] In order to better illustrate the present embodiment, some parts in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product;

[0026] It is understandable to those skilled in the art that some well-known structures and their descriptions may be omitted in the drawings.

[0027] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0028] Example 1

[0029] This embodiment proposes a multi-dimensional inspection and verification system based on planning results. Figure 1 It is a schematic diagram of the framework of the multi-dimensional inspection and verification system based on planning results of this embodiment;

[0030] A multi-dimensional inspection and verification system based on planning results proposed in this embodiment includes a place name matching detection module, a data consistency detection module and a regulation citation detection module;

[0031] The place name matching detection module is used to detect whether the place names in the planning results file meet the place name matching rules. If so, the detected place names are located and marked as compliant place names. Otherwise, the detected place names are located and marked as non-compliant place names.

[0032] The data consistency detection module is used to preset indicator keywords, detect, identify and locate inconsistent units and / or values ​​of the indicator keywords in the planning results document;

[0033] The regulation citation detection module is used to detect, identify and locate incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in planning outcome documents.

[0034] During the specific implementation process, the system includes a place name matching detection module, a data consistency detection module and a regulation citation detection module, which can automatically perform place name matching detection, data consistency detection and regulation citation detection on the content in the planning results document; it can unify the review standards to make the review more comprehensive, thereby improving the review quality, and can increase the speed of the review.

[0035] In an optional embodiment, the place name matching detection module is preset with a national place name database that classifies and stores place names according to administrative district levels;

[0036] Before the place name matching detection module detects whether the place names in the planning results file meet the place name matching rules, a threshold value of the difference between the main place name and the administrative area level is preset;

[0037] When the place name matching detection module detects whether the place names in the planning outcome file comply with the place name matching rules, the administrative district level corresponding to the place names in the planning outcome file and the administrative district level corresponding to the preset main place names are obtained based on the national place name database, and it is determined whether the absolute value of the difference between the administrative district levels of the two is less than or equal to the administrative district level difference threshold. If so, it is determined that the detected place name complies with the place name matching rules, the detected place name is located and identified as a compliant place name. Otherwise, it is determined that the detected place name does not comply with the place name matching rules, the detected place name is located and identified as an non-compliant place name.

[0038] In an optional embodiment, the data consistency detection module is preset with a legal measurement unit library;

[0039] Before the data consistency detection module detects inconsistent units of indicator keywords in the planning outcome file, preset indicator keywords and detection distances, wherein the number of the indicator keywords is greater than or equal to 1;

[0040] When the data consistency detection module detects inconsistent units in the planning result file, the unit consistency detection is performed on a single indicator keyword as a unit, and the steps include:

[0041] Within the full text of the planning outcome document, obtain units in the text whose distance from the target indicator keyword does not exceed the detection distance, and assign a unit replacement symbol to each detected unit, wherein the same unit corresponds to the same unit replacement symbol, and different units correspond to different unit replacement symbols;

[0042] Count the number of the unit replacement symbols. If the number of the unit replacement symbols is greater than 1, it is determined that the units corresponding to the target indicator keyword are inconsistent. All units corresponding to the target indicator keyword are identified and located, and the next indicator keyword is used as the target indicator keyword for unit consistency detection. The unit consistency detection is stopped when all indicator keywords have completed the unit consistency detection. Otherwise, the next indicator keyword is directly used as the target indicator keyword for unit consistency detection. The unit consistency detection is stopped when all indicator keywords have completed the unit consistency detection.

[0043] In an optional embodiment, after obtaining units in the text whose distance from the target indicator keyword does not exceed the detection distance within the full text of the planning outcome document, the data consistency detection module performs a numerical consistency detection on the numerical value corresponding to each unit based on all the obtained units, wherein the step of performing a numerical consistency detection on the numerical value corresponding to any unit includes:

[0044] Obtaining the numerical value in the text where the target unit is located and the distance from the target indicator keyword does not exceed the detection distance, and assigning a numerical value replacement symbol to each detected numerical value, wherein the same numerical value corresponds to the same numerical value replacement symbol, and different numerical values ​​correspond to different numerical value replacement symbols;

[0045] Count the number of the numerical replacement symbols. If the number of the numerical replacement symbols is greater than 1, determine that the numerical value corresponding to the target unit is inconsistent, identify and locate all the numerical values ​​corresponding to the target unit, and perform a numerical consistency check with the next unit as the target unit. When the numerical consistency check is completed for all units, stop the numerical consistency check; otherwise, perform a numerical consistency check with the next unit as the target unit. When the numerical consistency check is completed for all units, stop the numerical consistency check.

