CN115408420B - Method and apparatus for automatically filtering map notes and points of interest using a computer - Google Patents
Method and apparatus for automatically filtering map notes and points of interest using a computer Download PDFInfo
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- CN115408420B CN115408420B CN202211074988.7A CN202211074988A CN115408420B CN 115408420 B CN115408420 B CN 115408420B CN 202211074988 A CN202211074988 A CN 202211074988A CN 115408420 B CN115408420 B CN 115408420B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/242—Query formulation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2457—Query processing with adaptation to user needs
- G06F16/24575—Query processing with adaptation to user needs using context
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/284—Lexical analysis, e.g. tokenisation or collocates
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The invention provides a method and a device for automatically filtering map marks and interest points by using a computer, comprising the following steps: constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group; acquiring identification content; filtering the identification content sequentially through a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group to obtain a filtering result; the accuracy and the efficiency of recognition can be improved.
Description
Technical Field
The present invention relates to the field, and more particularly, to a method and apparatus for automatically filtering map notes and points of interest using a computer.
Background
Currently, the identification of map annotations is done entirely manually. The method mainly comprises the steps of keyword filtering and manual identification through a computer.
The interest points containing the keywords in the keyword library are filtered from massive interest points by determining the keyword library through a computer programming program, and whether the interest points can be represented or not is judged through manual identification, so that a final identification result is obtained.
In the identification process, the identification standards are not uniform and the identification results are not uniform because the identification is mainly carried out manually; when the workload of the staff is large, the timeliness cannot be ensured.
Disclosure of Invention
In view of the above, the present invention aims to provide a method and a device for automatically filtering map notes and points of interest by using a computer, which can improve the accuracy and the efficiency of recognition.
In a first aspect, an embodiment of the present invention provides a method for automatically filtering map notes and points of interest using a computer, the method comprising:
constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group;
acquiring identification content;
and filtering the identification content sequentially through the white list library, the black list word library group, the keyword library group, the reverse keyword library and the reverse keyword library group to obtain a filtering result.
In a second aspect, an embodiment of the present invention provides an apparatus for automatically filtering map notes and points of interest using a computer, the apparatus comprising:
the construction module is used for constructing a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group;
the acquisition module is used for acquiring the identification content;
the filtering module is used for filtering the identification content through the white list library, the black list word library group, the keyword library group, the reverse keyword library and the reverse keyword library group in sequence to obtain a filtering result.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, and a processor, where the memory stores a computer program executable on the processor, and where the processor implements a method as described above when executing the computer program.
In a fourth aspect, embodiments of the present invention provide a computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method as described above.
The embodiment of the invention provides a method and a device for automatically filtering map marks and interest points by using a computer, comprising the following steps: constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group; acquiring identification content; filtering the identification content sequentially through a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group to obtain a filtering result; the accuracy and the efficiency of recognition can be improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a method for automatically filtering map notes and points of interest using a computer according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an apparatus for automatically filtering map notes and points of interest using a computer according to a second embodiment of the present invention.
Icon:
1-building a module; 2-an acquisition module; 3-a filtration module.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to facilitate understanding of the present embodiment, the following describes embodiments of the present invention in detail.
Embodiment one:
fig. 1 is a flowchart of a method for automatically filtering map notes and points of interest using a computer according to an embodiment of the present invention.
Referring to fig. 1, the method includes the steps of:
step S101, a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group are constructed;
step S102, acquiring identification content;
step S103, filtering the identification content through the white list bank, the black list word bank and the black list word bank group, the keyword bank and the keyword bank group, the reverse keyword bank and the reverse keyword bank group in sequence to obtain a filtering result.
Here, the identification content is filtered through the white list library, and a first filtering result is obtained; when the first filtering result is suspected, filtering the identification content through a blacklist word stock and a blacklist word stock group to obtain a second filtering result; when the second filtering result is suspected, filtering the identification content through a keyword library and a keyword library group to obtain a third filtering result; and when the third filtering result is suspected, filtering the identification content through the reverse keyword library and the reverse keyword library group to obtain a fourth filtering result. If the fourth filtering result is suspected, the fourth filtering result is required to be identified manually.
