CN112307251A - Self-adaptive recognition correlation system and method for knowledge point atlas of English vocabulary - Google Patents
Self-adaptive recognition correlation system and method for knowledge point atlas of English vocabulary Download PDFInfo
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Abstract
The invention relates to an English vocabulary knowledge point atlas self-adaptive identification correlation system, in particular to the field of self-adaptive English vocabulary management. The invention provides an English vocabulary knowledge point atlas self-adaptive identification association system which can realize vocabulary atlas relationship creation and vocabulary audio resource automatic generation after a vocabulary list is imported, can quickly establish the atlas relationship for vocabularies, effectively reduces the labor cost, reduces the vocabulary input error rate, reduces the vocabulary editing process and reduces the vocabulary atlas association complexity.
Description
Technical Field
The invention relates to the field of self-adaptive English vocabulary management, in particular to a self-adaptive English learning word stock map management method and system.
Background
The current English learning field mainly has three backgrounds, namely, more and more scenes are provided for learning English by using mobile phone software in fragmented time by user groups at different stages; secondly, the vocabulary is used as the basis for learning English, and occupies a larger space than in the described scene; thirdly, the correlation among the vocabularies needs to be established, and a vocabulary atlas needs to be generated. At present, a simple vocabulary content management system is available on the market, but only manual addition management of vocabularies is met.
The existing vocabulary entry tool or system on the market basically meets the requirements of simply adding, deleting and modifying vocabulary information, has few functions on the establishment and management of a vocabulary atlas, and mainly inputs vocabulary and audio resources in a manual mode. The mode has high labor cost, long time consumption, high error rate, low timely discovery rate after errors occur and easy instability of learning products.
Disclosure of Invention
In view of the above defects in the prior art, the present invention provides a self-adaptive english thesaurus map management method and system, which can implement vocabulary map relationship creation and vocabulary audio resource automatic generation after the vocabulary list is imported, can quickly establish a map relationship for vocabularies, effectively reduce labor cost, reduce vocabulary input error rate, reduce vocabulary editing process, and reduce vocabulary map association complexity.
In one aspect, the invention provides a method for managing an English learning lexicon map in a self-adaptive manner, which comprises the following steps: acquiring a target vocabulary; filtering the suffix words of the target vocabulary to obtain character strings of the target vocabulary with the filtered suffix words; retrieving words containing character strings from a word stock to obtain suffix associated words; and establishing a map association relationship between the target vocabulary and the suffix association vocabulary.
In some embodiments, optionally, the step of obtaining the target vocabulary further includes: carrying out standardization processing on the newly added or modified vocabulary received by the client to obtain the vocabulary to be processed; and retrieving the vocabulary to be processed in the word stock, wherein if the vocabulary to be processed is not retrieved in the word stock, the vocabulary to be processed is taken as a target vocabulary.
In some embodiments, optionally, the step of normalizing further comprises: and removing spaces before and after the vocabulary, converting words in the vocabulary into lower case, and generating a unique code through Hash operation.
In some embodiments, optionally, the step of obtaining the target vocabulary further includes: and acquiring the audio of the target vocabulary, wherein the audio is generated by calling an audio API.
In some embodiments, optionally, the suffix word filtering step further comprises: judging whether the target vocabulary contains suffix words in the suffix word list or not; and if the target vocabulary contains suffix words, removing the suffix words in the target vocabulary to obtain the character string.
In some embodiments, optionally, the method further comprises the following steps: performing prefix word matching on the target vocabulary to obtain prefix words matched with the target vocabulary; and establishing the atlas incidence relation between the target vocabulary and the prefix words, thereby establishing the indirect atlas relation between the target vocabulary and other vocabularies containing the prefix words.
In some embodiments, optionally, the step of prefix word matching further comprises: judging whether the target vocabulary contains prefix words in the prefix word list or not; and if the target vocabulary comprises the prefix words, the prefix words are the prefix words matched with the target vocabulary.
In some embodiments, optionally, the method further comprises the following steps: and adding a target vocabulary in the word bank, and updating a word bank map according to the obtained map association relation related to the target vocabulary.