[0046] In an optional embodiment, the ordinance reference detection module is preset with a statutory standard library, and the statutory standard library includes: current relevant laws and regulations, current standards for planning, current standards for construction, current standards for structure, current standards for water supply and drainage, environment, current standards for electrical, current standards for gas, HVAC, current standards for civil air defense, current standards for municipal roads, current standards for cost, and current standards for surveying and mapping;

[0047] The regulation citation detection module is based on the statutory standard library and uses natural language processing technology to highlight the incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in the planning outcome documents and locate them to the corresponding positions in the text.

[0048] In an optional embodiment, the multi-dimensional inspection and verification system also includes a sensitive word detection module, which is pre-set with several sets of sensitive word libraries. The sensitive word detection module is used to detect, identify and locate sensitive words in the planning results file based on the sensitive word library, and can count and display the number of sensitive words detected.

[0049] In an optional embodiment, the multi-dimensional inspection and verification system also includes a similarity detection module, which is used to pre-upload a comparison file, preset a repetition threshold, and detect the character repetition between the planning results file and the comparison file, and locate and mark the part of the planning results file whose character repetition exceeds the preset repetition threshold, and the marked content includes the content in the comparison file that is repeated with the part.

[0050] In an optional embodiment, the multi-dimensional inspection and verification system uses word segmentation identification and automatic typesetting methods of natural language processing technology to locate and identify the content that needs to be identified.

[0051] Example 2

[0052] This embodiment is based on a multi-dimensional inspection and verification system based on planning results proposed in Embodiment 1, and proposes the following specific implementation examples:

[0053] The present invention provides a multi-dimensional inspection and verification system based on planning results, including a place name matching detection module, a data consistency detection module, a regulation citation detection module, a sensitive word detection module and a similarity detection module;

[0054] The place name matching detection module presets a national place name database, and can realize customized detection of main place names and positioning display of abnormal place name detection results; among them, the national place name database including four levels of province, city, district, county, street, town and village is preset; in the customized detection function of main place names, the user is allowed to operate and select to set the main place name of a project, and the matching detection includes all place names within the upper and lower levels of the main place name; in the positioning display function of abnormal place name detection results, when the content of the project text (planning results document) triggers a geographical term that does not conform to the upper and lower levels of the main place name, the abnormal place name is highlighted and located at the corresponding position of the text.

[0055] The data consistency detection module presets a measurement unit library, which can realize multi-indicator custom detection and positioning display of non-consistent indicator detection results; among them, eight sets of legal measurement unit libraries such as area, volume, length, mass, time, mechanics, electricity, and acoustics and optics are preset, allowing different measurement unit libraries to be called according to project requirements; in the multi-indicator custom detection function, users are allowed to customize the addition or deletion of indicator keywords to be detected, and match and detect whether the data and unit expressions that appear within the 20 characters before and after the indicator keyword are consistent in the context; in the positioning display function of non-consistent indicator detection results, when the project text triggers the retrieved indicator keyword, the data and unit expression characters involved in the indicator keyword are highlighted and positioned at the corresponding position of the text.

[0056] The regulation citation detection module presets a statutory standard library, which can realize the positioning and display of the normative expression detection results; among them, 11 sets of statutory planning standard libraries related to planning projects are preset, including current relevant laws and regulations, current norms and standards for planning professionals, current norms and standards for construction professionals, current norms and standards for structures, current norms and standards for water supply and drainage, environmental professionals, current norms and standards for electrical professionals, current norms and standards for gas and HVAC professionals, current norms and standards for civil air defense professionals, current norms and standards for municipal roads professionals, current norms and standards for cost professionals, and current norms and standards for surveying and mapping professionals, allowing them to be retrieved according to project needs; in the positioning and display function of the normative expression detection results, the document content is detected through natural language processing technology, and the erroneous citation of non-current repealed regulations and the regulations that are not correctly expressed are highlighted and located to the corresponding position of the text.

[0057] The sensitive word detection module presets a sensitive word library, which can realize customized detection of sensitive words and positioning display of sensitive word detection results; among them, multiple sets of sensitive word libraries are preset, including several sensitive words that are not allowed to appear in planning results documents, and can be retrieved according to project requirements; in the sensitive word customized detection function, according to the user's project business supervision needs, the sensitive words to be detected can be customized to be added or deleted, and single or batch addition is supported; in the sensitive word detection result positioning display function, when the project text content triggers sensitive words, the number of sensitive words appearing in the text is counted, the sensitive words are highlighted and located at the corresponding position of the text.

