TWI816141B - System and method for quickly searching for default lists in documents - Google Patents

Abstract

The system for quickly searching for a preset list in a file of the present invention is used to find the blacklist database name data that may be included in a search file with a plurality of consecutive words to be searched; the processing module first converts the blacklist data All the words in the name data in the database are built into a blacklist word list; then the consecutive plural words to be found in the file to be searched are read, and all the words in the blacklist word list that match one of the words to be searched are found and built as Target word list, then calculate the number of words belonging to the same name data in the target word list as the number of hit words, compare the number of hit words with the number of words of the name data, if the difference is within a hit range, it is determined that the name data is hit , to achieve the purpose of finding information with unspecified names in the files to be searched.

Description

System and method for quickly searching for default lists in documents

A search system and method, especially a system and method for quickly searching for a default list in a document.

In today's world of globalization, financial institutions around the world often have a certain degree of contact with each other. In order to facilitate communication, the message system is an important way to transmit information between financial institutions. In addition to the standard format of a message, there are no special restrictions on the main text of a message. Its narrative method, word length, etc. are different. One of the main keys is that the main text may appear to have a bad credit record or have had a bad credit record. Names of people, companies, or institutions that appear in bad news.

Financial institutions generally use global blacklist databases for verification and establish retrieval systems to search for personal information in the blacklist database when necessary. Generally speaking, the blacklist database is a relational database. When the user inputs the target name string to be searched into the retrieval system, the retrieval system will accurately compare the target name string with the list in the blacklist database. Compare and find the name field content that exactly matches the target name string, and after finding the matching field content, read and output the relevant information of the field for the user to browse.

However, this search system requires the user to input a name to be searched and perform precise comparison, and can only retrieve content that completely matches the entered name to be searched. Since the retrieval system sequentially compares the input text with the information in the blacklist database for retrieval, when a name that may be on the blacklist exists in an entire paragraph of unspecified text, the entire paragraph of text is entered for comparison in the retrieval system. The pair is meaningless because the retrieval system cannot detect or extract part of the text that may be the target name in the entire text. When a financial institution receives a message, it is difficult to directly determine where a person's name, company number, or the name of an institution appears in the main message because the main text in the message is continuous and the content has no specific format. Therefore, it cannot be used. General search systems perform blacklist name searches.

In addition, not only are these retrieval systems unable to automatically extract names hidden in the entire text, but the name of the same person, company, bank, or institution may have multiple forms, such as surnames, prefixes, titles, etc. For example, the name "Wang Xiaoming" may appear in different forms in a message such as "Xiaoming, Wang", "Mr. Wang Xiaoming", etc. In addition, it is possible to find multiple words that may be names from a random message and then re- Further difficulty in conducting blacklist database searches. Therefore, there is still room for improvement in the existing retrieval system.

In view of the fact that the existing blacklist database retrieval system cannot efficiently perform a list search on the entire document to find the target name, the present invention provides a method and system for quickly searching for a preset list in a document. The method includes the following steps: Read a blacklist database. The blacklist database contains plural record numbers, plural name data sorted according to each record number, and plural numeric data. Each of the name data includes plural single characters, and each of the word data records contains a plurality of characters. The number of characters in the name data; Create a blacklist word list based on the blacklist database. The blacklist word list includes each word in the name data and the record number corresponding to the name data to which each word belongs; Receive a file to be searched, and read a group of consecutive plural words to be searched in the file to be searched; Based on the group of consecutive plural words to be searched compared to the blacklist word list, at least one word that is the same as any word to be searched and at least one record number corresponding to the at least one word is established as a target word list; Calculate the number of words corresponding to the same record number in the target word list, and record the number as the number of at least one hit word corresponding to the at least one record number; Compare the at least one hit word count with the word count data corresponding to the at least one record number, and determine whether the difference between the at least one hit word count and the at least one word count data is within a hit range; If the difference between one of the hit word numbers and the corresponding word number data is within the hit range, the name data is a hit name data; If not, the name data corresponding to the record number is not the hit name data; Complete the comparison of the set of words to be found.

In addition, the present invention also provides a system for quickly searching for a default list in a file, including: A processing module connects to the blacklist database; A storage module connected to the processing module; wherein the processing module creates a blacklist word list based on the blacklist database, and stores the blacklist word list in the storage module; the blacklist word list includes Each word in the name data, and the record number corresponding to the name data to which each word belongs; The processing module receives a file to be searched, stores the file to be searched in the storage module, and reads a group of consecutive plural words to be searched in the file to be searched; The processing module compares the blacklist word list according to the group of consecutive plural words to be searched, and establishes at least one word that is the same as any word to be searched and at least one record number corresponding to the at least one word as a target word. list, and store the target word list in the storage module; The processing module calculates the number of words corresponding to the same record number in the target word list, and records the number as the number of at least one hit word corresponding to the at least one record number; The processing module compares the at least one hit word count with the word count data corresponding to the at least one record number, and determines whether the difference between the at least one hit word count and the at least one word count data is within a hit range; If the difference between one of the hit word numbers and the corresponding word number data is within the hit range, the processing module determines that the name data is a hit name data; If not, the processing module determines that the name data corresponding to the record number is not a hit name data; Complete the comparison of the set of words to be found.

