English reading ability is an important indicator to measure learners’ English ability. However, because reading ability cannot be directly observed, people usually take tests to judge the reading ability of learners. Therefore, it is very necessary to design a reasonable diagnostic practice sentence repetition recognition system to analyze and test, inform learners of the advantages and disadvantages in reading, and give corresponding countermeasures. In order to properly solve the problem of repeated recognition of English diagnostic sentences, we have developed a new recognition system combined with matching tree and edge computing technology. First, the matching tree algorithm is used for the repetitive diagnosis of English sentences. The algorithm has achieved good results in the repetitive diagnosis and matching. Secondly, an English diagnostic practice sentence repetition recognition system architecture is built through edge computing algorithms, which improves the efficiency of the English diagnostic system. Finally, through the simulation test of the English diagnostic practice system, the applicability of the established repeated recognition model is verified.
Testing is an essential part of language teaching. According to different purposes, language tests can be divided into diagnostic tests, proficiency tests, ability tests, placement tests, etc. Compared with other types of tests, the relationship between diagnostic tests and teaching is closer [
At present, most college students lack the ability to self-study under the influence of self-study, traditional classroom teaching, and test-oriented education mode. And the dependence on teachers is still very strong. The contradiction between the increasing number of students and the shortage of teaching resources makes students urgently need to improve their self-learning ability [
Previous studies mostly focused on analyzing the problems of learners in reading and did not put forward the advantages of learners in reading. At the same time, there are very few studies on these problems that give learners corresponding feedback. Therefore, it is very necessary to design a reasonable diagnostic practice sentence repetition recognition system to analyze and test, inform learners of the advantages and disadvantages in reading, and give corresponding countermeasures. In order to properly solve the problem of repeated recognition of English diagnostic sentences, we have developed a new recognition system combined with matching tree and edge computing technology. The matching tree algorithm and edge computing technology will be used in the model establishment and architecture design of the English diagnostic practice system. The improvement of computer network technology and teaching facilities has injected new vitality into college English teaching and learning. With its unique novelty, interactivity, and visibility, it attracts all students in the university and provides unprecedented advantages.
Traditional cloud computing can solve the core computing tasks of the network. However, with the continuous increase of data in the cloud, the transmission delay, and calculation delay of the cloud will be challenged [
Schematic diagram of the value chain model of mobile edge computing.
Mobile edge computing helps to realize the edge cache function and improve the current low efficiency of mobile content distribution. Based on the MEC server, wireless analysis applications can be deployed at the edge of the wireless access network to provide content servers with wireless environment information (such as real-time throughput of wireless links) [
Since word recognition and language comprehension capabilities make important meaning independent of their contribution to reading ability, based on this research, the speech efficiency theory (VET) proposed by Perfetti in 1985 was adopted [
Interaction between English listening and speaking-source.
Knowledge is divided into two categories: language knowledge and other related knowledge (social knowledge, personal experience, and background) and psychological activities of listening comprehension [
Only when readers recognize words quickly and automatically without using a lot of attention resources, they can make full use of most of their attention resources to achieve successful reading ability. Although VET also focuses on the automation of decoding, this is different from AT [
The diagnostic evaluation module of the current system is the early design of the system, and does not consider aspects of learning status, knowledge point correlation analysis, question type correlation analysis, four-level score prediction, etc. [
The learning guidance for learners is very limited, and it cannot be personalized study suggestions. Therefore, this chapter first analyzes and designs the diagnostic evaluation model and then preprocesses the data collected when the system is used. The three dimensions of learning status evaluation, question type association analysis, and college English four-level score prediction are modeled separately. Finally, after combining these submodels, a relatively complete and reliable diagnostic evaluation model was obtained, and related verification was carried out [
The matching tree algorithm first preprocesses all subscription collections into a tree. After the message arrives, it traverses the established tree to find matches between all messages and events. Its core is the matching tree. Figure
Recognition of repetitive sentences in English diagnostic exercises.
Constraints:
When algorithms are matched, in order to be able to quickly respond to query requests, we usually build indexes. Through the index, when responding to query requests, the system can quickly find the needs of users. The index establishes a mapping relationship between information and content storage location information. The information index is divided into the forward index and inverted index [
The forward index is expressed in the form of “document-keyword,” and the position information of each keyword in the document is recorded in the table.
When searching, scan the words in each document in turn according to the document number, and output all matching keywords. The establishment process and organization of the positive index are relatively simple and easy to maintain. However, all matching conditions must be scanned when querying, which results in a long response time and low efficiency.
The design idea of the inverted index is the catalog, and we can quickly find the specific location of the content through the catalog. The structure of the directory is <key, address>. In order to be able to match quickly, we set a keyword whose structure is the directory of <keyword, addres>, which we call an inverted index.
In the inverted index, the word in the document is used as the “directory” keyword, and the document number where the word appears is used as the storage address, that is, <word, key>. Generally, a word will appear in multiple documents or one or more times in a document. Therefore, the address in the “directory” is a list of document numbers. Each item in the list contains information about all the locations where the word appears in the document.
Based on the fast-matching algorithm of multilevel constraint search tree, this paper designs the matching mechanism of pub/subsystem based on inverted index. The fast-matching algorithm of multilayer constraint search tree reduces repeated matching through constraint coverage when one event matches multiple subscription conditions. However, there are still many repeated matching problems when multiple events match multiple subscription conditions. In order to solve this problem, by introducing an inverted index based on a multilayer constrained search tree, an efficient matching mechanism suitable for the parallel interaction of large-scale publishers and subscribers is constructed. The inverted index is used to analyze the coverage relationship between subscription conditions and events, which reduces the number of matching subscription conditions and events and further improves matching efficiency.
At present, due to the existence of test-oriented education, the development of diagnostic tests has not attracted enough attention. Especially because of the existence of test-oriented education, the development of diagnostic testing has been neglected, so its development is particularly important. In addition, the listening ability has always been an important part of language ability. With the development of computers and the Internet, in various public tests at home and abroad, many listening tests are trying to use online listening tests, and traditional listening tests are gradually being replaced by online listening tests.
In Figure
English diagnostic exercise matching model test based on an inverted index.
Figure
Comparison of the delay of matching tree algorithm with other algorithms.
When
Figure
Comparison of edge computing power consumption for English diagnostic exercises.
The results of the research prove that compared with the traditional diagnostic online hearing test, it can play a timelier diagnostic role, so that it can quickly and accurately feedback test information. Teachers can adjust teaching in time based on feedback information to improve teaching quality. Despite its limitations, the online diagnostic hearing test system is still a test method with great development and application prospects. English reading ability is an important indicator to measure learners’ English ability. However, because reading ability cannot be directly observed, people usually take tests to judge the reading ability of learners. Therefore, it is very necessary to design a reasonable diagnostic practice sentence repetition recognition system to analyze and test, inform learners of the advantages and disadvantages in reading, and give corresponding countermeasures. The matching tree algorithm and edge computing technology will be used in the model establishment and architecture design of the English diagnostic practice system. The improvement of computer network technology and teaching facilities has injected new vitality into college English teaching and learning. With its unique novelty, interactivity, and visibility, it attracts all students in the university and provides unprecedented advantages. In the future, we will collect more experimental data to optimize the matching tree algorithm based on the diagnostic evaluation model, and improve the repeated recognition of English diagnostic contact sentences.
The authors approve that data used to support the finding of this study are included in the article.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.