SMS interception method and device, storage medium and electronic device

Abstract

The present application provides a method and device for intercepting short messages, a storage medium and an electronic device. If the sending object is not included in the preset whitelist and the preset blacklist, the short message text is segmented, and each sentence after the segmentation is segmented to obtain multiple words. For each word, if there is a junk word matching the word in the junk word library, the word is determined to be a junk word; for each sentence, if the ratio between the total number of characters of the junk words included in the sentence and the total number of characters of the sentence is greater than a preset first threshold, the sentence is determined to be a junk sentence; if the ratio between the total number of characters of the junk sentences included in the short message text and the total number of characters of each sentence included in the short message text is greater than a preset second threshold, the short message text is determined to be a junk short message, and the short message text is stored in a preset junk mailbox. The judgment and interception of junk short messages outside the blacklist are realized without manual judgment, thereby improving the user experience.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a text message interception method and device, a storage medium and an electronic device. Background Art

[0002] With the development of mobile communication technology, smart terminals have been widely used. Users use smart terminals to communicate, such as making calls, sending text messages or voice communications. While enjoying the convenience brought by mobile communication technology, users are also troubled by spam text messages. Therefore, how to intercept spam text messages has become an important issue.

[0003] Existing SMS interception solutions all intercept spam messages based on blacklists. Users are required to edit the blacklist before the next blacklisted message is intercepted. This will result in manual judgment required for the first interception of spam messages, affecting user experience. Summary of the invention

[0004] The present application provides a text message interception method and device, a storage medium and an electronic device, the purpose of which is to solve the problem that the current text message interception solution requires manual judgment for the first interception of spam text messages, which affects the user experience.

[0005] In order to achieve the above objectives, this application provides the following technical solutions:

[0006] A text message interception method, comprising:

[0007] Obtaining a text message and determining a recipient of the text message;

[0008] If the sending object is not included in the preset list, the SMS text is segmented to obtain multiple sentences included in the SMS text; the preset list includes a preset white list and a preset black list;

[0009] Perform word segmentation on each sentence to obtain multiple words included in each sentence;

[0010] For each word, if there is a junk word matching the word in the preset junk word library, the word is determined to be a junk word;

[0011] For each sentence, if the ratio between the total number of characters of the junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold, the sentence is determined to be a junk sentence;

[0012] If the ratio of the total number of characters in the junk sentences included in the SMS text to the total number of characters in each sentence included in the SMS text is greater than a preset second threshold, the SMS text is determined to be a junk SMS, and the SMS text is stored in a preset junk mailbox.

[0013] The above method may optionally further include:

[0014] If the sending object is included in the preset white list, the SMS text is sent to the SMS receiving box of the terminal device.

[0015] The above method may optionally further include:

[0016] If the sending object is included in the preset blacklist, the text message is determined to be a spam message, and the text message is stored in a preset spam mailbox.

[0017] The above method may optionally further include:

[0018] If the ratio between the total number of characters of the junk sentences included in the SMS text and the total number of characters of each sentence included in the SMS text is not greater than a preset second threshold, outputting a prompt message; the prompt message is used to prompt the user to judge whether the SMS text is a junk SMS;

[0019] Obtaining a judgment result of the user;

[0020] If the judgment result indicates that the SMS text is a spam SMS, the spam SMS is stored in a preset spam mailbox;

[0021] If the judgment result indicates that the SMS text is not a junk SMS, the SMS text is sent to the SMS receiving box of the terminal device.

[0022] In the above method, optionally, the segmentation processing of the SMS text to obtain multiple sentences included in the SMS text includes:

[0023] Determine each punctuation mark in the text of the SMS;

[0024] Convert the punctuation marks in the SMS text that are half-width symbols into full-width symbols to obtain a target SMS text;

[0025] The target SMS text is segmented based on each full-width symbol in the target SMS text to obtain a plurality of sentences included in the SMS text.

[0026] In the above method, optionally, each sentence is segmented to obtain multiple words included in each sentence, including:

[0027] For each sentence, taking the first character in the sentence as the first character, taking the first character as the starting position, and selecting characters corresponding to a preset character string length from the sentence as the first character string;

[0028] Determining whether there is a character string matching the first character string in a preset dictionary;

[0029] If there is a character string matching the first character string in the preset dictionary, the first character string is used as a word of the sentence, and the next character of the first character string in the sentence is used as a new first character, and based on the new first character, the step of taking the first character as the starting position and intercepting characters corresponding to the preset character string length from the sentence as the first character string is returned to be executed;

[0030] If there is no character string matching the first character string in the preset dictionary, the next character of the first character string in the sentence and the first character string are combined into a new first character string, and based on the new first character string, the step of determining whether there is a character string matching the first character string in the preset dictionary is returned to be executed until the word segmentation of the sentence is completed.

[0031] In the above method, optionally, each sentence is segmented to obtain multiple words included in each sentence, including:

[0032] For each sentence, taking the first character in the sentence as the second character, and forming a second character string with the second character and the character next to the second character in the sentence;

[0033] Determine whether the frequency of occurrence of the second string in each sentence included in the text message is greater than a preset frequency threshold; wherein the frequency of occurrence of the second string in each sentence included in the text message is used to characterize the ratio between the number of occurrences of the second string in the text message and the total number of comparisons, wherein the total number of comparisons is the total number of times the second string is compared with the text message;

[0034] If the frequency of occurrence of the second character string in each sentence included in the text of the short message is greater than a preset frequency threshold, the second character string is used as a word of the sentence, and the next character of the second character string in the sentence is used as a new second character, and based on the new second character, the step of forming a second character string with the second character and the next character of the second character in the sentence is returned to be executed;

[0035] If the frequency of occurrence of the second character string in each sentence included in the SMS text is not greater than a preset frequency threshold, the next character of the second character string in the sentence and the second character string are combined into a new second character string, and based on the new second character string, the step of determining whether the frequency of occurrence of the second character string in each sentence included in the SMS text is greater than a preset frequency threshold is returned to execute until the word segmentation of the sentence is completed.