The method for searching the default list of the present invention first constructs all the words of all the name data in the blacklist database into the blacklist word list, and records the number of words contained in the name data to which each word belongs. When the file to be searched is received, a group of consecutive plural words to be searched are read, and the blacklist word list is also searched based on the words to be searched, and the same words, including those that are repeated in the blacklist word list, are All words corresponding to different record numbers are created as a target word list, and then the number of words in the target word list corresponding to the same record number, that is, the same name data, is calculated, and the number of hit words is corresponding to each record number record. in the target word list. Finally, compare the number of hit words for each record number in the target word list with the number of words in the blacklist database. If the difference between the two is within a hit range, it means that there are multiple words in the plural words to be searched. The single word is the same as the single word of a name data. There is a high probability that the plural text to be searched contains the name data. Therefore, the name data is judged to be the hit name data.

For example, the name in the blacklist database is "Wang Xiaoming", the number of characters is 3, and the corresponding character number data is "3"; the plural word to be searched read from the file to be searched is "Mr. Wang Xiaoming" "Ming", after the above search method, it will be judged that the number of hit words in the plural word to be searched is 3, and the difference between the number of hit words and the word number data is 0, so the name data "Wang Xiaoming" is judged to be the hit name data.

The method and system of the present invention decompose all the name data in the blacklist database into a list of blacklist words, compare the plural words to be found in the text to be found, and judge the words based on the number of hits. Whether the plural text to be searched for may contain a name data. Since this search method does not limit the order of the words in the plural word to be searched or the name data in the blacklist database, it does not matter whether the order of the words in the name data is the same as the order of the name words contained in the plural word to be searched, or whether there is Whether redundant words are inserted or not, the names included in them can all be found, which solves the problem that the conventional blacklist database search system cannot find the name data in the default list in the entire document.

The technical means adopted by the present invention to achieve the intended invention purpose will be further described below with reference to the drawings and embodiments of the present invention.

Referring to Figures 1 and 2, the system for quickly searching for a default list in a document of the present invention includes a processing module 10 and a storage module 20. The processing module 10 is connected to a blacklist database 30. The processing module 10 receives a file to be searched, and executes the method of quickly searching the preset list in the file according to the present invention. The storage module 20 is connected to the processing module 10 and is used to store or temporarily store the file to be found, the blacklist word list and the target word list. The processing module 10 is, for example, the main processing element of an electronic computer device such as a server or a personal computer; the storage module 20 is a storage device, such as a traditional hard disk (HDD), a solid state disk (SSD), etc. Preferably, the processing module 10 is a local storage device; the blacklist database 30 is, for example, established on a cloud server for the management unit to update at any time, and the processing module 10 passes The Internet connects to and reads the blacklist database 30, and accordingly creates the blacklist word list, which is stored in the local storage module 20.

The document to be searched is, for example, a message received by a banking unit or financial management unit through the Internet and sent by other relevant units, which contains content text of indefinite length and no specific specifications. When the processing module 10 receives the file to be found, it is temporarily stored in the storage module 20 .

The method of quickly searching for a preset list in a file according to the present invention includes the following steps: The processing module 10 reads a blacklist database 30. The blacklist database 30 includes plural record numbers, plural name data and plural numeric data sorted according to the record numbers (S101); wherein, each name data includes For plural words, each character number data records the number of words in each name data; The processing module 10 creates a blacklist word list based on the blacklist database 30 (S102); the blacklist word list includes each word in the name data and the record number corresponding to the name data to which the word belongs; The processing module 10 receives a file to be searched, and reads a group of consecutive plural words to be searched in the file to be searched (S103); in other words, the file to be searched contains a plurality of consecutive original words, and the group of consecutive plural words is A word to be searched is a word set, which is a part of the continuous original words in the file to be searched. In the embodiment of the present invention, the processing module 10 reads out the words from the file to be searched based on the number of words in a single comparison. The number of words in the group of consecutive plural words to be searched for is equal to the number of words in the single comparison, and the number of words in the single comparison is a preset value; The processing module 10 compares each word to be searched with the blacklist word list, and creates at least one word that is the same as any word to be searched and at least one record number corresponding to the at least one word as a target word list (S104) ;The target word list is stored in the storage module 20; The processing module 10 calculates the number of words corresponding to the same record number in the target word list, and records the number as the number of at least one hit word corresponding to the at least one record number (S105); The processing module 10 compares the at least one hit word count with the word count data corresponding to the at least one record number, and determines whether the difference between the at least one hit word count and the at least one word count data is within a hit range (S106 ); the hit range is a user-default value. The difference between the hit word count and the word count data within the hit range means that the difference is smaller than the hit range; If the difference between one of the hit word numbers and the corresponding word number data is within the hit range, the processing module 10 determines that the name data is a hit name data (S107); If not, the processing module 10 determines that the name data corresponding to the record number is not a hit name data; Complete the comparison of the group of words to be found (S108).

