CN116629215A - Teaching document generation method and device, electronic equipment and storage medium - Google Patents
Teaching document generation method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure provides a method, a device, an electronic device and a storage medium for generating a teaching document, comprising the following steps: performing word segmentation processing on the target character string to obtain a term of the target character string and an unfractionated character string without the term, performing knowledge point matching according to the term and a preset knowledge point to obtain a knowledge point to be edited of the target character string, determining the unmatched term in the term, identifying the unmatched term and/or the unfractionated character string according to a preset typesetting keyword, determining a typesetting mode of the target character string, and generating a teaching document of the target character string according to the knowledge point to be edited and the typesetting mode. By means of the technical scheme, the teaching document can be automatically generated according to the target character string under the condition that artificial interference is not needed, the generating efficiency of the teaching document is improved, and the objectivity and accuracy of the content of the teaching document are improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method for generating a teaching document, an electronic device, and a storage medium.
Background
The traditional teaching document generation mode mainly searches or screens teaching contents related to knowledge points to be edited from resources such as a teaching resource page, a knowledge square and the like according to the knowledge points to be edited, and assembles the acquired teaching contents by using a document editing tool.
Because the searching or screening operation of the teaching contents is completed manually, the problem of long processing time exists, the searching or screening of the teaching contents is influenced by artificial subjective intention, and the problem of insufficient objective teaching document contents exists.
In view of this, the present disclosure aims to provide a teaching document generation scheme that can improve document generation efficiency and ensure objectivity of document content.
Disclosure of Invention
In view of the above, embodiments of the present disclosure provide a method, an apparatus, an electronic device, and a storage medium for generating a teaching document, so as to at least partially solve the above-mentioned problems.
According to a first aspect of the present disclosure, there is provided a teaching document generation method, including: performing word segmentation on a target character string to obtain at least one term and an unfractionated character string of the target character string, wherein the unfractionated character string comprises a character string which does not contain the at least one term in the target character string; according to the at least one term and the preset knowledge points, performing knowledge point matching to obtain knowledge points to be edited of the target character string, and determining unmatched terms of the target character string, wherein the unmatched terms comprise terms which are unmatched with the knowledge points to be edited in the at least one term; identifying the unmatched terms and/or the unmatched character strings according to preset typesetting keywords, and determining the typesetting mode of the target character strings; and generating the teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
According to a second aspect of the present disclosure, there is provided a document generating apparatus including: the word segmentation processing module is used for performing word segmentation processing on a target character string to obtain at least one term and an unfractionated character string of the target character string, wherein the unfractionated character string comprises a character string which does not contain the at least one term in the target character string; the knowledge point matching module is used for executing knowledge point matching according to the at least one term and a preset knowledge point to obtain a knowledge point to be edited of the target character string, and determining an unmatched term of the target character string, wherein the unmatched term comprises a term which is unmatched with the knowledge point to be edited in the at least one term; the typesetting mode matching module is used for identifying the unmatched terms and/or the unmatched character strings according to preset typesetting keywords and determining the typesetting mode of the target character strings; and the document generation module is used for generating the teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory storing a program, wherein the program comprises instructions that when executed by the processor cause the processor to perform the teaching document generation method of the first aspect described above.
According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the teaching document generation method according to the first aspect.
In summary, according to the teaching document generation method provided by the embodiment of the disclosure, knowledge point matching and typesetting pattern matching can be performed on the target character string according to the word segmentation processing result of the target character string, and the teaching document of the target character string is automatically generated without human intervention, so that the generation efficiency of the teaching document is effectively improved.
In addition, according to the teaching document generation scheme provided by the embodiment of the disclosure, the matching processing of the knowledge points to be edited is executed according to each term in the target character string, and the matching processing of the typesetting mode is executed based on the non-segmented character string and the non-matched term in the target character string, so that all information in the target character string can be ensured to be adopted in the document generation process, and the objectivity and accuracy of the document content in the generated teaching document are improved.
Drawings
Further details, features and advantages of the present disclosure are disclosed in the following description of exemplary embodiments, with reference to the following drawings, wherein:
Fig. 1 is a process flow diagram of a method of generating a teaching document according to an exemplary embodiment of the present disclosure.
Fig. 2A to 2B are application diagrams of the teaching document generation method of the exemplary embodiment of the present disclosure.
Fig. 3 is a block diagram of a teaching document generation apparatus according to an exemplary embodiment of the present disclosure.