[0036] A text message interception device, comprising:

[0037] A first acquisition unit, used to acquire a text message and determine a recipient of the text message;

[0038] A segmentation unit, for segmenting the text message to obtain a plurality of sentences included in the text message if the sending object is not included in a preset list; the preset list includes a preset white list and a preset black list;

[0039] A word segmentation unit is used to perform word segmentation processing on each sentence to obtain multiple words included in each sentence;

[0040] A first determination unit is used for determining, for each word, if there is a junk word matching the word in a preset junk word library, that the word is a junk word;

[0041] a second determination unit, configured to determine, for each sentence, if a ratio between the total number of characters of junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold, then determine that the sentence is a junk sentence;

[0042] The third determination unit is used to determine that the SMS text is a spam SMS and store the SMS text in a preset spam mailbox if the ratio between the total number of characters in the spam sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is greater than a preset second threshold.

[0043] A storage medium stores an instruction set, wherein the instruction set, when executed by a processor, implements the above-mentioned SMS interception method.

[0044] An electronic device, comprising:

[0045] A memory for storing at least one set of instructions;

[0046] The processor is used to execute the instruction set stored in the memory, and implement the above-mentioned SMS interception method by executing the instruction set.

[0047] A storage medium stores an instruction set, wherein the instruction set, when executed by a processor, implements the above-mentioned SMS interception method.

[0048] An electronic device, comprising:

[0049] A memory for storing at least one set of instructions;

[0050] The processor is used to execute the instruction set stored in the memory, and implement the above-mentioned SMS interception method by executing the instruction set.

[0051] Compared with the prior art, this application has the following advantages:

[0052] The present application provides a method and device for intercepting short messages, a storage medium and an electronic device, comprising: obtaining a short message text, and determining a sending object of the short message text; if the sending object is not included in a preset white list and a preset black list, segmenting the short message text to obtain a plurality of sentences included in the short message text, segmenting each sentence to obtain a plurality of words included in each sentence, and for each word, if there is a junk word matching the word in a preset junk word library, determining that the word is a junk word; for each sentence, if the ratio between the total number of characters of the junk words included in the sentence and the total number of characters of the sentence is greater than a preset first threshold, determining that the sentence is a junk sentence; if the ratio between the total number of characters of the junk sentences included in the short message text and the total number of characters of each sentence included in the short message text is greater than a preset second threshold, determining that the short message text is a junk short message, and storing the short message text in a preset junk mailbox. It can be seen that the present application scheme does not require manual judgment for SMS texts whose recipients are not included in the blacklist. Instead, it determines the spam words in the SMS texts, and based on the spam words, determines the spam sentences in the SMS texts, and then based on the spam sentences, determines whether the SMS texts are spam text messages, thereby improving ease of use and improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0054] Figure 1 A method flow chart of a text message interception method provided by this application;

[0055] Figure 2 A method flow chart of a segmented processing method provided in this application;

[0056] Figure 3 A method flow chart of a word segmentation processing method provided in this application;

[0057] Figure 4 A method flow chart of another word segmentation processing method provided by this application;

[0058] Figure 5 An example diagram of a method for intercepting text messages provided in this application;

[0059] Figure 6A schematic diagram of the structure of a text message interception device provided by this application;

[0060] Figure 7 A schematic diagram of the structure of an electronic device provided in this application. DETAILED DESCRIPTION

[0061] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0062] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0063] It should be noted that the concepts such as "first" and "second" mentioned in the present application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0064] It should be noted that the modifications of "one" and "plurality" mentioned in the disclosure of this application are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0065] The present application embodiment provides a method for intercepting short messages, which can be applied to a terminal device. The flowchart of the method for intercepting short messages is as follows: Figure 1 As shown, specifically including:

[0066] S101: Obtain a text message and determine a recipient of the text message.

[0067] In this embodiment, before the SMS text is sent to the SMS receiving box of the terminal device, the SMS text is intercepted and the SMS text is obtained. Specifically, the SMS text is obtained upstream through the built-in information transceiver module of the terminal device.

[0068] In this embodiment, after the SMS text is obtained, the sending object of the SMS text is determined, and the sending object of the SMS text is the sending user who sends the SMS text.

[0069] S102, determine whether the sending object is included in the preset whitelist, if so, execute S103, if not, execute S104.

[0070] In this embodiment, a whitelist is preset, and the preset whitelist includes at least one user list, and the text messages sent by the users corresponding to the preset whitelist can be directly stored in the text message inbox. Optionally, the user can edit the preset whitelist.

[0071] Determine whether the sending object is included in the preset whitelist. Specifically, compare the object identifier of the sending object with the user list in the preset whitelist to determine whether the sending object is included in the preset whitelist.

[0072] Among them, if there is a user list in the preset whitelist that matches the object identifier of the sending object, it is determined that the sending object is included in the preset whitelist. If there is no user list in the preset whitelist that matches the object identifier of the sending object, it is determined that the sending object is not included in the preset whitelist.

[0073] S103: Send the SMS text to the SMS receiving box of the terminal device.

[0074] In this implementation, if the recipient is included in the preset whitelist, it is determined that the SMS text is not a spam SMS, and the SMS text is sent to the terminal device.

[0075] In this embodiment, if the sending object is not included in the preset whitelist and the preset blacklist, the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is not greater than the preset second threshold, and the user's judgment result indicates that the SMS text is not a junk SMS, then it is determined that the SMS text is not a junk SMS, and the SMS text is sent to the terminal device.

[0076] S104, determine whether the sending object is included in the preset blacklist, if so, execute S105, if not, execute S106.