Please refer to FIG. 3 . In one embodiment of the present invention, the words in the blacklist word list are sorted according to the value of each word, so that the same words are arranged together. Among them, in the step of establishing the blacklist word list (S102), the following sub-steps can be performed: The processing module 10 sequentially reads each word in each name data according to the record number in the blacklist database 30, and temporarily stores it as a full word list (S1021); each word in the full word list is based on Arrange the order of the words in each record number and name data; The processing module 10 rearranges each word in the full word list according to the value of the word and stores it in the blacklist word list (S1022).

Since the blacklist word list of the present invention has been stored in the storage module 20, when the processing module 10 compares the word to be found with the words in the blacklist word list, it can be directly read by the proximal storage module 20. There is no need to access the remote blacklist database 30 through the Internet, thus increasing the speed of search and comparison by the processing module 10; in addition, the processing module 10 pairs the word to be searched in the blacklist word list The words in the blacklist are compared one-to-one, and the blacklist word list has been arranged according to the value of each word. When the processing module 10 finds a matching word, it can find other matching words at a similar storage address in the storage module 20 words to further improve the efficiency of search and comparison; therefore, compared with inputting name strings to conduct complex cross-comparison of name data strings in the blacklist database, the present invention can find possible names in the entire document to be searched. The target name will have a clear processing speed advantage.

In an embodiment of the present invention, when the processing module 10 receives a file to be searched, it first creates a search list and stores it in the storage module 20. The search list includes consecutive files in the file to be searched. The plural group of words to be searched for contains all the words to be searched for in the file to be searched. After establishing the search list, the processing module 10 first performs the comparison of steps S104 to S107 from the first group of words to be searched. After the comparison is completed, it moves to the next group of words in the list to be searched. Comparison is performed until the comparison of each group of words to be found in the list to be found is completed.

Please refer to Figure 4. Preferably, the to-be-searched list is established according to the following sub-steps: The processing module 10 starts from the first word to be found in the file to be found, reads a continuous single comparison of a number of words to be found, and stores them in the to-be-searched list (S401); The processing module 10 starts from the second word to be searched among the plural words to be searched read in the previous step, reads the continuous single comparison number of words to be searched, and stores them in the search list ( S402); The processing module 10 repeats the previous step until the last word of the plurality of words to be searched is the last word to be searched in the file to be searched (S403); Complete the creation of the to-be-found list.

That is to say, the way to create the search list is to start from the starting word, read and store the number of words to be searched for in a single comparison, then move one word, and start reading from the second word to be searched in the file. Fetch and store the number of words to be searched for in a single comparison, and read and store them in translation again until the end word in the entire file to be searched is read and stored. In this way, the search list includes all consecutive words to be searched from the starting word to the end word in the file to be searched. The number of single comparisons determines the number of words to be found that the processing module 10 compares in a hit comparison, which can be based on the average number of words and the highest value of the name data in the blacklist database 30 Or based on rules of thumb. For example, if the number of single comparisons is 5, it means that each group of words to be searched for contains 5 consecutive words to be searched for.

When reading a number of consecutive words to be searched for in a single comparison, the processing module 10 further determines whether the word to be searched contains two consecutive and identical words to be searched; if so, the processing module 10 ignores the word to be searched. One of the consecutive and identical words to be found, and the next word to be found is updated to the group of words to be found.

That is to say, when establishing the search list, when one of the groups of words to be searched contains consecutive and repeated words to be searched, one of the consecutive and repeated words to be searched is ignored, and the next word to be searched is further read. Search words to avoid repeated comparisons caused by duplicate words to be found in the same set of words to be searched.

In another embodiment of the present invention, before establishing the blacklist word list, each name data is compared against a common word list containing a plurality of commonly used words, and the common words contained in each name data are removed. Vocabulary, the blacklist word list is created based on the name data from which the common vocabulary has been removed.

In this embodiment, these commonly used words are, for example, "company", "limited company", and "foundation" in Chinese; "COMPANY LIMITED", "COMPANY", "LIMITED", "IMPORT EXPORT CORP", " IMPORT EXPORT CORPORATION", "IMPORT AND EXPORT CORPORATION", etc. Since these common words in the blacklist database 30 are noisy words that do not have the representative meaning of names, when it is determined that the name data contains these common words, these common words will be removed first to make the blacklist The number of words in the word list is more streamlined, improving comparison efficiency.