Further, the black list word stock and the black list word stock group, the keyword stock and the keyword stock group, the reverse keyword stock and the reverse keyword stock group all comprise word types and appearance positions; the word category includes single keywords and combined keywords, and the appearance positions include beginning, middle and ending; wherein, the single keyword is an independent word, and the combined keyword is formed by arbitrarily combining words in 3 or more keyword libraries of the same type.
Specifically, the white list library refers to the identification content of the manually identified allowable representation. The white list library is required to be gradually expanded according to the manual identification result, and the library is empty when the white list library is initially constructed.
And constructing a blacklist word stock and a blacklist word stock group, wherein each keyword comprises 2 attributes of word category and appearance position.
Word category. The method is divided into two types of single keywords and combined keywords. A single keyword indicates that the keyword is an independent word; the combined keywords are formed by arbitrarily combining words in 3 or more keyword libraries of the same type. The keyword library of the same type is formed by summarizing all words of the same type, and comprises a digital type library, a chemical element type library and the like. The keywords are classified into a beginning category, a middle category and an ending category according to the specific positions of the keywords in the identified content.
A keyword library and a keyword library group are constructed, and each keyword comprises 2 attributes of word category and appearance position.
And constructing a reverse keyword library and a reverse keyword library group, wherein each keyword comprises 2 attributes of word category and appearance position. Wherein the identification content generally refers to a single word or a combination of words. For example, a single word is a province army area, and a combination word composed of a plurality of words is a province army area hospital east gate.
The word category and the appearance position are already described in the blacklist word stock and the blacklist word stock group, and are not described in detail herein.
Further, step S103 includes:
the recognition content is filtered sequentially through the filtering rules of the white list library, the filtering rules of the black list word library and the black list word library group, the filtering rules of the keyword library and the keyword library group, and the filtering rules of the reverse keyword library and the reverse keyword library group, so that a filtering result is obtained.
Specifically, 1) filtering the identified content by the filtering rule of the white list library, specifically referring to table 1:
TABLE 1
Wherein W represents the identification content to be filtered, and if the first filtering result is suspected, only represents that the identification content is possibly judged to be wrong, and does not represent that the identification content is already judged to be wrong. The filtering results of the second step and the third step are the same.
2) Comparing the identification content with the words in the blacklist word stock and the blacklist word stock group one by one, and adopting the filtering rule of the blacklist word stock as shown in table 2:
TABLE 2
Wherein W represents the identification content to be filtered, L Blacklist words The blacklist word appears at a location identifying the content; l (L) Prescribed position And the specified position of the blackname word specified in the blacklist word library in the identification content is referred to. When any blackname word epsilon W and L in the blacklist word stock Blacklist words ＝L Prescribed position I.e. the result of the second step is considered to be erroneous.
The filtering rules using the blacklist word stock set are shown in table 3:
TABLE 3 Table 3
Wherein, the black name word N refers to the N black name word of the black list phrase; l (L) Black name word N Indicating that the nth blacklist word appears at the position of the second identification content; l (L) Prescribed position N And designating the designated position of the Nth blackname word of the blacklist phrase in the second identification content.
When N blacklist words in any blacklist phrase must be allSatisfies the black name word N epsilon W and L Black name word N ＝L Prescribed position N When the second step of filtering is performed, the result is considered to be an error.
If the filtering result of the second step is wrong, the representation identification content does not allow representation.