[0077] In this embodiment, a blacklist is preset, and the preset blacklist includes at least one user list. SMS sent by users corresponding to the preset blacklist can be directly stored in a preset spam mailbox instead of being sent to the SMS receiving mailbox of the terminal device. The user can edit the preset blacklist.

[0078] In this embodiment, if the sending object is not included in the preset whitelist, it is further determined whether the sending object is included in the preset blacklist. Specifically, the object identifier of the sending object is compared with the user list in the preset blacklist to determine whether the sending object is included in the preset blacklist.

[0079] Among them, if there is a user list matching the object identifier of the sending object in the preset blacklist, it is determined that the sending object is included in the preset blacklist; if there is no user list matching the object identifier of the sending object in the preset blacklist, it is determined that the sending object is not included in the preset blacklist.

[0080] S105: Determine that the text message is a junk message, and store the text message in a preset junk mailbox.

[0081] In this embodiment, if the sending object is included in the preset blacklist, the SMS text is determined to be a spam SMS, and the SMS text is stored in a preset spam mailbox, but not stored in the SMS receiving mailbox of the terminal device.

[0082] In this embodiment, if the sending object is not included in the preset whitelist and the preset blacklist, but the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is greater than the preset second threshold, then the SMS text is determined to be a junk SMS, and the SMS text is stored in a preset junk mailbox.

[0083] In this embodiment, if the sending object is not included in the preset whitelist and the preset blacklist, and the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is not greater than the preset second threshold, but the user's judgment result indicates that the SMS text is a junk SMS, then the SMS text is determined to be a junk SMS, and the SMS text is stored in a preset junk mailbox.

[0084] S106: Segment the text of the short message to obtain a plurality of sentences included in the text of the short message.

[0085] In this embodiment, if the sending object is not included in the preset blacklist, the SMS text is segmented to obtain multiple sentences included in the SMS text. Specifically, the SMS text is divided into multiple segments, each segment being a sentence.

[0086] See also Figure 2 , Figure 2 A segmentation processing method provided in this embodiment is used to segment a text message to obtain multiple sentences included in the text message, and specifically includes the following steps:

[0087] S201: Determine each punctuation mark in the text of the short message.

[0088] S202: Convert the punctuation marks in the SMS text that are half-width symbols into full-width symbols to obtain a target SMS text.

[0089] In this embodiment, for each punctuation mark in the SMS text, it is determined whether the punctuation mark is a half-width mark. If the punctuation mark is a half-width mark, the punctuation mark is converted into a full-width mark corresponding to the half-width mark. If the punctuation mark is a full-width mark, the punctuation mark is not processed, thereby obtaining the target SMS text.

[0090] That is to say, all punctuation marks in the target SMS text are full-width marks.

[0091] S203: Segment the target SMS text based on each full-width symbol in the target SMS text to obtain a plurality of sentences included in the SMS text.

[0092] In this embodiment, the target SMS text is segmented based on each full-width symbol in the target SMS text to obtain multiple sentences included in the SMS text. That is, the target SMS text is segmented from the full-width symbol, the character string before the first full-width symbol is formed into one sentence, the character string after the first full-width symbol to before the second full-width symbol is formed into another sentence, the character string after the second full-width symbol to before the third full-width symbol is formed into another sentence, and so on, until the target SMS text is segmented.

[0093] S107: Perform word segmentation processing on each sentence to obtain multiple words included in each sentence.

[0094] In this embodiment, word segmentation is performed on each sentence to obtain multiple words included in each sentence. In other words, word segmentation is performed on each sentence to obtain multiple words included in each sentence.

[0095] See also Figure 3 , Figure 3 A word segmentation processing method provided in this embodiment is used to perform word segmentation processing on each sentence to obtain multiple words included in the sentence. The process of performing word segmentation processing on each sentence specifically includes the following steps:

[0096] S301. Take the first character in the sentence as the first character.

[0097] In this embodiment, the first character in the sentence is used as the first character. For example, if the sentence is AGSYKH, the first character A is used as the first character.

[0098] S302: Taking the first character as the starting position, select characters corresponding to a preset character string length from the sentence as the first character string.

[0099] In this embodiment, the first character is used as the starting position, and characters corresponding to a preset character string length are selected from the sentence as the first character string. Exemplarily, the preset character string length may be 1.

[0100] For example, the statement is AGSYKH, the first character is A, and the preset string length is 1. Then, starting from character A, 1 character is selected, so A is selected as the first string.

[0101] It should be noted that the characters in the first character string are arranged in the order in which they are arranged in the sentence.

[0102] S303, determining whether there is a character string matching the first character string in the preset dictionary, if yes, executing S304, if no, executing S305.

[0103] In this embodiment, the preset dictionary includes a plurality of words, each of which is a character string. It is determined whether there is a character string matching the first character string in the preset dictionary, specifically, by traversing each character string in the dictionary, comparing the first character string with each character string in the dictionary, if the comparison is consistent, it is determined that there is a character string matching the first character string in the dictionary, if the comparison is inconsistent, it is determined that there is no character string matching the first character string in the dictionary.

[0104] S304: Use the first character string as a word of the sentence.

[0105] In this embodiment, if there is a character string matching the first character string in the dictionary, it is determined that the first character string can be a word, and the first character string is used as the word of the sentence.

[0106] S305 , compose a new first string with the next character of the first string in the statement and the first string, and return to execute S303 .

[0107] In this embodiment, if there is no character string matching the first character string in the dictionary, it is determined that the first character string cannot be the first word, and characters are continued to be taken, that is, the next character of the first character string in the sentence is taken, and the next character of the first character string in the sentence and the first character string are combined to form a new first character string.

[0108] It should be noted that the characters in the new first character string are arranged in the order in which they are arranged in the sentence.

[0109] For example, the statement is AGSYKH. If there is no string matching the first string A in the dictionary, then the next character of the first string A in the statement AGSYKH is set to G, and A and G are combined into a new string AG.