Fig. 4 is a schematic architecture diagram of an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is 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. Related definitions of other terms will be given in the description below. It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise. The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
The existing teaching document generation method needs to search or screen the teaching document content in a manual mode, and has the problems that the document generation efficiency is low, the document content is not objective enough and the like. In view of this, the present disclosure provides a teaching document generation scheme,
specific embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a process flow of a teaching document generation method according to an exemplary embodiment of the present disclosure, which mainly includes the following steps:
step S102, word segmentation processing is carried out on the target character string, and at least one term and an unfractionated character string of the target character string are obtained.
Alternatively, the target string may comprise a user input string. For example, a character string of "group me talks about a rational number of lectures" is input in the text editing field 202 of the document editing interface 200.
Alternatively, the target string may be obtained from an existing resource, such as from an existing document or from an existing network resource.
In this embodiment, the target string may include sentences, paragraphs, articles, and the like.
In this embodiment, the word-unsegmented character string is a character string that does not include any term in the target character string.
Illustratively, word segmentation processing is performed on a target character string of "group me talks of rational numbers", two word segments of "rational numbers" and "talks" are obtained, and an unsegmented character string of "group me talks" is obtained according to the two word segments.
It should be noted that, in the case where the target character string is completely divided into a plurality of terms, there may be a case where the target character string does not have an unfractionated character string.
Step S104, according to at least one term and the preset knowledge points, performing knowledge point matching to obtain knowledge points to be edited of the target character string, and determining unmatched terms of the target character string.
In this embodiment, a knowledge tree of each preset knowledge point may be constructed according to each knowledge point attribute corresponding to each preset knowledge point, where each preset knowledge point belonging to the same knowledge tree may be a parent-child node relationship or a sibling node relationship.
Illustratively, knowledge point attributes of the preset knowledge points may include, but are not limited to, disciplines, grades, textbook versions, and the like.
Optionally, knowledge point matching may be performed according to at least one term, each preset knowledge point, and each knowledge tree corresponding to each preset knowledge point in the target character string, so as to obtain a knowledge point to be edited of the target character string.
In an embodiment, knowledge point matching may be performed according to at least one term of the target character string and a plurality of preset knowledge points, and if at least one term is matched with at least one candidate knowledge point of the plurality of preset knowledge points and the matched at least one candidate knowledge point belongs to the same knowledge tree, each candidate knowledge point may be determined as a target knowledge point, and at least one knowledge point to be edited of the target character string is obtained according to the determined at least one target knowledge point, where the number of candidate knowledge points and the number of target knowledge points should be consistent.
In another embodiment, knowledge point matching is performed according to at least one term of the target character string and a plurality of preset knowledge points, if the at least one term is matched with a plurality of candidate knowledge points in the plurality of preset knowledge points and the matched plurality of candidate knowledge points belong to a plurality of knowledge trees, one target knowledge tree with the highest priority level can be determined in each knowledge tree, at least one target knowledge point belonging to the target knowledge tree can be determined in the plurality of candidate knowledge points, and at least one knowledge point to be edited of the target character string can be determined according to the at least one target knowledge point, in this case, since only a part of the candidate knowledge points are determined as target knowledge points, the number of candidate knowledge points should be greater than the number of target knowledge points.
For example, if at least one term of the target character string is only matched with one candidate knowledge point of the plurality of preset knowledge points (i.e., when at least one term of the target character string hits the same preset knowledge point), since one candidate knowledge point necessarily belongs to only one knowledge tree, the one candidate knowledge point can be directly determined as one target knowledge point, and accordingly, one knowledge point to be edited of the target character string can be obtained.
For another example, if at least one term in the target character string is simultaneously matched with a plurality of candidate knowledge points in a plurality of preset knowledge points (i.e., at least one term in the target character string hits a plurality of preset knowledge points at the same time), and all the candidate knowledge points belong to the same knowledge tree, each candidate knowledge point can be determined as the target knowledge point, so as to obtain a plurality of knowledge points to be edited of the target character string.
For another example, if at least one term in the target character string is simultaneously matched with a plurality of candidate knowledge points in a plurality of preset knowledge points (i.e., the at least one term in the target character string hits the plurality of preset knowledge points) and the plurality of candidate knowledge points belong to different knowledge trees, then according to each priority level corresponding to each predefined knowledge tree, one knowledge tree with the highest priority level is determined as the target knowledge tree, and each candidate knowledge point on the target knowledge tree is determined as the target knowledge point, so as to obtain at least one knowledge point to be edited of the target character string.