The method of quickly searching for a default list in a document according to the present invention will be described below with an example.

In this example, the record number, name data and word count data contained in the blacklist database 30 are as shown in Table 1 below. record number Name information word count data R1 Doosan Heavy Industries Construction Company Limited C6 R2 Korea Heavy Industries Construction Company Limited C6 R3 Giad Heavy Industries Complex C4 R4 Esfahan Chemical Industries C3 R5 Canadian Spooner Industries Corporation C4 R6 Khartoum Industrial Complex Giad C4 R7 Hadid Industrial Complex C3 R8 Shohadayeh Hadid Industries C3 R9 Nuclear Fuel Complex C3 R10 Kim Chaek Iron And Steel Complex C6 R11 Namhung Chemical Union Complex C4 R12 Giad Cars Heavy Trucks Company C5 R13 Heavy Electrical Complex Private Limited C5 R14 Danbel Industries Incorporated C3 R15 Pakistan Aeronautical Complex C3 R16 Heavy Mechanical Complex C3 R17 Giad Metal Industries C3 R18 Power Construction Complex of Unified Energy System of Russia Joint Stock Company C12 R19 Heavy Water Board C3 R20 Bharat Heavy Electricals Limited C4 R21 Heavy Vehicles Design and Engeeniring Private Joint Stock Company C9 R22 Iran Shipbuilding and Offshore Industries Complex Company C7 R23 Oil Industries Management Services Private Joint Stock Company C8 R24 Moscow Design Industrial Complex Universal Federal State Unitary Enterprise C9 R25 Oil Industries Engineering Construction Public Joint Stock Company C8 R26 Farasakht Industries C2 R27 Iran Aircraft Manufacturing Industries C4 R28 Sairan Telecommuncation Industries Private Joint Stock Company C7 R29 Shiraz Electronics Industries C3 R30 Thong Guan Industries Berhad C4 Table I

Among them, C1 indicates that the count value is 1, C2 indicates that the count value is 2, and so on, and Cn indicates that the count value is n. Therefore, the word count data is C1, which means that the name data contains 1 word, C2 means that the name data contains 2 words, and so on, Cn means that the name data contains n words.

The blacklist word list established according to step S102 and its sub-steps is shown in Table 2 below: single word record number AERONAUTICAL R15 AIRCRAFT R27 AND R10 AND R21 AND R22 BERHAD R30 BHARAT R20 BOARD R19 CANADIAN R5 CARS R12 CHAEK R10 CHEMICAL R4 CHEMICAL R11 COMPANY R1 COMPANY R2 COMPANY R12 COMPANY R18 COMPANY R21 COMPANY R22 COMPANY R23 COMPANY R25 COMPANY R28 COMPLEX R3 COMPLEX R6 COMPLEX R7 COMPLEX R9 COMPLEX R10 COMPLEX R11 COMPLEX R13 COMPLEX R15 COMPLEX R16 COMPLEX R18 COMPLEX R22 COMPLEX R24 CONSTRUCTION R1 CONSTRUCTION R2 CONSTRUCTION R18 CONSTRUCTION R25 CORPORATION R5 DANBEL R14 DESIGN R21 DESIGN R24 DOOSAN R1 ELECTRICAL R13 ELECTRICALS R20 ELECTRONICS R29 能源 R18 ENGEENIRING R21 ENGINEERING R25 ENTERPRISE R24 ESFAHAN R4 FARASAKHT R26 FEDERAL R24 FUEL R9 GIAD R3 GIAD R6 GIAD R12 GIAD R17 GUAN R30 HADID R7 HADID R8 HEAVY R1 HEAVY R2 HEAVY R3 HEAVY R12 HEAVY R13 HEAVY R16 HEAVY R19 HEAVY R20 HEAVY R21 INCORPORATED R14 INDUSTRIAL R6 INDUSTRIAL R7 INDUSTRIAL R24 INDUSTRIES R1 INDUSTRIES R2 INDUSTRIES R3 INDUSTRIES R4 INDUSTRIES R5 INDUSTRIES R8 INDUSTRIES R14 INDUSTRIES R17 INDUSTRIES R22 INDUSTRIES R23 INDUSTRIES R25 INDUSTRIES R26 INDUSTRIES R27 INDUSTRIES R28 INDUSTRIES R29 INDUSTRIES R30 IRAN R22 IRAN R27 IRON R10 JOINT R18 JOINT R21 JOINT R23 JOINT R25 JOINT R28 KHARTOUM R6 KIM R10 KOREA R2 LIMITED R1 LIMITED R2 LIMITED R13 LIMITED R20 MANAGEMENT R23 MANUFACTURING R27 MECHANICAL R16 METAL R17 MOSCOW R24 NAMHUNG R11 NUCLEAR R9 OF R18 OF R18 OFFSHORE R22 OIL R23 OIL R25 PAKISTAN R15 POWER R18 PRIVATE R13 PRIVATE R21 PRIVATE R23 PRIVATE R28 PUBLIC R25 RUSSIA R18 SAIRAN R28 SERVICES R23 SHIPBUILDING R22 SHIRAZ R29 SHOHADAYEH R8 SPOONER R5 STATE R24 STEEL R10 STOCK R18 STOCK R21 STOCK R23 STOCK R25 STOCK R28 SYSTEM R18 TELECOMMUNCATION R28 THONG R30 TRUCKS R12 UNIFIED R18 UNION R11 UNITARY R24 UNIVERSAL R24 VEHICLES R21 WATER R19 Table II