[0110] In this embodiment, after forming a new first character string, the process returns to step S303 based on the new first character string.

[0111] S306, determine whether the next character of the first string exists in the statement, if yes, execute S307, if not, end directly.

[0112] In this embodiment, it is determined whether the next character of the first string exists in the sentence, that is, it is determined whether the word segmentation of the sentence is completed. If the next character of the first string exists in the sentence, it is determined that the word segmentation of the sentence is not completed, and step S307 is executed. If the next character of the first string does not exist in the sentence, it is determined that the word segmentation of the sentence is completed, and the process ends.

[0113] For example, the sentence is AGSYKH. If the current first character string is KH, since the next character KH does not exist in the sentence AGSYKH, it is determined that the word segmentation of the sentence is completed. If the current first character string is SY, since the next character K of AG does not exist in the sentence AGSYKH, it is determined that the word segmentation of the sentence AGSYKH is not completed.

[0114] S307: Use the next character of the first string in the statement as a new first character, and return to execute S302.

[0115] In this embodiment, if the next character of the first string exists in the sentence, the next character of the first string in the sentence is used as the new first character, and the process returns to step S302 until the sentence is segmented.

[0116] In this embodiment, the word segmentation of the sentence is implemented according to a method based on dictionary string matching.

[0117] See also Figure 4 , Figure 4 Another word segmentation method provided for this implementation is used to perform word segmentation processing on each sentence to obtain multiple words included in each sentence, which specifically includes the following steps:

[0118] S401. Use the first character in the sentence as the second character.

[0119] In this embodiment, the first character in the sentence is used as the second character.

[0120] S402: Combine the second character and the next character of the second character in the sentence into a second character string.

[0121] In this embodiment, the second character and the next character of the second character in the sentence are combined into a second string. It should be noted that the characters in the second string are arranged according to the order in which they are arranged in the sentence, that is, in the second string, the second character is arranged before the next character of the second character.

[0122] S403, determining whether the frequency of the second character string appearing in each sentence included in the text of the short message is greater than a preset frequency threshold, if so, executing S404, if not, executing S405.

[0123] In this embodiment, the frequency of occurrence of the second string in each sentence included in the text of the SMS is determined. The specific process includes: firstly comparing the second string with each sentence included in the text of the SMS respectively to obtain a comparison result of the second string with each sentence, each comparison result including the number of times the second string appears in the corresponding sentence and the number of times the second string is compared with the corresponding sentence, accumulating the number of times the second string appears in each sentence to obtain the number of times the second string appears in the text of the SMS, accumulating the number of times the second string is compared with each sentence to obtain the total number of comparisons, and dividing the number of times the second string appears in the text of the SMS by the total number of comparisons to obtain the frequency of occurrence of the second string in each sentence included in the text of the SMS.

[0124] Exemplarily, the comparison process of the second string with each statement is as follows: the first character of each character included in the statement is determined as the third character, starting from the third character, taking a number of characters corresponding to the second string to form a string to be compared, and comparing the string to be compared with the first character. If the comparison is consistent, the number of times the second string appears in the statement is increased by one, and the number of comparisons is increased by one, and the next character of the third character is taken from each character included in the statement as a new third character, based on the new third character, returning to execute the step of taking a number of characters corresponding to the second string to form a string to be compared starting from the third character; if the comparison is inconsistent, the number of comparisons is increased by one, and the next character of the third character is taken from each character included in the statement as a new third character, based on the new third character, returning to execute the step of taking a number of characters corresponding to the second string to form a string to be compared starting from the third character, until the next character of the third character that does not exist in the characters included in the statement is completed.

[0125] The comparison process of the second string with each statement is illustrated as follows:

[0126] For example, the second string AB, the sentence is NABYBAC, then AB is compared with NA in the sentence NABYBAC. If the comparison is inconsistent, the number of times the second string AB appears in the sentence NABYBAC is 0, and the number of comparisons is 1. Then AB is compared with AB in the sentence NABYBAC. If the comparison is consistent, the number of times the second string AB appears in the sentence NABYBAC is 1, and the number of comparisons is 2. Then AB is compared with BY in the sentence NABYBAC. If the comparison is inconsistent, the number of times the second string AB appears in the sentence NABYBAC is 1, and the number of comparisons is 3. Then AB is compared with YB in the statement NABYBAC. If the comparison is inconsistent, the number of times the second string AB appears in the statement NABYBAC is 1, and the number of comparisons is 4. AB is then compared with BA in the statement NABYBAC. If the comparison is inconsistent, the number of times the second string AB appears in the statement NABYBAC is 1, and the number of comparisons is 5. AB is then compared with AC in the statement NABYBAC. If the comparison is inconsistent, the number of times the second string AB appears in the statement NABYBAC is 1, and the number of comparisons is 6. The comparison process of the second string AB and the statement NABYBAC is now completed.

[0127] In this implementation example, it is determined whether the frequency of occurrence of the second character string in each sentence included in the SMS text is greater than a preset frequency threshold, wherein the frequency of occurrence of the second character string in each sentence included in the SMS text is used to characterize the ratio between the number of times the second character string appears in the SMS text and the total number of comparisons, and the total number of comparisons is the total number of times the second character string is compared with the SMS text.

[0128] S404: Use the second character string as a word of the sentence.

[0129] In this embodiment, if the frequency of the second character string appearing in each sentence included in the text of the short message exceeds a preset frequency threshold, the second character string is used as a word of the sentence.

[0130] S405 , compose a new second string with the next character of the second string in the statement and the second string, and return to execute S403 .

[0131] In this embodiment, if the frequency of the second character string appearing in each sentence included in the text of the short message exceeds a preset frequency threshold, the next character of the second character string in the sentence and the second character string are combined into a new second character string.