Optionally, according to the knowledge points to be edited of the target character string, unmatched terms in each term are determined, wherein the unmatched terms are terms which are unmatched with any knowledge point to be edited in each term.
For example, referring to the embodiment shown in fig. 2A, according to the two terms "rational numbers" and "lecture" of the target character string "group i talks about the rational numbers", if the term "rational number" is determined as the knowledge point to be edited of the target character string, the term "lecture" is the unmatched term of the target character string.
In this embodiment, if all terms in the target string match the "knowledge point to be edited", there are no unmatched terms in the target string.
Step S106, identifying unmatched terms and/or unmatched character strings according to preset typesetting keywords, and determining the typesetting mode of the target character strings.
Alternatively, the preset typesetting keywords may include test question keywords and text keywords.
Illustratively, the question keywords may include, but are not limited to: exercises, questions, exercises, training, tests, quizzes, etc.
Illustratively, text keywords may include, but are not limited to: theory, definition, concept, principle, property, and the like.
Optionally, the unmatched term and/or the unmatched character string can be identified according to the test question key words and the text key words, if the unmatched term and/or the unmarked character string only contain the test question key words, the typesetting mode is determined to be the test question typesetting mode, and if the unmatched term and/or the unmarked character string only contain the text key words, the typesetting mode is determined to be the text typesetting mode; if the unmatched terms and/or the unmatched character strings simultaneously contain test question keywords and text keywords, determining the typesetting mode as a comprehensive typesetting mode (namely, the typesetting mode of test questions and texts).
Step S108, generating a teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
Optionally, according to the typesetting mode, the teaching information of the knowledge points to be edited can be retrieved to obtain the content to be edited of the knowledge points to be edited.
In this embodiment, the teaching information retrieval of the knowledge points to be edited may be performed in a specified retrieval range (for example, a specified database, a specified website, etc.), or may be performed by a full network search method without specifying a retrieval range.
Alternatively, the typesetting mode may include one of a test question typesetting mode, a text typesetting mode, and a comprehensive typesetting mode.
Alternatively, the teaching information may include test question information and/or text information.
In an embodiment, in the case that the typesetting mode is a test question typesetting mode, test question information of the knowledge points to be edited can be searched according to the test question typesetting mode, so as to obtain the test questions to be edited of the knowledge points to be edited.
In another embodiment, in the case that the typesetting mode is a text typesetting mode, text information of the knowledge points to be edited may be retrieved according to the text typesetting mode, so as to obtain the text to be edited of the knowledge points to be edited.
In still another embodiment, in the case that the typesetting mode is the comprehensive typesetting mode, the test question information and the text information of the knowledge points to be edited may be searched according to the comprehensive typesetting mode, so as to obtain the test questions to be edited and the text to be edited of the knowledge points to be edited.
In this embodiment, the text to be edited includes at least theoretical knowledge information of knowledge points to be edited, which includes but is not limited to: definition, concept, principle, property, etc. For example, in the embodiment shown in fig. 2B, the theoretical knowledge information of the "rational number" of the knowledge points to be edited includes "definition", "concept", "property", and the like.
Optionally, under the condition that the typesetting mode is a test question typesetting mode or a comprehensive typesetting mode, the unmatched word terms and/or unmatched word strings can be identified according to preset question type keywords to obtain the questions to be edited of the knowledge points, and the test questions to be edited meeting the knowledge points to be edited are screened according to the questions to be edited.
In this embodiment, the preset topic keywords may include, but are not limited to: filling in blank questions, judging questions, selecting questions, connecting questions, answering questions and the like.
If the unmatched term and/or the unmatched word string contain keywords of "blank filling questions" according to preset question type keywords, the questions with the question type of "blank filling questions" can be screened from the question information of the knowledge points to be edited, so that the questions to be edited of the knowledge points to be edited can be determined; if the unmatched term and/or the unmatched word string simultaneously contain keywords of "blank filling questions" and "answering questions", screening test question information of which the questions are "blank filling questions" or "answering questions" from the test question information of the knowledge points to be edited, and determining the test questions to be edited of the knowledge points to be edited.