[0058] The similarity detection module has the functions of uploading detection and comparison files, setting detection similarity thresholds, and positioning and displaying text detection and comparison results. In the detection and comparison file uploading function, it is allowed to upload a text for reference comparison and perform character repetition detection with the project text; in the detection similarity threshold setting function, it is allowed to adjust the threshold for prompting the repetition ratio calculated by paragraphs, and only when it is higher than the input threshold, the similar paragraph text is highlighted; in the text detection and comparison result positioning and display function, the document content is accurately compared at the paragraph level, sentence level and even word level through natural language processing technology, and the corresponding position of the repeated content in the text is marked and positioned.

[0059] As an example, Figure 2 This is a partial pseudo code diagram of the place name matching detection module proposed in this embodiment. Figure 3 This is a partial pseudo code diagram of the data consistency detection module proposed in this embodiment. Figure 4 This is a partial pseudo code diagram of the regulation reference detection module proposed in this embodiment. Figure 5 This is a partial pseudo code diagram of the sensitive word detection module proposed in this embodiment. Figure 6 This is a partial pseudo code diagram of the similarity detection module proposed in this embodiment.

[0060] Figure 2 The following pseudo code shows the place name matching detection module: Figure 2 As shown, part of the operation logic of the place name matching detection module includes: creating a temporary document for processing the uploaded document; reading all the place name information in the database; reading the document of the temporary document, traversing the run segment of the document, comparing the place name information in the database, and obtaining the place name set existing in the document; obtaining the information of the main place name and the upper and lower place names from the database; judging whether the existing place name is consistent with the main place name and the upper and lower place names.

[0061] If they are consistent, obtain a set that is consistent with the main place name and the upper and lower level place names, obtain the place names in the set, add separators before and after the place names in the run segment in the document based on string matching, and cut the place names from the old run segment based on the identifier to form a new run segment, give the new run segment the format of the old segment, and set the font color to green, and determine whether it is the last element of the set. If so, generate a processing document based on the new document. Otherwise, return to obtain the place names in the set, match based on the string, and repeat subsequent operations.

[0062] If there is inconsistency, obtain a collection that is inconsistent with the main place name and the upper and lower level place names, obtain the place names in the collection, and add separators before and after the place names in the run segment in the document based on string matching; split the place names from the old run segment based on the identifier to form a new run segment, assign the new run segment the format of the old segment, and set the font color to red, and determine whether it is the last element of the collection. If so, generate a processing document based on the new document. Otherwise, return to obtain the place names in the collection, match based on the string, and repeat subsequent operations.

[0063] Figure 3 The following pseudo code shows the data consistency detection module: Figure 3 As shown, part of the operation logic of the data consistency detection module includes: generating a temporary processing document according to the uploaded document; obtaining the information of the keywords, units, and the distance before and after the keywords in the database; reading the document of the document, traversing the paragraphs, finding the strings with the distance before and after the keywords in the paragraphs, storing them in the string set, obtaining the units in the unit set, and matching them with the strings; generating a unique unit replacement symbol, and generating a mapping map1 between the unit and the replacement symbol; generating a new string according to the original string, and replacing the unit of the new string with the unit replacement symbol, adding separators before and after the unit replacement symbol, and generating a mapping map2 between the old string and the new string; matching the numbers in the new string, and putting them into the set set; judging whether it is the last unit in the unit set.

[0064] If not, return to get the unit in the unit collection and repeat the subsequent operations.

[0065] If so, determine whether the number of sets is greater than 1. If so, generate a unique data replacement symbol based on the set, and generate a mapping map3 between the data and the replacement symbol; generate another new string based on the new string, and replace the data of the new string with the data replacement symbol, add separators before and after the data replacement symbol, and generate a mapping map4 between the old string and the new string; traverse the paragraph paragraph and match the string in the string set; otherwise, directly traverse the paragraph paragraph and match the string in the string set.

[0066] Traverse the paragraph, match the string in the string set, and replace the matched string in the paragraph with a new string according to map4; split the new run segment according to the separator; restore the replacement symbol to the unit and data according to the unit mapping map1 and the data mapping map3, and set the font color of the run segment to red; determine whether it is the last string in the character set.

[0067] If not, return to traverse paragraph paragraph, match the string in the string set, and repeat the subsequent operations.

[0068] If so, generate and process the document based on the new document.