3) Comparing the recognition content with the words in the keyword library and the keyword library group one by one, and adopting the filtering rule of the keyword library as shown in the table 4:
TABLE 4 Table 4
Wherein L is Keyword(s) The key words appear at the positions of the identification content; l (L) Prescribed position Refers to the specified location of a specified keyword in a keyword library in the identified content. When any keyword E W and L in keyword library Keyword(s) ＝L Prescribed position The result of the third step is considered to be suspected. The filtering rules for using keyword library sets are shown in table 5:
TABLE 5
Wherein, the keyword N refers to the N-th keyword of the keyword group; l (L) Keyword N Meaning that the nth keyword appears at the location of the identified content; l (L) Prescribed position N Refers to the appointed position of the N-th keyword of the keyword group in the identification content.
When N keywords in any keyword group must all satisfy the keywords N E W and L Keyword N ＝L Prescribed position N When the filtering result of the third step is suspected; if the result of the filtering in the third step is correct, the representation identifies the content-allowed representation.
4) Comparing the identification content with the words in the reverse keyword library and the reverse keyword library group one by one, and adopting the filtering rule of the reverse keyword library as shown in table 6:
TABLE 6
Wherein L is Reverse keyword Indicating that the reverse keyword appears at the position of the identification content; l (L) Prescribed position Refers to the specified position of the specified reverse keyword in the reverse keyword library in the identification content.
When any reverse keyword E W and L in the reverse keyword library Reverse keyword ＝L Prescribed position The result of the fourth step is considered to be correct.
The filtering rules for using the reverse keyword library set are shown in table 7:
TABLE 7
Wherein, the reverse keyword N refers to the N reverse keyword of the reverse keyword group; l (L) Reverse keyword N Indicating that the Nth reverse keyword appears at the position of the identification content; l (L) Prescribed position N The designated position of the N reverse keyword of the reverse keyword group in the identification content is indicated.
When N reverse keywords in any reverse keyword group must all satisfy the reverse keywords N E W and L Reverse keyword N ＝L Prescribed position N In this case, the result of the fourth step was considered to be correct.
If the result of the filtering in the fourth step is correct, the representation identifies the content-allowed representation.
Further, the method comprises the following steps:
step S201, if the filtering result is suspected, identifying by a manual filtering method to obtain an identification result;
step S202, if the identification result is correct, the identification result is stored in a white list library.
Specifically, if the identification content is filtered by the method and the identification content with the suspected filtering result still exists, whether the identification content can be represented is manually judged. And the identification content with the correct judgment result is included in the white list library, so that the identification content is prevented from entering a manual filtering step in the next filtering process. Meanwhile, the modification of each library is perfect according to the manual filtering result.
The embodiment of the invention provides a method for automatically filtering map marks and interest points by using a computer, which comprises the following steps: constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group; acquiring identification content; filtering the identification content sequentially through a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group to obtain a filtering result; the accuracy and the efficiency of recognition can be improved.
Embodiment two:
fig. 2 is a schematic diagram of an apparatus for automatically filtering map notes and points of interest using a computer according to a second embodiment of the present invention.
Referring to fig. 2, the apparatus includes:
the construction module 1 is used for constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank and a reverse keyword bank group;
an acquisition module 2 for acquiring the identification content;
the filtering module 3 is configured to filter the identification content sequentially through the white list library, the black list word library group, the keyword library group, the reverse keyword library, and the reverse keyword library group, to obtain a filtering result.
Further, the filtering module 3 is specifically configured to:
the recognition content is filtered sequentially through the filtering rules of the white list library, the filtering rules of the black list word library and the black list word library group, the filtering rules of the keyword library and the keyword library group, and the filtering rules of the reverse keyword library and the reverse keyword library group, so that a filtering result is obtained.
Further, the black list word stock and the black list word stock group, the keyword stock and the keyword stock group, the reverse keyword stock and the reverse keyword stock group all comprise word types and appearance positions;
the word category includes single keywords and combined keywords, and the appearance positions include beginning, middle and ending;
wherein, the single keyword is an independent word, and the combined keyword is formed by arbitrarily combining words in 3 or more keyword libraries of the same type.