Optionally, under the condition that the typesetting mode is a test question typesetting mode or a comprehensive typesetting mode, each test question in the test question information of the knowledge point to be edited is used as a candidate test question, each candidate test question is ordered according to a preset test question ordering condition, and the test questions to be edited of the knowledge point to be edited are determined from each candidate test question according to the number of the preset test questions to be edited and the ordering result of each candidate test question.
For example, the candidate questions may be ranked according to the ranking conditions of the candidate questions, such as the year of the candidate questions, the question difficulty, the question accuracy, etc., to obtain a candidate question sequence, and according to the candidate question sequence and the number of the questions to be edited (for example, 5 questions), 5 candidate questions ranked in the first 5 bits are obtained from the candidate question sequence, so as to determine the questions to be edited of the knowledge point to be edited.
In some embodiments, if the number of candidate questions is smaller than the number of questions to be edited, all the candidate questions may be directly determined as the questions to be edited.
Optionally, according to the typesetting mode, typesetting editing can be performed on the content to be edited of the knowledge point to be edited, so as to generate the teaching document of the target character string.
In an embodiment, when the typesetting mode is a test question typesetting mode, a first-level title name may be generated according to the to-be-edited knowledge point, a second-level title name may be generated according to the to-be-edited test question of the to-be-edited knowledge point, the first-level title name may be filled into the first-level title, the second-level title name may be filled into the second-level title under the first-level title, and the to-be-edited test question of the to-be-edited knowledge point may be filled into the text under the second-level title, to generate the teaching document of the target character string.
In an exemplary case that the typesetting mode is a test question typesetting mode, a primary title name "rational number" may be generated according to a knowledge point to be edited, a secondary title name "classical example title" may be generated according to a test question to be edited of the knowledge point to be edited, the primary title name "rational number" is filled into the primary title, the secondary title name "classical example title" is filled into the secondary title under the primary title, and the test question to be edited of the knowledge point to be edited is filled into the text under the secondary title, so as to generate the teaching document of the target character string.
In another embodiment, when the typesetting mode is a text typesetting mode, a primary title name may be generated according to the knowledge point to be edited, a secondary title name may be generated according to the text to be edited of the knowledge point to be edited, the primary title name may be filled into the primary title, the secondary title name may be filled into the secondary title under the primary title, and the text to be edited of the knowledge point to be edited may be filled into the text under the secondary title, thereby generating the teaching document of the target character string.
For example, referring to fig. 2B, in the case where the typesetting mode is the text typesetting mode, a primary title name "rational number" may be generated according to the knowledge point to be edited, a secondary title name "knowledge point eye" may be generated according to the text to be edited of the knowledge point to be edited, the primary title name "rational number" may be filled into the primary title (refer to a dashed box 204 of fig. 2B), the secondary title name "knowledge point eye" may be filled into the secondary title under the primary title (refer to a dashed box 206 of fig. 2B), and the text to be edited of the knowledge point to be filled into the text under the secondary title (refer to a dashed box 208 of fig. 2B), thereby generating the teaching document of the target character string.
In still another embodiment, in the case that the typesetting mode is the integrated typesetting mode, a first-level title name may be generated according to the knowledge point to be edited, a first-level title name may be generated according to the text to be edited of the knowledge point to be edited, a second-level title name may be generated according to the test question to be edited of the knowledge point to be edited, the first-level title name may be filled into the first-level title, the text to be edited of the knowledge point may be filled into the text under the first-level title, the second-level title name may be filled into the second-level title under the first-level title, and the test question to be edited of the knowledge point may be filled into the text under the second-level title, so as to generate the teaching document of the target character string.
Alternatively, in the case that the typesetting mode is the comprehensive typesetting mode, a first-level title name may be generated according to the knowledge point to be edited, a first-level title name may be generated according to the test question to be edited, a second-level title name may be generated according to the text to be edited, the first-level title name may be filled into the first-level title second-level title, the test question to be edited may be filled into the text under the first-level title second-level title, the second-level title name may be filled into the first-level title second-level title, and the text to be edited may be filled into the second-level title text under the second-level title.