[0069] Figure 4 The following is a partial pseudo code of the regulation citation detection module: Figure 4 As shown, part of the operation logic of the regulation reference detection module includes: generating a temporary processing document based on the uploaded document; reading regulation information from the database and obtaining a regulation information collection; reading the document of the temporary document and traversing the run segment of the document; obtaining the regulations of the collection and performing string matching in the run segment; adding separators before and after the regulations; separating the regulations from the old run segment according to the identifier to form a new run segment, giving the new run segment the format of the old segment, and setting the font color to red; determining whether it is the last regulation, if not, returning the regulations of the collection and repeating subsequent operations; if so, generating a processing document based on the new document.

[0070] Figure 5 Some pseudocode of the sensitive word detection module is shown, such as Figure 5As shown, part of the operation logic of the sensitive word detection module includes: generating a temporary processing document according to the uploaded document; reading sensitive word information from the database to obtain a sensitive word set; reading the document of the temporary document and traversing the run segment of the document; obtaining the sensitive words of the set and performing string matching in the run segment; adding separators before and after the sensitive words; separating the sensitive words from the old run segment according to the identifier to form a new run segment, giving the new run segment the format of the old segment, and setting the font color to red; judging whether it is the last sensitive word, if not, returning the sensitive words of the set and repeating the subsequent operations; if so, generating a processing document according to the new document.

[0071] Figure 6 Some pseudo codes of the similarity detection module are shown, such as Figure 6 As shown, part of the operation logic of the similarity detection module includes: generating a temporary processing file based on the uploaded document and the comparison document; reading the document of the uploaded document and the comparisonDocument of the comparison document; obtaining the paragraph of the document and the paragraph of the comparisonDocument to calculate the word segmentation calculation vector, thereby obtaining the Hamming distance to obtain the similarity of the paragraphs; judging whether the content similarity is greater than the set similarity (repetition threshold).

[0072] If not, return to get the paragraph of document and the paragraph of comparisonDocment to calculate the word segmentation vector, and repeat the subsequent operations;

[0073] If so, generate a mapping map of paragraphs and similarities. If the similarity of subsequent paragraphs is greater than the similarity, they will be overwritten; further determine whether it is the last paragraph of the comparison file; if not, return to obtain the paragraph of document and the paragraph of comparisonDocment to calculate the word segmentation calculation vector, and repeat the subsequent operations; if so, obtain the paragraph and similarity of the uploaded document with the greatest similarity to the comparison document, set the font color of the similar paragraph to red, and further determine whether it is the last paragraph of the uploaded file. If not, return to obtain the paragraph of document and the paragraph of comparisonDocment to calculate the word segmentation calculation vector, and repeat the subsequent operations; if so, obtain the mapping map of similar paragraphs and similarities between the complete uploaded document paragraph and the comparison document paragraph; generate two processed documents based on document and comparisonDocument.

[0074] In this embodiment, document represents XWPFDocument. In the Apache POI library, XWPFDocument is a key class used to process Microsoft Office Word's .docx format documents. The XWPFDocument class provides developers with an interface for accessing and manipulating the content of .docx files. By using this class, you can read the text, tables, pictures, paragraphs, headers and footers in the document, and you can also create a new .docx document or modify an existing document. The main functions of XWPFDocument include reading documents, creating documents, editing documents, and saving documents; in the function of reading documents, it is possible to load an existing .docx file and allow access to its internal structure and content; in the function of creating documents, it is possible to create a new blank .docx document and allow content to be added to it; in the function of editing documents, it is possible to modify the content of an existing document, including adding, deleting or modifying elements such as text, tables, and pictures; in the function of saving documents, the modified document is saved to the file system or output as a byte stream for further processing.

[0075] Paragraph represents XWPFParagraph. In the Java Apache POI library, XWPFParagraph is a class used to represent and manipulate paragraphs in Microsoft Word documents. It is an important component of the Apache POI library for processing .docx format documents. The main functions of XWPFParagraph include representing paragraphs, accessing paragraph content, setting paragraph styles, and adding content. In the function of representing paragraphs, the XWPFParagraph object represents a paragraph in a Word document. Each XWPFDocument (representing the entire document) can contain multiple XWPFParagraph objects. In the function of accessing paragraph content, the text content in the paragraph can be accessed and manipulated through the XWPFParagraph object. The text in a paragraph is represented by an XWPFRun object, and each XWPFRun represents a continuous text with the same style. In the function of setting paragraph style, you can set various style attributes of the paragraph, such as alignment (left, right, center, etc.), indentation, line spacing, paragraph spacing, etc. In the function of adding content, you can add a new text run (XWPFRun) to the paragraph to add or modify the text content in the paragraph.