In some embodiments, optionally, if the target vocabulary is the newly added vocabulary, a new atlas is created for the target vocabulary; and if the target vocabulary is the modified vocabulary, updating the original atlas.
In another aspect, the present invention further provides an adaptive english learning thesaurus map management system, configured to perform the above method, wherein the system includes: the vocabulary information management module is configured to be capable of performing import creation, updating and deletion operations on vocabularies; the vocabulary resource generation module is configured to be capable of automatically generating audio of the newly added vocabulary and uploading the audio to the resource server; the vocabulary atlas type management module is configured to be capable of performing creating, updating and deleting operations on the vocabulary atlas; the automatic vocabulary atlas identification module is configured to automatically generate atlas relations of the newly added vocabulary; and the vocabulary map relation management module is configured to be capable of establishing, updating and deleting the vocabulary map relation.
The beneficial effects of the invention at least comprise: an efficient vocabulary knowledge point input mode is provided, vocabulary audio resources are automatically generated, and a knowledge point spectrum is automatically identified and associated. In the traditional manual input mode, one to two hours are consumed for inputting one hundred words and uploading audio, and after the technical scheme of the invention is adopted, the input of the words to the uploading of resources is completed, and the time can be up to 3 minutes. In the aspect of maintaining the vocabulary atlas relationship, at least 5 minutes are needed for one vocabulary association atlas in a manual mode, and after the automatic knowledge point recognition atlas is adopted, the time can be reduced to less than 10 seconds.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
Drawings
The present invention will become more readily understood from the following detailed description when read in conjunction with the accompanying drawings, wherein like reference numerals designate like parts throughout the figures, and in which:
fig. 1 is a block diagram of an embodiment of an adaptive english learning thesaurus map management system according to the present invention.
Fig. 2-6 are block diagrams of various modules of the adaptive english learning thesaurus management system according to the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
The invention provides a self-adaptive English learning word stock map management method, which comprises the following steps:
firstly, acquiring a target vocabulary. The vocabulary is managed through the client, and the vocabulary can be imported, created, modified and deleted. In some embodiments, the edited excel vocabulary documents can be uploaded by the client for batch import, and the server receives the files and analyzes each vocabulary therein, so that the efficiency is remarkably improved.
In some embodiments, the newly added or modified vocabulary received by the client may be standardized to obtain the vocabulary to be processed. Wherein the normalization process may include one or more of the following operations: and removing spaces before and after the vocabulary, converting words in the vocabulary into lower case, and generating the unique code through Hash operation. After standardization processing, subsequent operations such as retrieval, addition, modification and the like can be more conveniently carried out.
Then, the vocabulary to be processed is retrieved in the word stock. And if the vocabulary to be processed is not retrieved in the word stock, taking the vocabulary to be processed as the target vocabulary. In some embodiments, after detecting that the vocabulary is absent from the storage system, the vocabulary may be created and set the vocabulary flag to "new". Besides, the vocabulary information can be modified or deleted on the page of the client, and the server side modifies or deletes the data in the storage system correspondingly after receiving the request.
In some embodiments, audio of the target vocabulary may also be obtained. In some embodiments, the system may set a task to be started for a fixed period of time (e.g., every 1 minute), automatically detect a list of words marked as "new" in the storage system, and then loop to call a third-party audio API to generate audio while uploading the generated audio file to the resource file server. The vocabulary is combined with the audio files thereof, so that convenience and learning effect of English learning can be effectively improved.
Secondly, establishing an association map aiming at the target vocabulary. In some embodiments, the associative map may be established only for words marked as "audio download successful" such that all occurring words in the map have corresponding audio.
In some embodiments, a suffix word association map may be established for the target vocabulary, including:
1. and filtering the target vocabulary by using the suffix words to obtain the character strings of which the target vocabulary is filtered by the suffix words. Judging whether the target vocabulary contains suffix words in a suffix word list or not; and if the target vocabulary contains suffix words, removing the suffix words in the target vocabulary to obtain the character string.
2. The vocabulary comprising the character strings is retrieved from the lexicon to obtain a suffix associated vocabulary.