Referring to fig. 2B, in the case where the typesetting mode is the integrated typesetting mode, a primary title name "rational number" may be generated according to the knowledge point to be edited, a secondary title name "knowledge point eye" may be generated according to the text to be edited of the knowledge point to be edited, a second secondary title name "classical example title" may be generated according to the test question to be edited of the knowledge point to be edited, the primary title name "rational number" may be filled into the primary title (refer to "one, rational number" in the dashed frame 204 or the dashed frame 210 of fig. 2B), the first secondary title name "knowledge point eye" may be filled into the first secondary title under the primary title (refer to the dashed frame 206 or "(one) knowledge point" in the dashed frame 210 of fig. 2B), the text to be edited of the knowledge point may be filled into the text to be edited under the first secondary title (refer to the dashed frame 208 or "one, defined in the dashed frame … …" in the dashed frame 210 of fig. 2B), the second secondary title name "classical title name" is filled into the first secondary title (refer to the dashed frame 208 or the dashed frame 210) under the second title), and the text to "text of the text to be edited" text of the second title "in the dashed frame 210" in the dashed frame 2B "(refer to the dashed frame 2B).
Alternatively, index information of the teaching document may be generated according to the typesetting editing result of the teaching document (refer to a dotted line box 210 of fig. 2B).
In addition, in some embodiments, when in step S104, if knowledge point matching is performed according to at least one term and a preset knowledge point, the knowledge point to be edited of the target character string is not obtained, the target character string may be directly filled into the body text, so as to generate the teaching document.
Alternatively, a trained neural network may be used to perform a search based on the target string (e.g., performing a full network search by invoking openAI), and all the obtained search results are used as the content to be edited of the knowledge point to be edited, and the teaching document of the target string is generated by filling the content to be edited into the text.
In summary, according to the method for generating a teaching document provided by the embodiment of the disclosure, the matching of the knowledge points and the typesetting modes is performed on the target character string according to the word segmentation result of the target character string, and the teaching document of the target character string is generated according to the matching result of the knowledge points and the typesetting modes, so that the automatic generation of the teaching document can be realized without human intervention (for example, without searching or screening of the teaching content), and the generation efficiency of the teaching document is improved.
Furthermore, according to the method for generating the teaching document provided by the embodiment of the disclosure, the matching of the knowledge points is performed according to the terms in the target character string, and the matching of the typesetting mode is performed according to the unmatched terms in the target character string (namely, the terms which are unmatched with any knowledge point to be edited in each term) and/or the unmatched character string (namely, the character string which does not contain any term in the target character string), so that all information in the target character string is ensured to be adopted in the document generation process, and the objectivity and accuracy of the content of the teaching document are improved. In addition, as each term matched with the knowledge point is removed from the target character string when the typesetting mode matching is executed, the data processing amount during the typesetting mode matching can be effectively reduced, and the document generation efficiency is further improved.
Fig. 3 is a block diagram of a teaching document generation apparatus according to an exemplary embodiment of the present disclosure. As shown in the figure, the teaching document generation apparatus 300 of the present embodiment mainly includes:
the word segmentation processing module 302 is configured to perform word segmentation processing on a target character string to obtain at least one term of the target character string and an unfractionated character string, where the unfractionated character string is a character string that does not include the at least one term in the target character string;
The knowledge point matching module 304 is configured to perform knowledge point matching according to the at least one term and a preset knowledge point, obtain a knowledge point to be edited of the target character string, and determine an unmatched term of the target character string, where the unmatched term is a term that is not matched with the knowledge point to be edited in the at least one term;
the typesetting mode matching module 306 is configured to identify the unmatched term and/or the unmatched character string according to a preset typesetting keyword, and determine a typesetting mode of the target character string;
the document generation module 308 is configured to generate a teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
Optionally, the knowledge point matching module 304 is further configured to: performing knowledge point matching according to the at least one term and a plurality of preset knowledge points, if the at least one term is matched with at least one candidate knowledge point in the plurality of preset knowledge points and the at least one candidate knowledge point belongs to the same knowledge tree, determining at least one target knowledge point according to the at least one candidate knowledge point, and obtaining at least one knowledge point to be edited of the target character string according to the at least one target knowledge point; if the at least one term is matched with a plurality of candidate knowledge points in the plurality of preset knowledge points, the plurality of candidate knowledge points belong to a plurality of knowledge trees, a target knowledge tree with the highest priority level is determined in each knowledge tree, at least one target knowledge point belonging to the target knowledge tree is determined in the plurality of candidate knowledge points, and at least one knowledge point to be edited of the target character string is obtained according to the at least one target knowledge point.