[0076] Run represents XWPFRun. In the Java Apache POI library, XWPFRun is a key class for processing text runs in Word documents. XWPFRun represents a continuous text with the same style and is part of XWPFParagraph. Each paragraph can contain multiple XWPFRun objects, and each object can independently set the text style, such as font, size, color, bold, underline, etc. The main functions of XWPFRun include text setting, style setting, special character processing and text formatting. In the text setting function, you can set or modify the text content through XWPFRun; in the style setting function, you can set the font, size, color, bold, italic, underline, emphasis and other styles of the text; in the special character processing function, you can insert special characters such as line breaks and page breaks through XWPFRun; in the text formatting function, you can process the format of the text, such as setting superscripts and subscripts.

[0077] Example 3

[0078] This embodiment proposes a multi-dimensional inspection and verification method based on planning results, and applies the multi-dimensional inspection and verification system based on planning results proposed in Example 1.

[0079] The multi-dimensional inspection and verification method based on planning results includes the following steps:

[0080] S1: Upload the planning results file to be tested to the multi-dimensional inspection and verification system, and select a detection module to test the planning results file according to the requirements;

[0081] S2: When the selected detection module is a place name matching detection module, the place name matching detection module detects whether the place names in the planning result file comply with the place name matching rules. If so, the detected place names are located and identified as compliant place names. Otherwise, the detected place names are located and identified as non-compliant place names.

[0082] S3: When the selected detection module is a data consistency detection module, an indicator keyword is preset, and the data consistency detection module detects, identifies and locates inconsistent units and / or values ​​of the indicator keyword in the planning outcome document;

[0083] S4: When the selected detection module is a regulation citation detection module, the regulation citation detection module detects, identifies and locates erroneously cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in the planning outcome documents.

[0084] This embodiment proposes a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the multi-dimensional inspection and verification method based on planning results.

[0085] The same or similar reference numerals correspond to the same or similar components;

[0086] The terms used to describe the positional relationship in the drawings are only used for illustrative purposes and should not be construed as limiting the present embodiment;

[0087] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A multi-dimensional inspection and verification system based on planning results, characterized in that: It includes place name matching detection module, data consistency detection module and regulation citation detection module; The place name matching detection module is used to detect whether the place names in the planning results file meet the place name matching rules. If so, the detected place names are located and marked as compliant place names. Otherwise, the detected place names are located and marked as non-compliant place names. The data consistency detection module is used to preset indicator keywords, detect, identify and locate inconsistent units and / or values ​​of the indicator keywords in the planning results document; The regulation citation detection module is used to detect, identify and locate incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in planning outcome documents.

2. The multi-dimensional inspection and verification system based on planning results according to claim 1 is characterized in that: The place name matching detection module is preset with a national place name database that classifies and stores place names according to administrative district levels; Before the place name matching detection module detects whether the place names in the planning results file meet the place name matching rules, a threshold value of the difference between the main place name and the administrative area level is preset; When the place name matching detection module detects whether the place names in the planning outcome file comply with the place name matching rules, the administrative district level corresponding to the place names in the planning outcome file and the administrative district level corresponding to the preset main place names are obtained based on the national place name database, and it is determined whether the absolute value of the difference between the administrative district levels of the two is less than or equal to the administrative district level difference threshold. If so, it is determined that the detected place name complies with the place name matching rules, the detected place name is located and identified as a compliant place name. Otherwise, it is determined that the detected place name does not comply with the place name matching rules, the detected place name is located and identified as an non-compliant place name.

3. The multi-dimensional inspection and verification system based on planning results according to claim 1 is characterized in that: The data consistency detection module is preset with a legal measurement unit library; Before the data consistency detection module detects inconsistent units of indicator keywords in the planning outcome file, preset indicator keywords and detection distances, wherein the number of the indicator keywords is greater than or equal to 1; When the data consistency detection module detects inconsistent units in the planning result file, the unit consistency detection is performed on a single indicator keyword as a unit, and the steps include: Within the full text of the planning outcome document, obtain units in the text whose distance from the target indicator keyword does not exceed the detection distance, and assign a unit replacement symbol to each detected unit, wherein the same unit corresponds to the same unit replacement symbol, and different units correspond to different unit replacement symbols; Count the number of the unit replacement symbols. If the number of the unit replacement symbols is greater than 1, it is determined that the units corresponding to the target indicator keyword are inconsistent. All units corresponding to the target indicator keyword are identified and located, and the next indicator keyword is used as the target indicator keyword for unit consistency detection. The unit consistency detection is stopped when all indicator keywords have completed the unit consistency detection. Otherwise, the next indicator keyword is directly used as the target indicator keyword for unit consistency detection. The unit consistency detection is stopped when all indicator keywords have completed the unit consistency detection.