Further, the device further comprises:
the identification module (not shown) is used for carrying out identification by a manual filtering method to obtain an identification result when the filtering result is suspected;
and the storage module (not shown) is used for storing the identification result into the white list library when the identification result is correct.
The embodiment of the invention provides a device for automatically filtering map marks and interest points by using a computer, which comprises the following steps: constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group; acquiring identification content; filtering the identification content sequentially through a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group to obtain a filtering result; the accuracy and the efficiency of recognition can be improved.
The embodiment of the invention also provides electronic equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the method for automatically filtering map notes and interest points by using the computer.
The present invention also provides a computer readable medium having non-volatile program code executable by a processor, the computer readable medium having a computer program stored thereon, the computer program when executed by the processor performing the steps of the method of automatically filtering map notes and points of interest using a computer of the above embodiments.
The computer program product provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to perform the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In addition, in the description of embodiments of the present invention, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (6)
1. A method for automatically filtering map notes and points of interest using a computer, the method comprising:
constructing a white list bank, a black list word bank group, a keyword bank group, a reverse keyword bank, and a reverse keyword bank group;
acquiring identification content;
the identification content is filtered through the white list library, the black list word library group, the keyword library group, the reverse keyword library and the reverse keyword library group in sequence, so that a filtering result is obtained;
the blacklist word stock and the blacklist word stock group, the keyword stock and the keyword stock group, the reverse keyword stock and the reverse keyword stock group all comprise word types and appearance positions;
the word category comprises a single keyword and a combined keyword, and the appearance positions comprise a beginning, a middle and an ending;
wherein the single keywords are independent words, and the combined keywords are formed by arbitrarily combining words in 3 or more keyword libraries of the same type;
the recognition content is filtered sequentially through the white list bank, the black list word bank group, the keyword bank group, the reverse keyword bank and the reverse keyword bank group to obtain a filtering result, wherein the filtering result comprises the following steps:
filtering the identification content through the white list library to obtain a first filtering result; when the first filtering result is suspected, filtering the identification content through the blacklist word stock and the blacklist word stock group to obtain a second filtering result; when the second filtering result is suspected, filtering the identification content through the keyword library and the keyword library group to obtain a third filtering result; when the third filtering result is suspected, filtering the identification content through the reverse keyword library and the reverse keyword library group to obtain a fourth filtering result; if the fourth filtering result is suspected, the fourth filtering result is required to be identified manually;
the filtering rules of the white list library are as follows:
when the identification content to be filtered belongs to the white list library, the first filtering result is correct; when the identification content to be filtered does not belong to the white list library, the first filtering result is suspected;
the filtering rule of the blacklist word stock is as follows:
when any blacklist word in the blacklist word stock belongs to the identification content to be filtered, and the position of the blacklist word in the identification content is equal to the appointed position of the blacklist word in the identification content, which is specified in the blacklist word stock, the second filtering result is wrong;
when any black name word in the black list word stock does not belong to the identification content to be filtered, or the position of the black list word in the identification content is not equal to the appointed position of the black list word in the identification content, which is specified in the black list word stock, the second filtering result is suspected;
the filtering rule of the blacklist word stock group is as follows:
when all of the N blacklist words in any blacklist phrase satisfy: the N-th blacklist word of the blacklist phrase belongs to the identification content to be filtered, and the position of the N-th blacklist word in the second identification content is equal to the appointed position of the N-th blacklist word of the blacklist phrase in the second identification content, and the second filtering result is an error;
when all N blacklist words in any blacklist phrase meet the following conditions: the N-th blacklist word of the blacklist phrase does not belong to the identification content to be filtered, or the position of the N-th blacklist word in the second identification content is not equal to the appointed position of the N-th blacklist word of the blacklist phrase in the second identification content, and the second filtering result is suspected;