Optionally, the typesetting keywords comprise test question keywords and text keywords; the typesetting pattern matching module 306 is further configured to: identifying the unmatched term and/or the unmatched character string according to the test question keyword and the text keyword; if the unmatched term and/or the unmatched character string only contain the test question keywords, determining the typesetting mode as a test question typesetting mode; if the unmatched term and/or the unmatched character string only contain the text keyword, determining the typesetting mode as a text typesetting mode; and if the unmatched term and/or the unmatched character string contain the test question keywords and the text keywords, determining the typesetting mode as a comprehensive typesetting mode.
Optionally, the document generation module 308 is further configured to: according to the typesetting mode, retrieving teaching information of the knowledge points to be edited to obtain the content to be edited of the knowledge points to be edited; and executing typesetting editing on the content to be edited according to the typesetting mode, and generating the teaching document of the target character string.
Optionally, the document generation module 308 is further configured to: under the condition that the typesetting mode is the test question typesetting mode, retrieving test question information of the knowledge points to be edited according to the test question typesetting mode to obtain test questions to be edited of the knowledge points to be edited; under the condition that the typesetting mode is the text typesetting mode, retrieving text information of the knowledge points to be edited according to the text typesetting mode to obtain a text to be edited of the knowledge points to be edited; under the condition that the typesetting mode is the comprehensive typesetting mode, according to the comprehensive typesetting mode, searching test question information and text information of the knowledge points to be edited to obtain test questions to be edited and texts to be edited of the knowledge points to be edited; the text to be edited at least comprises theoretical knowledge information of the knowledge points to be edited.
Optionally, the document generation module 308 is further configured to: under the condition that the typesetting mode is the test question typesetting mode or the comprehensive typesetting mode, identifying the unmatched word terms and/or the unmatched word character strings according to preset question type keywords to obtain the questions to be edited of the knowledge points to be edited; and screening test question information of the knowledge points to be edited according to the questions to be edited to obtain the test questions to be edited which meet the questions to be edited.
Optionally, the document generation module 308 is further configured to: and under the condition that the typesetting mode is the test question typesetting mode, generating a primary title name according to the to-be-edited knowledge point, generating a secondary title name according to the to-be-edited test question of the to-be-edited knowledge point, filling the primary title name into the primary title, filling the secondary title name into the secondary title under the primary title, filling the to-be-edited test question of the to-be-edited knowledge point into the text under the secondary title, and generating the teaching document of the target character string.
Optionally, the document generation module 308 is further configured to: and under the condition that the typesetting mode is the text typesetting mode, generating a primary title name according to the knowledge point to be edited, generating a secondary title name according to the text to be edited of the knowledge point to be edited, filling the primary title name into the primary title, filling the secondary title name into the secondary title under the primary title, filling the text to be edited of the knowledge point to be edited into the text under the secondary title, and generating the teaching document of the target character string.
Optionally, the document generation module 308 is further configured to: under the condition that the typesetting mode is the comprehensive typesetting mode, generating a first-level title name according to the knowledge point to be edited, generating a first-level title name according to the text to be edited of the knowledge point to be edited, generating a second-level title name according to the test question to be edited of the knowledge point to be edited, filling the first-level title name into the first-level title under the first-level title, filling the text to be edited of the knowledge point to be edited into the text under the first-level title, filling the second-level title name into the second-level title under the first-level title, and filling the test question to be edited of the knowledge point to be edited into the text under the second-level title, so as to generate the teaching document of the target character string.
Optionally, the document generation module 308 is further configured to: if the knowledge point matching module 304 performs knowledge point matching according to the at least one term and the preset knowledge point, the knowledge point to be edited of the target character string is not obtained, and the target character string is filled into the text, so as to generate the teaching document.
The present disclosure provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the teaching document generation method according to the exemplary embodiments of the present disclosure.
Exemplary embodiments of the present disclosure provide an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor. The memory stores a computer program executable by the at least one processor for causing the electronic device to perform the teaching document generation method according to the exemplary embodiments of the present disclosure when executed by the at least one processor.