4. The multi-dimensional inspection and verification system based on planning results according to claim 1 is characterized in that: After obtaining units in the text whose distance from the target indicator keyword does not exceed the detection distance within the full text of the planning outcome document, the data consistency detection module performs a numerical consistency detection on the numerical value corresponding to each unit based on all the obtained units, wherein the step of performing a numerical consistency detection on the numerical value corresponding to any unit includes: Obtaining the numerical value in the text where the target unit is located and the distance from the target indicator keyword does not exceed the detection distance, and assigning a numerical value replacement symbol to each detected numerical value, wherein the same numerical value corresponds to the same numerical value replacement symbol, and different numerical values ​​correspond to different numerical value replacement symbols; Count the number of the numerical replacement symbols. If the number of the numerical replacement symbols is greater than 1, determine that the numerical value corresponding to the target unit is inconsistent, identify and locate all the numerical values ​​corresponding to the target unit, and perform a numerical consistency check with the next unit as the target unit. When the numerical consistency check is completed for all units, stop the numerical consistency check; otherwise, perform a numerical consistency check with the next unit as the target unit. When the numerical consistency check is completed for all units, stop the numerical consistency check.

5. The multi-dimensional inspection and verification system based on planning results according to claim 4 is characterized in that: The regulation reference detection module is preset with a statutory standard library, which includes: current relevant laws and regulations, current standards for planning, current standards for construction, current standards for structure, current standards for water supply and drainage, environment, current standards for electrical, current standards for gas, HVAC, current standards for civil air defense, current standards for municipal roads, current standards for cost, and current standards for surveying and mapping; The regulation citation detection module is based on the statutory standard library and uses natural language processing technology to highlight the incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in the planning outcome documents and locate them to the corresponding positions in the text.

6. The multi-dimensional inspection and verification system based on planning results according to claim 4 is characterized in that: The multi-dimensional inspection and verification system also includes a sensitive word detection module, which is preset with several sets of sensitive word libraries. The sensitive word detection module is used to detect, identify and locate sensitive words in the planning results file based on the sensitive word library, and can count and display the number of sensitive words detected.

7. The multi-dimensional inspection and verification system based on planning results according to claim 1 is characterized in that: The multi-dimensional inspection and verification system also includes a similarity detection module, which is used to pre-upload a comparison file, preset a repetition threshold, and detect the character repetition between the planning result file and the comparison file, and locate and mark the part of the planning result file whose character repetition exceeds the preset repetition threshold, and the marked content includes the content in the comparison file that is repeated with the part.

8. The multi-dimensional inspection and verification system based on planning results according to any one of claims 1 to 7, characterized in that: The multi-dimensional inspection and verification system uses the word segmentation identification and automatic typesetting method of natural language processing technology to locate and identify the content that needs to be identified.

9. A multi-dimensional inspection and verification method based on planning results, which is applied to implement the multi-dimensional inspection and verification system based on planning results according to any one of claims 1 to 8, characterized in that: The following steps are involved: Upload the planning results file that needs to be tested to the multi-dimensional inspection and verification system, and select a detection module to test the planning results file according to the needs; When the selected detection module is a place name matching detection module, the place name matching detection module detects whether the place names in the planning outcome file comply with the place name matching rules. If so, the detected place names are located and identified as compliant place names; otherwise, the detected place names are located and identified as non-compliant place names; When the selected detection module is a data consistency detection module, an indicator keyword is preset, and the data consistency detection module detects, identifies and locates inconsistent units and / or values ​​of the indicator keyword in the planning outcome document; When the selected detection module is a regulation citation detection module, the regulation citation detection module detects, identifies and locates incorrectly cited regulations, non-current and repealed regulations and / or regulations that are not correctly expressed in planning outcome documents.

10. A computer device comprising a memory and a processor, wherein the memory stores computer-readable instructions, characterized in that: When the computer-readable instructions are executed by the processor, the processor performs the steps of the multi-dimensional inspection and verification method based on planning results as described in claim 9.

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