[0132] It should be noted that the characters in the new second character string are arranged in the order in which they are arranged in the sentence.

[0133] S406: Determine whether the next character of the second string exists in the statement. If yes, execute S407; if no, terminate directly.

[0134] In this embodiment, it is determined whether the next character of the second string exists in the sentence, that is, it is determined whether the word segmentation of the sentence is completed. If the next two characters of the first string exist in the sentence, it is determined that the word segmentation of the sentence is not completed, and step S307 is executed. If the next character of the second string does not exist in the sentence, it is determined that the word segmentation of the sentence is completed, and the process ends.

[0135] S407. Use the next character of the second string in the statement as a new second character, and return to execute S402.

[0136] In this embodiment, if the next character of the second string exists in the sentence, the next character of the second string in the sentence is used as a new second character, and the process returns to step S402 until the sentence is segmented.

[0137] In this embodiment, the frequency-based word segmentation method does not need to pre-build a dictionary or store the dictionary, thereby saving a large amount of storage space and reducing memory usage.

[0138] S108. For each word, determine whether there is a junk word matching the word in the preset junk word library. If so, execute S109; if not, execute S110.

[0139] In this embodiment, a junk word library is preset, and the junk word library includes a plurality of junk words.

[0140] In this embodiment, for each word, the word is matched with each junk word in a preset junk word library. If there is a junk word matching the word in the junk word library, S109 is executed. If there is no junk word matching the word in the junk word library, S110 is executed.

[0141] S109: Determine whether the word is a junk word.

[0142] In this embodiment, for each word, if there is a junk word matching the word in the junk word library, the word is determined to be a junk word.

[0143] S110: Determine whether the word is a junk word.

[0144] In this embodiment, for each word, if there is no junk word matching the word in the junk word library, it is determined that the word is not a junk word.

[0145] S111. For each sentence, determine whether the ratio between the total number of characters of the junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold. If so, execute S112; if not, execute S113.

[0146] In this embodiment, the total number of characters of the junk words included in each sentence is counted, and the total number of characters of the sentence is counted, wherein the total number of characters of the sentence is used to represent the total number of characters included in the sentence.

[0147] Calculate the ratio between the total number of characters of the junk words included in each sentence and the total number of characters of the sentence. Specifically, for each sentence, divide the total number of characters of the junk words included in the sentence by the total number of characters of the sentence to obtain the ratio between the total number of characters of the junk words included in the sentence and the total number of characters of the sentence.

[0148] Determine whether the ratio between the total number of characters of the junk words included in the sentence and the total number of characters of the sentence is greater than a preset first threshold, if so, execute step S112, if not, execute step S113.

[0149] S112. Determine whether the statement is a junk statement.

[0150] In this embodiment, for each sentence, if the ratio between the total number of characters of junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold, the sentence is determined to be a junk sentence.

[0151] S113. Determine whether the statement is a junk statement.

[0152] In this embodiment, for each sentence, if the ratio between the total number of characters of junk words included in the sentence and the total number of characters of the sentence is not greater than a preset first threshold, it is determined that the sentence is not a junk sentence.

[0153] S114, determining whether the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is greater than a preset second threshold, if so, executing S105, if not, executing S115.

[0154] In this embodiment, the total number of characters in the junk sentences included in the SMS text is counted, and the total number of characters in each sentence included in the SMS text is counted.

[0155] In this embodiment, the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is counted. Specifically, the total number of characters in the junk sentences included in the SMS text is divided by the total number of characters in each sentence included in the SMS text.

[0156] Determine whether the ratio of the total number of characters of the junk sentences included in the SMS text to the total number of characters of each sentence included in the SMS text is greater than a preset second threshold value; if the ratio of the total number of characters of the junk sentences included in the SMS text to the total number of characters of each sentence included in the SMS text is greater than the preset second threshold value, execute step S105; if the ratio of the total number of characters of the junk sentences included in the SMS text to the total number of characters of each sentence included in the SMS text is not greater than the preset second threshold value, execute step S115.

[0157] S115, outputting prompt information; the prompt information is used to prompt the user to determine whether the SMS text is a junk SMS.

[0158] In this embodiment, if the ratio between the total number of characters in the junk sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is not greater than the preset second threshold, a prompt message is output to facilitate the user to determine whether the SMS text is a junk SMS under the prompt of the prompt message.

[0159] In this embodiment, the prompt information may be output in the form of a selection box so that the user can choose whether the SMS text is a spam SMS.

[0160] S116: Obtain the user's judgment result.

[0161] In this embodiment, the user's judgment result is obtained.

[0162] S117, judging whether the judgment result indicates that the text message is a spam message, if so, executing S105. If not, executing S103.

[0163] In this embodiment, it is determined whether the judgment result indicates that the text message is a spam message. If the judgment result indicates that the text message is a spam message, step S105 is executed. If the judgment result indicates that the text message is not a spam message, step S103 is executed.

[0164] Optionally, the preset junk word library may also be updated based on the user's judgment result.

[0165] In the SMS interception method provided in the embodiment of the present application, by extracting sentences and words and then comparing them with a preset junk word library, the junk SMS outside the blacklist can be judged and intercepted, thereby improving the convenience of use and user experience, as well as improving the accuracy of junk SMS interception.

[0166] In the SMS interception method provided in the embodiment of the present application, word segmentation is implemented based on a frequency method, in which a single character and its adjacent characters form a combination form, which is then compared with the extracted sentence in the combination form, and the sentence is segmented by judging the frequency threshold, thereby saving the entry of the vocabulary and greatly reducing memory usage.

[0167] In the SMS interception method provided in the embodiment of the present application, a blacklist and a whitelist are preset. The SMS text is first filtered through the preset whitelist and the preset blacklist, so as to effectively reduce the amount of SMS data to be processed, thereby improving the processing efficiency. In addition, the blacklist and the whitelist can also be edited by the user independently, further improving the practicality of use.