Referring to fig. 4, a block diagram of an electronic device 400 that may be a server or client of the present disclosure, which is an example of a hardware device that may be applied to aspects of the present disclosure, will now be described. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 4, the electronic device 400 includes a computing unit 401 that can perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 402 or a computer program loaded from a storage unit 408 into a Random Access Memory (RAM) 403. In RAM 403, various programs and data required for the operation of device 400 may also be stored. The computing unit 401, ROM 402, and RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
Various components in electronic device 400 are connected to I/O interface 405, including: an input unit 406, an output unit 407, a storage unit 408, and a communication unit 409. The input unit 406 may be any type of device capable of inputting information to the electronic device 400, and the input unit 406 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. The output unit 407 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, media/audio output terminals, vibrators, and/or printers. Storage unit 408 may include, but is not limited to, magnetic disks, optical disks. The communication unit 409 allows the electronic device 400 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunications networks, and may include, but is not limited to, modems, network cards, infrared communication devices, wireless communication transceivers and/or chipsets, such as bluetooth (TM) devices, wiFi devices, wiMax devices, cellular communication devices, and/or the like.
The computing unit 401 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the respective methods and processes described above. For example, in some embodiments, the teaching document generation method as described above may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 400 via the ROM 402 and/or the communication unit 409. In some embodiments, the computing unit 401 may be configured to perform the teaching document generation method described above by any other suitable means (e.g., by means of firmware).
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
As used in this disclosure, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data service), or that includes a middleware component (e.g., an application service), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and the server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be noted that each component/step described in the embodiments of the present disclosure may be split into more components/steps, or two or more components/steps or partial operations of the components/steps may be combined into new components/steps according to implementation needs, to achieve the objects of the embodiments of the present disclosure.
The above embodiments are only for illustrating the embodiments of the present disclosure, not for limiting the embodiments of the present disclosure, and various changes and modifications may be made by one of ordinary skill in the relevant art without departing from the spirit and scope of the embodiments of the disclosure, so all equivalent technical solutions also fall within the scope of the embodiments of the present disclosure, the scope of which is defined by the claims.
Claims (11)
1. A method of generating a teaching document, comprising:
performing word segmentation on a target character string to obtain at least one term and an unfractionated character string of the target character string, wherein the unfractionated character string comprises a character string which does not contain the at least one term in the target character string;
According to the at least one term and the preset knowledge points, performing knowledge point matching to obtain knowledge points to be edited of the target character string, and determining unmatched terms of the target character string, wherein the unmatched terms comprise terms which are unmatched with the knowledge points to be edited in the at least one term;
identifying the unmatched terms and/or the unmatched character strings according to preset typesetting keywords, and determining the typesetting mode of the target character strings;
and generating the teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
2. The method of claim 1, wherein the performing knowledge point matching according to the at least one term and a preset knowledge point to obtain a knowledge point to be edited of the target character string includes:
performing knowledge point matching according to the at least one term and a plurality of preset knowledge points,
if the at least one term is matched with at least one candidate knowledge point in the plurality of preset knowledge points, and the at least one candidate knowledge point belongs to the same knowledge tree, determining at least one target knowledge point according to the at least one candidate knowledge point, and obtaining at least one knowledge point to be edited of the target character string according to the at least one target knowledge point;
If the at least one term is matched with a plurality of candidate knowledge points in the plurality of preset knowledge points, the plurality of candidate knowledge points belong to a plurality of knowledge trees, a target knowledge tree with the highest priority level is determined in each knowledge tree, at least one target knowledge point belonging to the target knowledge tree is determined in the plurality of candidate knowledge points, and at least one knowledge point to be edited of the target character string is obtained according to the at least one target knowledge point.
3. The method according to claim 1 or 2, wherein the typesetting keywords include test question keywords and text keywords;
wherein, the identifying the unmatched term and/or the unmatched character string according to the preset typesetting keyword, and determining the typesetting mode of the target character string comprise:
identifying the unmatched term and/or the unmatched character string according to the test question keyword and the text keyword;
if the unmatched term and/or the unmatched character string only contain the test question keywords, determining the typesetting mode as a test question typesetting mode;
if the unmatched term and/or the unmatched character string only contain the text keyword, determining the typesetting mode as a text typesetting mode;
And if the unmatched term and/or the unmatched character string contain the test question keywords and the text keywords, determining the typesetting mode as a comprehensive typesetting mode.
4. The method of claim 1, wherein the generating the teaching document of the target character string according to the knowledge points to be edited and the typesetting mode comprises:
according to the typesetting mode, retrieving teaching information of the knowledge points to be edited to obtain the content to be edited of the knowledge points to be edited;
and executing typesetting editing on the content to be edited according to the typesetting mode, and generating the teaching document of the target character string.