3. And establishing a map association relationship between the target vocabulary and the suffix association vocabulary.
For example, for the word "provision", the word is first filtered using a suffix word list (such as a division, an ion, an, a ment, a ness, ure, an able, an ible, an al, a sight, ful, ous, fy, ish, ize, etc.) to find the suffix word "division", thereby obtaining a character string "provi" after filtering.
Then, a vocabulary list containing the character string "provi", such as "provide, provident, providence, provided, provider", etc., is retrieved or screened from a word stock or a storage system. "provision" is then mapped individually to these words.
The words retrieved by the suffix word filtering are generally similar in spelling and have similar or associated meanings, and the words are organically associated together, so that a plurality of words can be learned at one time and the understanding and the memory can be effectively deepened in the English learning process.
In some embodiments, a prefix word association map may also be established for the target vocabulary, including:
1. and performing prefix word matching on the target vocabulary to obtain prefix words matched with the target vocabulary. Judging whether the target vocabulary contains prefix words in a prefix word list or not; and if the target vocabulary comprises the prefix words, the prefix words are the prefix words matched with the target vocabulary.
2. And establishing the atlas incidence relation between the target vocabulary and the prefix words, thereby establishing the indirect atlas relation between the target vocabulary and other vocabularies containing the prefix words.
For example, for the word "provision", it is compared and matched to a list of prefix words (e.g., ac, ad, ap, at, com, con, be, de, dis, em, en, ex, extra, im, in, inter, micro, mis, ob, op, over, per, pre, pro, re, sub, suc, sug, trans, un, uni, up, etc.) and found to match the "pro" prefix.
And then establishing mapping association between the prefix word of the "pro" and the "provision". Because the existing vocabulary in the lexicon establishes the associated map with the prefix word, the "protocol" has an indirect map association relationship with all words (such as "progress, program" and the like) containing the prefix of the "pro".
These words typically have similar or partially similar meanings based on the same prefix, which facilitates understanding and learning of different words and meanings through the prefix. Through prefix word matching and association with the words containing the same prefix words, a plurality of words can be learned at one time and understanding and memory can be effectively deepened in the English learning process.
There is no order requirement for the two steps of prefix word matching and suffix word filtering. In some embodiments, prefix word matching and suffix word filtering may be performed first, suffix word filtering may be performed first and prefix word matching may be performed second, and prefix word matching and suffix word filtering may be performed simultaneously. In other embodiments, only prefix word matching or only suffix word filtering may be performed.
And thirdly, adding target vocabularies in the word stock, and updating the word stock maps according to the obtained map association relation related to the target vocabularies. If the target vocabulary is the newly added vocabulary, establishing a new atlas aiming at the target vocabulary and adding the atlas into the lexicon; and if the target vocabulary is the modified vocabulary, updating the original map.
In some embodiments, the graph association relationship may be a one-to-one correspondence relationship, and an association relationship graph of the vocabulary may also be generated according to a plurality of association relationships of the same vocabulary, which is helpful for learning the vocabulary or knowledge points containing the vocabulary. And in some embodiments, an association relation graph can be generated according to a plurality of associated words, which is helpful for carrying out extended learning on a single knowledge point or carrying out multi-angle understanding and analysis on the associated knowledge points.
As shown in fig. 1, the present invention provides a self-adaptive english learning thesaurus map management system, which includes: the vocabulary information management module is used for carrying out import, creation, updating and deletion operations on vocabularies; the vocabulary resource generation module is used for automatically generating the audio frequency of the newly added vocabulary and uploading the audio frequency to the resource server; the vocabulary atlas type management module is used for creating, updating and deleting the vocabulary atlas; the automatic vocabulary atlas recognition module is used for automatically generating the atlas relation of the newly added vocabulary; and the vocabulary map relation management module is used for establishing, updating and deleting the vocabulary map relation.