[0168] See also Figure 5 The SMS interception method mentioned in the above embodiment is illustrated as follows:

[0169] The system components required to realize the function of the SMS interception method mainly include information acquisition module, information processing module and storage module; the specific steps are:

[0170] S0: Preparation work, loading the system required for function implementation into the mobile phone and connecting it with the mobile phone system. After connection, the user edits the black / white list settings;

[0171] S1: Acquisition of SMS text, the information acquisition module acquires the SMS text from the upstream of the built-in information transceiver module of the mobile phone;

[0172] S2: After obtaining the text, first compare the sender of the text. If the sender is in the white list, cancel the subsequent steps and directly forward the message to the mobile phone inbox. If the sender is in the black list, the text message is directly intercepted to the spam mailbox. If the sender is neither in the white list nor in the black list, the obtained text is sent to the information processing module;

[0173] S3: After receiving the information, the information processing module processes the information text

[0174] S31: After obtaining the text, firstly extract the character string of the text in segments;

[0175] S32: After the segmented extraction, the extracted character string is subjected to content analysis processing;

[0176] S4: After analysis and processing, the text is classified according to the content, and the text marked as spam is fed back to the information acquisition module, which intercepts it to the spam mailbox, and the text marked as non-spam is directly transferred to the mobile phone inbox.

[0177] The information acquisition module is used for acquiring information and is placed upstream of the information transceiver module provided by the mobile phone system.

[0178] The information processing module is a written program that uses the computing power of the mobile phone system to complete the processing and analysis of information text.

[0179] The storage module is a writing program, which divides the internal storage space of the mobile phone into an area separately, and the area includes a junk mailbox storage block, a black / white list storage block, a word library storage block, and a user judgment habit storage block.

[0180] In S2, the whitelist includes mobile phone address books, WeChat address books and other social software address books containing bound mobile phone numbers. In addition, the whitelist also includes a list that can be edited by the user at will.

[0181] In S2, the blacklist includes a list that can be edited by the user and a list of names that have been detected to have sent spam text messages in the past.

[0182] In S31, the specific method of segmenting and extracting the text string is as follows:

[0183] A1: Detect all punctuation marks in the text;

[0184] A2: Replace all non-full-width symbols with full-width symbols;

[0185] A3: Segment the sentences according to punctuation marks, and split the text before the first punctuation mark and between two punctuation marks into a single sentence;

[0186] A4: Perform further word segmentation on the sentence.

[0187] In the above S32, the method for analyzing and processing the character string content is: comparing the single word after word segmentation with the database for junk words, and judging the type of the short message according to the comparison result and the preset judgment logic.

[0188] In S32, the preset judgment logic is:

[0189] a1: The segmented words are compared with the junk word database. If they match, the word is marked as junk. If they do not match, the subsequent processing of the word is skipped.

[0190] a2: If the ratio of the number of characters marked as junk words to the number of characters in the entire sentence is greater than the threshold, the sentence is considered junk.

[0191] a3: If the ratio of the number of characters in the spam sentence to the number of characters in the entire text is greater than the threshold, the text is marked as spam;

[0192] a4: If the ratio of the number of characters marked as junk sentences to the number of characters in the entire text is less than a threshold, the user is reminded to make a judgment, and the user's judgment on this SMS is used as the basis for judging the next time such junk sentences are encountered.

[0193] In A4, the word segmentation process is implemented according to a method based on dictionary string matching, and the specific steps are as follows:

[0194] A41: Compare the extracted sentence, starting from its first character, with the character strings in the dictionary according to the preset character string length;

[0195] A42: If the string in the sentence is found in the dictionary, a word is successfully separated;

[0196] A43: If the string in the sentence is not found in the dictionary, the string in the selected sentence is moved back one character and continues to match with the dictionary until the end of the sentence is reached and all matching words are separated.

[0197] In A4, word segmentation is performed according to a frequency-based method, and the specific steps are as follows:

[0198] A41: Extract a single character from the first character of the extracted sentence, and record the string consisting of the single character and the characters before and after it as the combination form of the character;

[0199] A42: Compare the combined form with the character strings of all the extracted sentences;

[0200] A43: If the frequency of occurrence of the character string composed of the characters is greater than the threshold, the combination of the characters is determined to be a word;

[0201] A44: If the frequency of occurrence of the character string composed of the characters is less than the threshold, increase the length of the character string in the character combination form and perform the comparison again.

[0202] In the SMS interception method provided in the present embodiment, when a mobile phone receives a SMS, the information acquisition module first intercepts the SMS. After acquiring the text, the sender of the text is first compared. If the sender is in the white list, the subsequent steps are cancelled and the message is directly forwarded to the mobile phone inbox. If the sender is in the black list, the SMS is directly intercepted to the spam mailbox. If the sender is neither in the white list nor in the black list, the acquired text is sent to the information processing module, and the information processing module extracts sentences and words from the SMS, and then compares the extracted words with the words in the preset spam word library. This is used as a basis for judgment, and then the spam SMS is judged according to the preset threshold of the proportion of spam words and sentences. This method can, on the one hand, judge and process spam SMS separately, prevent some SMS hazards such as fraudulent SMS, and protect the mental and property safety of users. On the other hand, when judging spam SMS, the accuracy of spam SMS interception can be greatly improved by extracting sentences and words and then comparing with the word library. For fuzzy judgment, the judgment result of the user can also be learned, which improves the practicality of use.

[0203] It should be noted that although the instructions are depicted in a particular order, this should not be understood as requiring that the instructions be executed in the particular order shown or in a sequential order. In certain circumstances, multitasking and parallel processing may be advantageous.