the filtering rules of the keyword library are as follows:
when any keyword in the keyword library belongs to the identification content to be filtered, and the position of the keyword appearing in the identification content is equal to the appointed position of the keyword specified in the keyword library in the identification content, the third filtering result is suspected;
when any keyword in the keyword library does not belong to the identification content to be filtered, or the position of the keyword appearing in the identification content is not equal to the appointed position of the keyword specified in the keyword library in the identification content, the third filtering result is correct;
the filtering rules of the keyword library group are as follows:
when all N keywords in any keyword group satisfy: the N-th keyword of the keyword group belongs to the identification content to be filtered, the position of the N-th keyword in the identification content is equal to the appointed position of the N-th keyword of the keyword group in the identification content, and the third filtering result is suspected;
when all N keywords in any keyword group satisfy: the N-th keyword of the keyword group does not belong to the identification content to be filtered, or the position of the N-th keyword in the identification content is not equal to the appointed position of the N-th keyword of the keyword group in the identification content, and the third filtering result is correct;
the filtering rules of the reverse keyword library are as follows:
when any reverse keyword in the reverse keyword library belongs to the identification content to be filtered, and the position of the reverse keyword appearing in the identification content is equal to the appointed position of the reverse keyword specified in the reverse keyword library in the identification content, the fourth filtering result is correct;
when any reverse keyword in the reverse keyword library does not belong to the identification content to be filtered, or the position of the reverse keyword appearing in the identification content is not equal to the appointed position of the reverse keyword specified in the reverse keyword library in the identification content, the fourth filtering result is suspected;
the filtering rule of the reverse keyword library group is as follows:
when all N reverse keywords in any reverse keyword group satisfy: the N reverse keywords of the reverse keyword group belong to the identification content to be filtered, the position of the N reverse keywords in the identification content is equal to the appointed position of the N reverse keywords of the reverse keyword group in the identification content, and the fourth filtering result is correct;
when all N reverse keywords in any reverse keyword group meet the following conditions: the N-th reverse keyword of the reverse keyword group does not belong to the identification content to be filtered, or the position of the N-th reverse keyword in the identification content is not equal to the appointed position of the N-th reverse keyword of the reverse keyword group in the identification content, and the fourth filtering result is suspected.
2. The method for automatically filtering map notes and points of interest using a computer of claim 1, wherein the method further comprises:
if the filtering result is suspected, identifying by a manual filtering method to obtain an identification result;
and if the identification result is correct, storing the identification result into the white list library.
3. An apparatus for automatically filtering map notes and points of interest using a computer, the apparatus comprising:
the construction module is used for constructing a white list library, a black list word library group, a keyword library group, a reverse keyword library and a reverse keyword library group;
the acquisition module is used for acquiring the identification content;
the filtering module is used for filtering the identification content through the white list library, the black list word library group, the keyword library group, the reverse keyword library and the reverse keyword library group in sequence to obtain a filtering result;
the blacklist word stock and the blacklist word stock group, the keyword stock and the keyword stock group, the reverse keyword stock and the reverse keyword stock group all comprise word types and appearance positions;
the word category comprises a single keyword and a combined keyword, and the appearance positions comprise a beginning, a middle and an ending;
wherein the single keywords are independent words, and the combined keywords are formed by arbitrarily combining words in 3 or more keyword libraries of the same type;
the filter module is specifically used for:
filtering the identification content through the white list library to obtain a first filtering result; when the first filtering result is suspected, filtering the identification content through the blacklist word stock and the blacklist word stock group to obtain a second filtering result; when the second filtering result is suspected, filtering the identification content through the keyword library and the keyword library group to obtain a third filtering result; when the third filtering result is suspected, filtering the identification content through the reverse keyword library and the reverse keyword library group to obtain a fourth filtering result; if the fourth filtering result is suspected, the fourth filtering result is required to be identified manually;
the filtering rules of the white list library are as follows:
when the identification content to be filtered belongs to the white list library, the first filtering result is correct; when the identification content to be filtered does not belong to the white list library, the first filtering result is suspected;