In this example, the content of the file to be found is as follows: "REGARDING OUR ACKNOWLEDGEMENT CONCERNING GIAD HEAVY INDUSTRIES COMPLEX DATED DD 20200929 WE HAVE TODAY SENT A SECOND REMINDER ON YOUR BEHALF. FOR ANY FUTURE CORRESPONDENCE RELATED TO THIS CASE PLEASE QUOTE OUR ENQUIRY REFERENCE USP200928-000830. REGARDS CLIENT SERVICES"

The search list established according to step S401 is shown in Table 3 below. Among them, the number of words in a single comparison is exemplarily set to 5, so each group of words to be searched contains 5 consecutive words to be searched. Table 3 lists a total of 32 groups of words to be searched (WL1~WL32). : to be found list WL1 REGARDING,OUR,ACKNOWLEDGEMENT,CONCERNING,GIAD WL2 OUR,ACKNOWLEDGEMENT,CONCERNING,GIAD,HEAVY WL3 ACKNOWLEDGEMENT,CONCERNING,GIAD,HEAVY,INDUSTRIES WL4 CONCERNING,GIAD,HEAVY,INDUSTRIES,COMPLEX WL5 GIAD,HEAVY,INDUSTRIES,COMPLEX,DATED WL6 HEAVY,INDUSTRIES,COMPLEX,DATED,DD WL7 INDUSTRIES,COMPLEX,DATED,DD,WE WL8 COMPLEX,DATED,DD,WE,HAVE WL9 DATED,DD,WE,HAVE,TODAY WL10 DD,WE,HAVE,TODAY,SENT WL11 WE,HAVE,TODAY,SENT,SECOND WL12 HAVE,TODAY,SENT,SECOND,REMINDER WL13 TODAY,SENT,SECOND,REMINDER,ON WL14 SENT,SECOND,REMINDER,ON,YOUR WL15 SECOND,REMINDER,ON,YOUR,BEHALF WL16 REMINDER,ON,YOUR,BEHALF,FOR WL17 ON,YOUR,BEHALF,FOR,ANY WL18 YOUR,BEHALF,FOR,ANY,FUTURE WL19 BEHALF,FOR,ANY,FUTURE,CORRESPONDENCE WL20 FOR,ANY,FUTURE,CORRESPONDENCE,RELATED WL21 ANY,FUTURE,CORRESPONDENCE,RELATED,TO WL22 FUTURE,CORRESPONDENCE,RELATED,TO,THIS WL23 CORRESPONDENCE,RELATED,TO,THIS,CASE WL24 RELATED,TO,THIS,CASE,PLEASE WL25 TO,THIS,CASE,PLEASE,QUOTE WL26 THIS,CASE,PLEASE,QUOTE,OUR WL27 CASE,PLEASE,QUOTE,OUR,ENQUIRY WL28 PLEASE,QUOTE,OUR,ENQUIRY,REFERENCE WL29 QUOTE,OUR,ENQUIRY,REFERENCE,USP WL30 OUR,ENQUIRY,REFERENCE,USP,REGARDS WL31 ENQUIRY,REFERENCE,USP,REGARDS,CLIENT WL32 REFERENCE,USP,REGARDS,CLIENT,SERVICES Table 3

In step S104, the processing module 10 compares the words to be searched in each group of words to be searched with the blacklist word list (Table 2), and compares any word to be searched that is the same as a word in the blacklist word list. And the record numbers corresponding to the words in the blacklist word list are established as the target word list. For example, the target word list established after comparing the first group of words to be found (WL1) is as shown in Table 4 below: record number without REGARDING without OUR without ACKNOWLEDGEMENT without CONCERNING R3 GIAD R6 GIAD R12 GIAD R17 GIAD Table 4

In step S105, the number of words corresponding to the same record number in the target word list is calculated, and the number is recorded as the number of hit words corresponding to the record number. For example, in the target word list, the word corresponding to the record number "R3" is "GIAD", that is, there is only one word corresponding to the record number "R3", so the hit word count record is C1. In this step, words to be found that do not match the words in the blacklist word list can be removed, such as "REGARDING", "OUR", "ACKNOWLEDGEMENT", "CONCERNING" and other words. Further record the number of hit words in the target word list, as shown in Table 5 below: record number hit word hit word count R3 GIAD C1 R6 GIAD C1 R12 GIAD C1 R17 GIAD C1 Table 5