In some embodiments, the implementation method of each module of the adaptive english learning word stock management system of the present invention is shown in fig. 2, fig. 3, fig. 4, fig. 5, and fig. 6, and the following describes in detail fig. 2, fig. 3, fig. 4, fig. 5, and fig. 6:
1. the main functions of the managed vocabulary are importing, modifying and deleting vocabulary. The process is realized, as shown in fig. 2, 1, an edited excel vocabulary document is uploaded through a client, a server receives a file and analyzes each vocabulary, spaces before and after each vocabulary are removed, a unique code is generated through hash operation, the vocabulary is created after the vocabulary does not exist in a detection storage system, and a vocabulary mark is set as 'new'; 2. and modifying or deleting the vocabulary information on the page of the client, and modifying or deleting the data in the storage system after the server receives the request.
2. The system automatically generates the vocabulary resource module, as shown in fig. 3, the system sets to start a task every 1 minute, automatically detects the vocabulary list marked as 'new' in the storage system, then circularly calls a third party audio API to generate audio, simultaneously uploads the generated audio file to the resource file server, and after the uploading is successful, modifies the set mark of the vocabulary to be 'audio downloading successful'.
3. In the process of knowledge point graph type management, as shown in fig. 4, a graph type is added, modified or deleted on a client page, and after a server receives a request, the graph type is added, modified or deleted on a storage system.
4. The automatic knowledge point spectrum association module is mainly used for generating a spectrum relationship of a newly added vocabulary and dynamically updating a modified vocabulary, and comprises the following specific steps as shown in fig. 5:
step 2, filtering suffix words for the knowledge points, wherein the specific filtered suffix word list is (version, ion, ance, conference, ness, ure, able, ible, al, tive, ful, ous, fy, ish, ize), and carrying out lowercase processing on the residual character strings after filtering;
step 3, screening words containing the character strings obtained in the step 2 from a storage system, and making lower case on all the words;
step 5, judging whether the vocabulary in the step 1 contains prefix words (the prefix word list is ac, ad, ap, at, com, con, be, de, dis, em, en, ex, extra, im, in, inter, micro, mis, ob, op, over, per, pre, pro, re, sub, suc, sag, trans, un, uni, up);
and 6, establishing a map association between the prefix words and the vocabularies contained in the step 5, and storing the map association in a storage system.
For example, the vocabulary "provision" firstly filters the suffix word "sion" in step 2 to get "provi";
then, step 3 is carried out, and a vocabulary list containing "provi" is screened out from the storage system, such as "provide, provident, providence, provided, provider" and the like;
then step 4, establishing map association between the vocabulary and the vocabularies one by one;
next, in step 5, "provision" is compared to the list of prefix words, which match the "pro" prefix,
in step 6, a map association is established between the prefix word of "pro" and "protocol", so that "protocol" has an indirect map relationship with all words (such as "progress, program") of the prefix of "pro"
Note that the steps 2, 3 and 4 and the steps 5 and 6 can be interchanged, that is, there is no order requirement for the two execution processes of map association after prefix word filtering and map association after suffix word filtering.
5. The process of managing the spectrum association relationship of the knowledge point diagram is realized, as shown in fig. 6, the management of adding, modifying or deleting the spectrum relationship is carried out on the page of the client, and after the server receives the request, the adding, modifying or deleting operation of the spectrum relationship is carried out on the storage system.
In some embodiments, the various methods described above may be implemented in one or more processing devices (e.g., a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and/or other mechanisms for electronically processing information). The one or more processing devices may include one or more devices that perform some or all of the operations of a method in response to instructions stored electronically on an electronic storage medium. The one or more processing devices may include one or more devices configured through hardware, firmware, and/or software to be specifically designed for performing one or more operations of a method. The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Embodiments of the invention may be implemented in hardware, firmware, software, or various combinations thereof. The invention may also be implemented as instructions stored on a machine-readable medium, which may be read and executed using one or more processing devices. In one implementation, a machine-readable medium may include various mechanisms for storing and/or transmitting information in a form readable by a machine (e.g., a computing device). For example, a machine-readable storage medium may include read-only memory, random-access memory, magnetic disk storage media, optical storage media, flash-memory devices, and other media for storing information, and a machine-readable transmission medium may include various forms of propagated signals (including carrier waves, infrared signals, digital signals), and other media for transmitting information. While firmware, software, routines, or instructions may be described in the above disclosure in terms of performing certain exemplary aspects and embodiments of certain actions, it will be apparent that such descriptions are merely for convenience and that such actions in fact result from computing devices, processing devices, processors, controllers, or other devices or machines executing the firmware, software, routines, or instructions.