[0204] It should be understood that the various steps described in the method embodiments disclosed in the present application can be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0205] and Figure 1 Corresponding to the method described above, the embodiment of the present application also provides a text message interception device for Figure 1 The specific implementation of the method is shown in the following diagram: Figure 6 As shown, specifically including:

[0206] The first acquisition unit 601 is used to acquire a text message and determine a recipient of the text message;

[0207] The segmentation unit 602 is used to segment the text of the short message if the sending object is not included in the preset list, so as to obtain a plurality of sentences included in the text of the short message; the preset list includes a preset white list and a preset black list;

[0208] A word segmentation unit 603 is used to perform word segmentation processing on each sentence to obtain multiple words included in each sentence;

[0209] A first determination unit 604 is configured to determine, for each word, if there is a junk word matching the word in a preset junk word library, that the word is a junk word;

[0210] A second determining unit 605 is configured to determine, for each sentence, if a ratio between the total number of characters of junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold, then determine that the sentence is a junk sentence;

[0211] The third determination unit 606 is used to determine that the SMS text is a spam SMS and store the SMS text in a preset spam mailbox if the ratio between the total number of characters in the spam sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is greater than a preset second threshold.

[0212] The SMS interception device provided in the embodiment of the present application realizes the judgment and interception of spam SMS outside the blacklist through sentence extraction, word extraction, and then comparison with a preset spam word library, thereby improving the convenience of use and user experience, and improving the accuracy of spam SMS interception.

[0213] In one embodiment of the present application, based on the above solution, it can also be configured as follows:

[0214] The first sending unit is used to send the SMS text to the SMS receiving box of the terminal device if the sending object is included in the preset white list.

[0215] In one embodiment of the present application, based on the above solution, it can also be configured as follows:

[0216] The first storage unit is used to determine that the SMS text is a spam SMS if the sending object is included in a preset blacklist, and store the SMS text in a preset spam mailbox.

[0217] In one embodiment of the present application, based on the above solution, it can also be configured as follows:

[0218] A prompt unit, configured to output a prompt message if the ratio between the total number of characters of the junk sentences included in the SMS text and the total number of characters of each sentence included in the SMS text is not greater than a preset second threshold; the prompt message is used to prompt the user to judge whether the SMS text is a junk SMS;

[0219] A second obtaining unit, used to obtain the judgment result of the user;

[0220] A second storage unit, configured to store the spam text in a preset spam mailbox if the judgment result indicates that the text of the SMS is a spam text;

[0221] The second sending unit is configured to send the SMS text to a SMS receiving box of a terminal device if the judgment result indicates that the SMS text is not a junk SMS.

[0222] In one embodiment of the present application, based on the above solution, the segmentation unit 602 is specifically used for:

[0223] Determine each punctuation mark in the text of the SMS;

[0224] Convert the punctuation marks in the SMS text that are half-width symbols into full-width symbols to obtain a target SMS text;

[0225] The target SMS text is segmented based on each full-width symbol in the target SMS text to obtain a plurality of sentences included in the SMS text.

[0226] In one embodiment of the present application, based on the above solution, the word segmentation unit 603 is specifically used for:

[0227] For each sentence, taking the first character in the sentence as the first character, taking the first character as the starting position, and selecting characters corresponding to a preset character string length from the sentence as the first character string;

[0228] Determining whether there is a character string matching the first character string in a preset dictionary;

[0229] If there is a character string matching the first character string in the preset dictionary, the first character string is used as a word of the sentence, and the next character of the first character string in the sentence is used as a new first character, and based on the new first character, the step of taking the first character as the starting position and intercepting characters corresponding to the preset character string length from the sentence as the first character string is returned to be executed;

[0230] If there is no character string matching the first character string in the preset dictionary, the next character of the first character string in the sentence and the first character string are combined into a new first character string, and based on the new first character string, the step of determining whether there is a character string matching the first character string in the preset dictionary is returned to be executed until the word segmentation of the sentence is completed.

[0231] In one embodiment of the present application, based on the above solution, the word segmentation unit 603 is specifically used for:

[0232] For each sentence, taking the first character in the sentence as the second character, and forming a second character string with the second character and the character next to the second character in the sentence;

[0233] Determine whether the frequency of occurrence of the second string in each sentence included in the text message is greater than a preset frequency threshold; wherein the frequency of occurrence of the second string in each sentence included in the text message is used to characterize the ratio between the number of occurrences of the second string in the text message and the total number of comparisons, wherein the total number of comparisons is the total number of times the second string is compared with the text message;

[0234] If the frequency of occurrence of the second character string in each sentence included in the text of the short message is greater than a preset frequency threshold, the second character string is used as a word of the sentence, and the next character of the second character string in the sentence is used as a new second character, and based on the new second character, the step of forming a second character string with the second character and the next character of the second character in the sentence is returned to be executed;

[0235] If the frequency of occurrence of the second character string in each sentence included in the SMS text is not greater than a preset frequency threshold, the next character of the second character string in the sentence and the second character string are combined into a new second character string, and based on the new second character string, the step of determining whether the frequency of occurrence of the second character string in each sentence included in the SMS text is greater than a preset frequency threshold is returned to execute until the word segmentation of the sentence is completed.

[0236] An embodiment of the present application further provides a storage medium, wherein the storage medium stores an instruction set, wherein when the instruction set is executed, the SMS interception method disclosed in any of the above embodiments is executed.

[0237] The present application also provides an electronic device, whose structural diagram is as follows: Figure 7 As shown, it specifically includes a memory 701, which is used to store at least one set of instruction sets; a processor 702, which is used to execute the instruction set stored in the memory, and implement the following operations by executing the instruction set:

[0238] Upon receiving the page identifier fed back by the preset function, determining that a target page in the application to be tested is started; wherein the target page is a page in the application to be tested corresponding to the page identifier; during the process of starting the target page, the preset function is called;

[0239] The target page is intercepted by SMS to obtain the test result of the target page.