Next, in steps S106 to S107, it is determined whether the group of words to be searched includes a group of hit name data, where the hit range is exemplarily set to "1". After determining the number of hit words corresponding to each record number in the previous step (S105), further query the word count data corresponding to each record number according to Table 1; then, determine the "number of hit words" corresponding to each record number and Is the difference in "word count data" less than the hit range? If so, it means that the name data corresponding to the record number is the hit name data, and the group of words to be searched includes the name data in the blacklist database. The comparison results are shown in Table 6 below: record number hit word count word count information Comparison difference Is it a hit? R3 C1 C4 3 no R6 C1 C4 3 no R12 C1 C5 4 no R17 C1 C3 2 no Table 6

According to the "hit or not" column in Table 6, the method of the present invention can determine that the first group of words to be searched (WL1) in the file to be searched does not contain any name data in the blacklist database 30. Therefore, the first group of words to be searched (WL1) does not contain hit name data.

After the comparison is completed on the first group of words to be found (WL1), the processing module 10 sequentially performs the comparison on the second group, the third group... of the words to be found (WL2, WL3,...) in the list to be found. Compare until the comparison of each set of words to be found is completed.

The following uses the fourth group of words to be searched for (WL4) as an example to illustrate the comparison method. The content of the fourth group of words to be searched for (WL4) is "CONCERNING, GIAD, HEAVY, INDUSTRIES, COMPLEX". In step S104, the target word list established based on the fourth group of words to be found (WL4) is as follows: record number without CONCERNING R3 GIAD R6 GIAD R12 GIAD R17 GIAD R1 HEAVY R2 HEAVY R3 HEAVY R12 HEAVY R13 HEAVY R16 HEAVY R19 HEAVY R20 HEAVY R21 HEAVY R1 INDUSTRIES R2 INDUSTRIES R3 INDUSTRIES R4 INDUSTRIES R5 INDUSTRIES R8 INDUSTRIES R14 INDUSTRIES R17 INDUSTRIES R22 INDUSTRIES R23 INDUSTRIES R25 INDUSTRIES R26 INDUSTRIES R27 INDUSTRIES R28 INDUSTRIES R29 INDUSTRIES R30 INDUSTRIES R3 COMPLEX R6 COMPLEX R7 COMPLEX R9 COMPLEX R10 COMPLEX R11 COMPLEX R13 COMPLEX R15 COMPLEX R16 COMPLEX R18 COMPLEX R22 COMPLEX R24 COMPLEX

According to step S105, the number of words corresponding to the same record number in the target word list is calculated. For example, in the target word list, the words corresponding to the record number "R2" are "HEAVY" and "INDUSTRIES", that is, there are 2 words corresponding to the record number "R2", so the hit word count record is C2; corresponding The words of the record number "R3" are "GIAD", "HEAVY", "INDUSTRIES" and "COMPLEX", that is, there are 4 words corresponding to the record number "R3", so the number of hit words is recorded as C4. The target word list recording the hit word count data is as follows: record number hit word hit word count R1 HEAVY,INDUSTRIES C2 R2 HEAVY,INDUSTRIES C2 R3 GIAD, HEAVY, INDUSTRIES, COMPLEX C4 R4 INDUSTRIES C1 R5 INDUSTRIES C1 R6 GIAD, COMPLEX C2 R7 COMPLEX C1 R8 INDUSTRIES C1 R9 COMPLEX C1 R10 COMPLEX C1 R11 COMPLEX C1 R12 GIAD,HEAVY C2 R13 HEAVY,COMPLEX C2 R14 INDUSTRIES C1 R15 COMPLEX C1 R16 HEAVY, COMPLEX C2 R17 GIAD,INDUSTRIES C2 R18 COMPLEX C1 R19 HEAVY C1 R20 HEAVY C1 R21 HEAVY C1 R22 INDUSTRIES,COMPLEX C2 R23 INDUSTRIES C1 R24 COMPLEX C1 R25 INDUSTRIES C1 R26 INDUSTRIES C1 R27 INDUSTRIES C1 R28 INDUSTRIES C1 R29 INDUSTRIES C1 R30 INDUSTRIES C1