the filtering rule of the blacklist word stock is as follows:
when any blacklist word in the blacklist word stock belongs to the identification content to be filtered, and the position of the blacklist word in the identification content is equal to the appointed position of the blacklist word in the identification content, which is specified in the blacklist word stock, the second filtering result is wrong;
when any black name word in the black list word stock does not belong to the identification content to be filtered, or the position of the black list word in the identification content is not equal to the appointed position of the black list word in the identification content, which is specified in the black list word stock, the second filtering result is suspected;
the filtering rule of the blacklist word stock group is as follows:
when all of the N blacklist words in any blacklist phrase satisfy: the N-th blacklist word of the blacklist phrase belongs to the identification content to be filtered, and the position of the N-th blacklist word in the second identification content is equal to the appointed position of the N-th blacklist word of the blacklist phrase in the second identification content, and the second filtering result is an error;
when all N blacklist words in any blacklist phrase meet the following conditions: the N-th blacklist word of the blacklist phrase does not belong to the identification content to be filtered, or the position of the N-th blacklist word in the second identification content is not equal to the appointed position of the N-th blacklist word of the blacklist phrase in the second identification content, and the second filtering result is suspected;
the filtering rules of the keyword library are as follows:
when any keyword in the keyword library belongs to the identification content to be filtered, and the position of the keyword appearing in the identification content is equal to the appointed position of the keyword specified in the keyword library in the identification content, the third filtering result is suspected;
when any keyword in the keyword library does not belong to the identification content to be filtered, or the position of the keyword appearing in the identification content is not equal to the appointed position of the keyword specified in the keyword library in the identification content, the third filtering result is correct;
the filtering rules of the keyword library group are as follows:
when all N keywords in any keyword group satisfy: the N-th keyword of the keyword group belongs to the identification content to be filtered, the position of the N-th keyword in the identification content is equal to the appointed position of the N-th keyword of the keyword group in the identification content, and the third filtering result is suspected;
when all N keywords in any keyword group satisfy: the N-th keyword of the keyword group does not belong to the identification content to be filtered, or the position of the N-th keyword in the identification content is not equal to the appointed position of the N-th keyword of the keyword group in the identification content, and the third filtering result is correct;
the filtering rules of the reverse keyword library are as follows:
when any reverse keyword in the reverse keyword library belongs to the identification content to be filtered, and the position of the reverse keyword appearing in the identification content is equal to the appointed position of the reverse keyword specified in the reverse keyword library in the identification content, the fourth filtering result is correct;
when any reverse keyword in the reverse keyword library does not belong to the identification content to be filtered, or the position of the reverse keyword appearing in the identification content is not equal to the appointed position of the reverse keyword specified in the reverse keyword library in the identification content, the fourth filtering result is suspected;
the filtering rule of the reverse keyword library group is as follows:
when all N reverse keywords in any reverse keyword group satisfy: the N reverse keywords of the reverse keyword group belong to the identification content to be filtered, the position of the N reverse keywords in the identification content is equal to the appointed position of the N reverse keywords of the reverse keyword group in the identification content, and the fourth filtering result is correct;
when all N reverse keywords in any reverse keyword group meet the following conditions: the N-th reverse keyword of the reverse keyword group does not belong to the identification content to be filtered, or the position of the N-th reverse keyword in the identification content is not equal to the appointed position of the N-th reverse keyword of the reverse keyword group in the identification content, and the fourth filtering result is suspected.
4. The apparatus for automatically filtering map notes and points of interest using a computer of claim 3, said apparatus further comprising:
the identification module is used for identifying by a manual filtering method to obtain an identification result under the condition that the filtering result is suspected;
and the storage module is used for storing the identification result into the white list library under the condition that the identification result is correct.
5. An electronic device comprising a memory, a processor, the memory having stored thereon a computer program executable on the processor, characterized in that the processor implements the method of claim 1 or 2 when executing the computer program.
6. A computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of claim 1 or 2.
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