[0240] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

[0241] Although several specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope disclosed in the present application. Certain features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0242] The above description is only a preferred embodiment disclosed in this application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the disclosure of this application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the disclosure of this application (but not limited to) to form a technical solution.

Claims

1. A method for intercepting short messages, characterized in that: include: Obtaining a text message and determining a recipient of the text message; If the sending object is not included in the preset list, the SMS text is segmented to obtain multiple sentences included in the SMS text; the preset list includes a preset white list and a preset black list; Perform word segmentation on each sentence to obtain multiple words included in each sentence; For each word, if there is a junk word matching the word in the preset junk word library, the word is determined to be a junk word; For each sentence, if the ratio between the total number of characters of the junk words included in the sentence and the total number of characters of the sentence is greater than a preset first threshold, the sentence is determined to be a junk sentence; wherein the total number of characters of the sentence is used to represent the total number of characters included in the sentence; If the ratio of the total number of characters in the junk sentences included in the SMS text to the total number of characters in each sentence included in the SMS text is greater than a preset second threshold, the SMS text is determined to be a junk SMS, and the SMS text is stored in a preset junk mailbox.

2. The method according to claim 1, characterized in that Also includes: If the sending object is included in the preset white list, the SMS text is sent to the SMS receiving box of the terminal device.

3. The method according to claim 1, characterized in that Also includes: If the sending object is included in the preset blacklist, the text message is determined to be a spam message, and the text message is stored in a preset spam mailbox.

4. The method according to claim 1, characterized in that Also includes: If the ratio between the total number of characters of the junk sentences included in the SMS text and the total number of characters of each sentence included in the SMS text is not greater than a preset second threshold, outputting a prompt message; The prompt information is used to prompt the user to determine whether the SMS text is a spam SMS; Obtaining a judgment result of the user; If the judgment result indicates that the SMS text is a spam SMS, the spam SMS is stored in a preset spam mailbox; If the judgment result indicates that the SMS text is not a junk SMS, the SMS text is sent to the SMS receiving box of the terminal device.

5. The method according to claim 1, characterized in that The segmenting of the text message to obtain a plurality of sentences included in the text message includes: Determine each punctuation mark in the text of the SMS; Convert the punctuation marks in the SMS text that are half-width symbols into full-width symbols to obtain a target SMS text; The target SMS text is segmented based on each full-width symbol in the target SMS text to obtain a plurality of sentences included in the SMS text.

6. The method according to claim 1, characterized in that The word segmentation process is performed on each sentence to obtain multiple words included in each sentence, including: For each sentence, taking the first character in the sentence as the first character, taking the first character as the starting position, and selecting characters corresponding to a preset character string length from the sentence as the first character string; Determining whether there is a character string matching the first character string in a preset dictionary; If there is a character string matching the first character string in the preset dictionary, the first character string is used as a word of the sentence, and the next character of the first character string in the sentence is used as a new first character, and based on the new first character, the step of taking the first character as the starting position and intercepting characters corresponding to the preset character string length from the sentence as the first character string is returned to be executed; If there is no character string matching the first character string in the preset dictionary, the next character of the first character string in the sentence and the first character string are combined into a new first character string, and based on the new first character string, the step of determining whether there is a character string matching the first character string in the preset dictionary is returned to be executed until the word segmentation of the sentence is completed.

7. The method according to claim 1, characterized in that The word segmentation process is performed on each sentence to obtain multiple words included in each sentence, including: For each sentence, taking the first character in the sentence as the second character, and forming a second character string with the second character and the character next to the second character in the sentence; Determine whether the frequency of occurrence of the second string in each sentence included in the text message is greater than a preset frequency threshold; wherein the frequency of occurrence of the second string in each sentence included in the text message is used to characterize the ratio between the number of occurrences of the second string in the text message and the total number of comparisons, wherein the total number of comparisons is the total number of times the second string is compared with the text message; If the frequency of occurrence of the second character string in each sentence included in the text of the short message is greater than a preset frequency threshold, the second character string is used as a word of the sentence, and the next character of the second character string in the sentence is used as a new second character, and based on the new second character, the step of forming a second character string with the second character and the next character of the second character in the sentence is returned to be executed; If the frequency of occurrence of the second character string in each sentence included in the SMS text is not greater than a preset frequency threshold, the next character of the second character string in the sentence and the second character string are combined into a new second character string, and based on the new second character string, the step of determining whether the frequency of occurrence of the second character string in each sentence included in the SMS text is greater than a preset frequency threshold is returned to execute until the word segmentation of the sentence is completed.

8. A text message interception device, characterized in that: include: A first acquisition unit is used to acquire a text message and determine a recipient of the text message; A segmentation unit, for segmenting the text message to obtain a plurality of sentences included in the text message if the sending object is not included in a preset list; the preset list includes a preset white list and a preset black list; A word segmentation unit is used to perform word segmentation processing on each sentence to obtain multiple words included in each sentence; A first determination unit is used for determining, for each word, if there is a junk word matching the word in a preset junk word library, that the word is a junk word; A second determination unit is used to determine, for each sentence, that the sentence is a junk sentence if the ratio between the total number of characters of the junk words included in the sentence and the total number of characters in the sentence is greater than a preset first threshold value; wherein the total number of characters in the sentence is used to represent the total number of characters included in the sentence; The third determination unit is used to determine that the SMS text is a spam SMS and store the SMS text in a preset spam mailbox if the ratio between the total number of characters in the spam sentences included in the SMS text and the total number of characters in each sentence included in the SMS text is greater than a preset second threshold.

9. A storage medium, characterized in that: The storage medium stores an instruction set, wherein the instruction set, when executed by the processor, implements the SMS interception method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory for storing at least one set of instructions; The processor is used to execute the instruction set stored in the memory, and implement the SMS interception method according to any one of claims 1 to 7 by executing the instruction set.

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