This written description uses examples to disclose the invention, one or more examples of which are described or illustrated in the specification and drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment, can be used with another embodiment to yield a still further embodiment. It is therefore intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.
Claims (10)
1. The self-adaptive recognition and association system for the knowledge point atlas of the English vocabulary is characterized by comprising a client, a server and a data storage system, wherein:
the client is configured to be capable of acquiring a target vocabulary and submitting the target vocabulary to the server;
the server is configured to perform suffix word filtering on the target vocabulary to obtain character strings of the target vocabulary with filtered suffix words;
the server is further configured to be capable of retrieving a vocabulary comprising the character string from the data storage system to obtain a suffix filtering associated vocabulary; and
the server is further configured to be capable of establishing a map association of the target vocabulary with the suffix filtering associated vocabulary and updating the map association in the data storage system.
2. The system according to any one of the preceding claims, wherein:
the client is further configured to be capable of acquiring information for modifying or deleting vocabulary and making a request for modifying or deleting vocabulary to the server; and
the server is further configured to be able to modify or delete data in the data storage system accordingly upon accepting the request from the client.
3. The system according to any one of the preceding claims, wherein:
the server is further configured to be capable of performing standardization processing on the received newly added or modified vocabulary to obtain vocabulary to be processed; and retrieving the vocabulary to be processed in the data storage system, wherein if the vocabulary to be processed is not retrieved in the data storage system, the vocabulary to be processed is taken as the target vocabulary.
4. The system according to any one of the preceding claims, wherein:
the server is further configured to perform prefix matching on the target vocabulary to obtain prefix words matched with the target vocabulary; and establishing the atlas incidence relation between the target vocabulary and the prefix words, thereby establishing the indirect atlas relation between the target vocabulary and other vocabularies containing the prefix words.
5. The system according to any one of the preceding claims, wherein:
the server is further configured to determine whether the target vocabulary contains prefix words in a prefix word list; and if the target vocabulary comprises the prefix words, the prefix words are the prefix words matched with the target vocabulary.
6. An English vocabulary knowledge point atlas self-adaptive identification correlation method is characterized by comprising the following steps:
acquiring a target vocabulary;
filtering the target vocabulary by using suffix words to obtain character strings of the target vocabulary with the filtered suffix words;
retrieving the vocabulary comprising the character string from the data storage system to obtain a suffix filtering associated vocabulary; and
establishing an atlas incidence relation between the target vocabulary and the suffix filtering incidence vocabulary, and updating the atlas incidence relation;
the client acquires information for modifying or deleting the vocabulary, and provides a request for modifying or deleting the vocabulary to the server; and modifying or deleting, by the server, data in the data storage system accordingly upon accepting the request.
7. The method according to any of the preceding claims, characterized by the further step of:
performing prefix word matching on the target vocabulary to obtain prefix words matched with the target vocabulary; and
and establishing the atlas incidence relation between the target vocabulary and the prefix words, thereby establishing the indirect atlas relation between the target vocabulary and other vocabularies containing the prefix words.
8. The method of any preceding claim, wherein the step of prefix word matching further comprises:
judging whether the target vocabulary contains prefix words in a prefix word list or not; and
and if the target vocabulary comprises the prefix words, the prefix words are the prefix words matched with the target vocabulary.
9. An apparatus for associating adaptive recognition of knowledge point maps of english words, comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor is configured to implement the steps of the method for associating adaptive recognition of knowledge point maps of english words according to any one of claims 6 to 8 when the computer program is executed.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, is able to carry out the steps of the english vocabulary knowledge point spectrum adaptive recognition association method according to any of claims 6 to 8.
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| CN112307251B (en) | 2021-08-20 |
| CN110263210B (en) | 2020-10-27 |
| CN110263210A (en) | 2019-09-20 |
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