5. The method of claim 4, wherein the typesetting mode includes one of a test question typesetting mode, a text typesetting mode, and a comprehensive typesetting mode, and the teaching information includes test question information and text information; and wherein the first and second heat exchangers are configured to,
according to the typesetting mode, retrieving teaching information of the knowledge points to be edited to obtain contents to be edited of the knowledge points to be edited, including:
under the condition that the typesetting mode is the test question typesetting mode, retrieving test question information of the knowledge points to be edited according to the test question typesetting mode to obtain test questions to be edited of the knowledge points to be edited;
Under the condition that the typesetting mode is the text typesetting mode, retrieving text information of the knowledge points to be edited according to the text typesetting mode to obtain a text to be edited of the knowledge points to be edited;
under the condition that the typesetting mode is the comprehensive typesetting mode, according to the comprehensive typesetting mode, searching test question information and text information of the knowledge points to be edited to obtain test questions to be edited and texts to be edited of the knowledge points to be edited;
the text to be edited at least comprises theoretical knowledge information of the knowledge points to be edited.
6. The method according to claim 5, wherein, in the case that the typesetting mode is the test question typesetting mode or the comprehensive typesetting mode, the obtaining the test questions to be edited of the knowledge points to be edited includes:
identifying the unmatched term and/or the unmatched character string according to a preset question key word to obtain a question to be edited of the knowledge point to be edited;
and screening test question information of the knowledge points to be edited according to the questions to be edited to obtain the test questions to be edited which meet the questions to be edited.
7. The method according to claim 5, wherein the performing typesetting editing on the content to be edited according to the typesetting mode, generating the teaching document of the target character string, comprises:
Generating a primary title name according to the to-be-edited knowledge point, generating a secondary title name according to the to-be-edited test of the to-be-edited knowledge point, filling the primary title name into a primary title, filling the secondary title name into a secondary title under the primary title, filling the to-be-edited test of the to-be-edited knowledge point into a text under the secondary title, and generating a teaching document of the target character string;
generating a primary title name according to the knowledge point to be edited, generating a secondary title name according to the text to be edited of the knowledge point to be edited, filling the primary title name into a primary title, filling the secondary title name into a secondary title under the primary title, filling the text to be edited of the knowledge point to be edited into a text under the secondary title, and generating a teaching document of the target character string;
under the condition that the typesetting mode is the comprehensive typesetting mode, generating a first-level title name according to the knowledge point to be edited, generating a first-level title name according to the text to be edited of the knowledge point to be edited, generating a second-level title name according to the test question to be edited of the knowledge point to be edited, filling the first-level title name into the first-level title under the first-level title, filling the text to be edited of the knowledge point to be edited into the text under the first-level title, filling the second-level title name into the second-level title under the first-level title, and filling the test question to be edited of the knowledge point to be edited into the text under the second-level title, so as to generate the teaching document of the target character string.
8. The method of claim 1, wherein the method further comprises:
and if knowledge point matching is executed according to the at least one term and the preset knowledge points, the knowledge points to be edited of the target character string are not obtained, the target character string is filled into the text, and the teaching document is generated.
9. A teaching document generation device, comprising:
the word segmentation processing module is used for performing word segmentation processing on a target character string to obtain at least one term and an unfractionated character string of the target character string, wherein the unfractionated character string comprises a character string which does not contain the at least one term in the target character string;
the knowledge point matching module is used for executing knowledge point matching according to the at least one term and a preset knowledge point to obtain a knowledge point to be edited of the target character string, and determining an unmatched term of the target character string, wherein the unmatched term comprises a term which is unmatched with the knowledge point to be edited in the at least one term;
the typesetting mode matching module is used for identifying the unmatched terms and/or the unmatched character strings according to preset typesetting keywords and determining the typesetting mode of the target character strings;
And the document generation module is used for generating the teaching document of the target character string according to the knowledge points to be edited and the typesetting mode.
10. An electronic device, comprising:
a processor; and
a memory in which a program is stored,
wherein the program comprises instructions which, when executed by the processor, cause the processor to perform the teaching document generation method of any of claims 1-8.
11. A non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the teaching document generation method of any of claims 1-8.
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| CN116957872A (en) * | 2023-09-20 | 2023-10-27 | 广州宏途数字科技有限公司 | Intelligent classroom lesson preparation method based on big data |
| CN116957872B (en) * | 2023-09-20 | 2023-12-22 | 广州宏途数字科技有限公司 | Intelligent classroom lesson preparation method based on big data |
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