In steps S106 to S107, it is determined whether the group of words to be searched includes a group of hit name data. Similarly, query the word count data corresponding to each record number in the target word list to determine whether the difference between the "hit word count" and the "word count data" corresponding to each record number is less than the hit range "1". If so, Then it is determined that the name data corresponding to the record number is the hit name data. The complete list of comparison results is shown in the table below: record number hit word count word count data Comparison difference Is it a hit? R1 C2 C6 4 no R2 C2 C6 4 no R3 C4 C4 0 yes R4 C1 C3 2 no R5 C1 C4 3 no R6 C2 C4 2 no R7 C1 C3 2 no R8 C1 C3 2 no R9 C1 C3 2 no R10 C1 C6 5 no R11 C1 C4 3 no R12 C2 C5 3 no R13 C2 C5 3 no R14 C1 C3 2 no R15 C1 C3 2 no R16 C2 C3 1 no R17 C2 C3 1 no R18 C1 C12 11 no R19 C1 C3 2 no R20 C1 C4 3 no R21 C1 C9 8 no R22 C1 C7 6 no R23 C1 C8 7 no R24 C1 C9 8 no R25 C1 C8 7 no R26 C1 C2 1 no R27 C1 C4 3 no R28 C1 C7 6 no R29 C1 C3 2 no R30 C1 C4 3 no

The content of the fourth group of words to be searched (WL4) is "CONCERNING, GIAD, HEAVY, INDUSTRIES, COMPLEX", that is, the 5 consecutive words to be searched starting from the 4th one in the file to be searched include a total of 4 The word to be searched is the same as the name data "GIAD HEAVY INDUSTRIES COMPLEX" with record number R3, and the difference between the hit number C4 and the word number data C4 corresponding to R3 is 0, which is less than the hit range 1, so it is judged that R3 corresponds The name data is the hit name data.

In summary, the method and system for quickly searching for a preset list in a file of the present invention can capture consecutive plural words of a specific length to be searched starting from the starting word of the file in a file to be searched, and scan them in sequence. In the entire document, each word to be searched is compared with the pre-established blacklist word list in order. After the comparison is completed, the number of hit words corresponding to the same record number is calculated, and then the number of hit words is compared with the number of words in the name data. Compare the data and get the result of whether it is hit or not. The process of the method is to first establish the blacklist word list arranged according to the word value in the name data. When actually comparing to determine whether it is a hit name data, it only needs to compare whether the words are the same and simply compare the hit words. Numerical and word-count data, the execution burden is low and the speed is fast. And since the comparison of the words to be searched and the list of blacklisted words is a comparison of individual words, no matter whether the character arrangement of the hit names contained in each group of words to be searched is the same as the order of the words in the name data in the original blacklist database, It can find all the words to be searched that differ from the name data within a certain range, solving the problem of being unable to fuzzy compare the name data in the blacklist database with multiple consecutive unspecific words in the entire document.

The above descriptions are only embodiments of the present invention, and do not limit the present invention in any form. Although the present invention has been disclosed in the embodiments above, they are not used to limit the present invention. Any skilled person familiar with the art will not Without departing from the scope of the technical solution of the present invention, the technical content disclosed above can be used to make some changes or modifications to equivalent embodiments with equivalent changes. Any simple modifications, equivalent changes and modifications made to the above embodiments still fall within the scope of the technical solution of the present invention.

10: Processing module 20:Storage module 30: Blacklist database

Figure 1 is a judgment flow chart of the method of quickly searching for a preset list in a file according to the present invention. Figure 2 is a block diagram of a system for quickly searching for a preset list in a document according to the present invention. FIG. 3 is a partial judgment flow chart of an embodiment of a method for quickly searching for a preset list in a file according to the present invention. FIG. 4 is a partial judgment flow chart of an embodiment of a method for quickly searching for a preset list in a file according to the present invention.

Claims (14)

A method to quickly find the default list in a file includes the following steps: Read a blacklist database, the blacklist database contains plural record numbers, and plural name data and plural numeric data sorted according to each record number, wherein each name data contains plural single characters and each word number data record The number of words in each name data; Create a blacklist word list based on the blacklist database. The blacklist word list includes each word in the name data and the record number corresponding to the name data to which the word belongs; Receive a file to be searched, and read a group of consecutive plural words to be searched in the file to be searched; Based on the group of consecutive plural words to be searched compared to the blacklist word list, at least one word that is the same as any word to be searched and at least one record number corresponding to the at least one word is established as a target word list; Calculate the number of words corresponding to the same record number in the target word list, and record the number as the number of at least one hit word corresponding to the at least one record number; Compare the at least one hit word count with the word count data corresponding to the at least one record number, and determine whether the difference between the at least one hit word count and the at least one word count data is within a hit range; If the difference between one of the hit word numbers and the corresponding word number data is within the hit range, the name data is a hit name data; If not, the name data corresponding to the record number is not the hit name data; Complete the comparison of the set of words to be found. A method to quickly search for a default list in a document as described in request 1, where: The words in the blacklist word list are sorted according to the value of the words, and the same words are arranged together. A method for quickly searching a preset list in a file as described in request item 1, wherein when receiving the file to be searched, a list to be searched for is first created, and the list to be searched for includes a plurality of consecutive groups of files in the file to be searched. plural words to be found, and when the comparison of a group of words to be found is completed, the system moves to the next group of words to be found in the list to be found, and the comparison is performed again until each group of words to be found in the list is completed. Find word comparisons. The method of quickly searching for a preset list in a file is as described in request 3, wherein the list to be searched is created according to the following sub-steps: Starting from the first word to be found in the file to be found, read a number of consecutive single comparison words to be found, and store them in the to-be-searched list; Starting from the second word to be found among the plural words to be found read in the previous step, read the number of words to be found for a continuous single comparison and store them in the to-be-searched list; Repeat the previous step until the last word of the plurality of words to be searched is the last word to be searched in the file to be searched. A method for quickly searching a preset list in a file as described in request 4, wherein when reading a number of consecutive words to be searched for in a single comparison, it is also determined whether the plurality of words to be searched include consecutive and identical words. The two words to be searched for; If there is, then ignore one of the consecutive and identical words to be found, and update and read the next word to be found of the consecutive plural words to be found in the file to be found, and update the next word to be found to the The set of search words in the search list. The method of quickly searching for a default list in a document is as described in request 1, wherein the step of creating the blacklist word list includes the following sub-steps: Read each word in the name data sequentially according to the record number, and temporarily save it as a full word list; Each word in the full word list is rearranged according to the value of the word and stored as the blacklist word list. A method for quickly searching a default list in a document as described in request 6, wherein when creating the blacklist word list, each name data is first compared against a common word list containing a plurality of commonly used words. Common words contained in each name data are removed, and then the blacklist database is created based on the name data that does not contain common words. A system for quickly searching for a default list in a document, connected to a blacklist database. The blacklist database contains plural name data sorted according to plural record numbers, and plural numeric data corresponding to each name data, each of which The name data contains plural characters, and each word number data records the number of single characters contained in each name data; the system for quickly searching the default list in the document includes: A processing module connects to the blacklist database; A storage module connected to the processing module; wherein the processing module creates a blacklist word list based on the blacklist database, and stores the blacklist word list in the storage module; the blacklist word list includes Each word in the name data, and the record number corresponding to the name data to which each word belongs; The processing module receives a file to be searched, stores the file to be searched in the storage module, and reads a group of consecutive plural words to be searched in the file to be searched; The processing module compares the blacklist word list according to the group of consecutive plural words to be searched, and establishes at least one word that is the same as any word to be searched and at least one record number corresponding to the at least one word as a target word. list, and store the target word list in the storage module; The processing module calculates the number of words corresponding to the same record number in the target word list, and records the number as the number of at least one hit word corresponding to the at least one record number; The processing module compares the at least one hit word count with the word count data corresponding to the at least one record number, and determines whether the difference between the at least one hit word count and the at least one word count data is within a hit range; If the difference between one of the hit word numbers and the corresponding word number data is within the hit range, the processing module determines that the name data is a hit name data; If not, the processing module determines that the name data corresponding to the record number is not a hit name data; Complete the comparison of the set of words to be found. A system for quickly searching a preset list in a document as described in request 8, wherein the words in the blacklist word list are sorted according to the value of each word, and the same words are arranged together. A system for quickly searching a preset list in a file as described in request item 8, wherein when the processing module receives the file to be searched, it first creates a list to be searched, and the list to be searched includes a plurality of groups of the files to be searched. Continuous plural words to be found in the file, and when the comparison of a group of words to be found is completed, the system moves to the next group of words to be found in the list to be found, and the comparison is performed again until the list to be found is completed. Comparison of each group of words to be found. A system for quickly searching for a preset list in a file as described in claim 10, wherein when the processing module creates the search list, it first starts with the first word to be searched in the file to be searched, and reads Continuous single comparison of a number of words to be found and stored in the to-be-searched list; Starting from the second word to be found among the plural words to be found read in the previous step, read the number of words to be found for a continuous single comparison and store them in the to-be-searched list; Repeat the previous step until the last word of the plurality of words to be searched is the last word to be searched in the file to be searched. A system for quickly searching for a preset list in a file as described in request 11, wherein when reading a continuous single comparison of a number of words to be searched for, the processing module also determines whether the plurality of words to be searched for contains There are two consecutive and identical words to be searched; If so, the processing module ignores one of the consecutive and identical words to be searched, and updates and reads the next word to be searched for the plurality of consecutive words to be searched in the file to be searched, and replaces the next word to be searched. The words are updated to the group of words to be found in the list to be found. A system for quickly searching for a default list in a document as described in request item 8, wherein when the processing module creates the blacklist word list, the processing module first reads the names in sequence according to the record numbers. The words in the data are temporarily stored in the storage module as a full word list; then each word in the full word list is rearranged according to the word value and stored in the storage module as a blacklist single word list. A system for quickly searching for a default list in a document as described in request 8, wherein when creating the blacklist word list, the processing module first compares each word according to a common word list containing a plurality of common words. From the name data, common words contained in the name data are removed, and then the blacklist database is created based on the name data that does not contain common words.

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