Reviewerly/exHarmony huggingface dataset:
Implementation on Spark Based Self-service Drug Purchase Platform for Disease Diagnosis and Treatment

Aiming at the current shortage of medical resources, Spark parallel computing framework, OID identification, cloud computing and other technologies were used to build Spark based self-service drug purchase platform for disease diagnosis and treatment. To launch shared drug unpacking retail service, online APP mutual aid alliance and personalized service of shared service, combined with offline physical cabinet shared drug unpacking retail area, reduce drug waste while meeting user needs, and promote a green and healthy development system.
System Design of Agricultural Economic Management Mode in China Under Data Mining Technology

Agriculture is the foundation of China’s national economic development Under the new social background, the introduction of information technology into agricultural production and economic management is becoming an inevitable trend of agricultural development. This paper first analyzes the impact of data mining technology on China’s agricultural development, then finds out the problems existing in the application of data mining technology in agricultural economic management, and finally discusses the new way of agricultural economic management information.
Design of Intelligent Education Platform for College Students Based on Intelligent Virtual Technology

With the development of information technology into the cloud era, there are many hidden dangers in China's educational information construction: the educational information systems of educational units such as schools and educational institutions are usually small, independent and heterogeneous systems, which are difficult to cope with the high concurrent access of a large number of users and the blowout growth of data volume. What's more, various information resources are relatively scattered, Forming an information island is not conducive to the distribution and sharing of educational resources. In addition, different environments and expansion difficulties also increase the burden of operation and maintenance. Aiming at the field of education, this paper uses intelligent virtual technology to design and implement a large-scale, flexibly configurable and expanded intelligent education platform, which is characterized by high efficiency and stability, massive data sharing, and multi-party cooperation among learners, educators, education managers and service resources. The intelligent education platform based on intelligent virtual technology is deployed in a highly available and load balanced server cluster environment. Through the large-scale computing and storage cluster managed by Hadoop as the data storage center, it provides support for the expansion of rich and diverse educational resources, education and teaching, education management, education evaluation and other educational service applications, All services are delivered to the education Cloud Service Center for unified access and management.
Hybrid Teaching Model of Internet Marketing Gold Course: Based on Chaoxing Information Technology

With the development of modern education informatization, and the arrival of the global COVID-19 epidemic in 2020, online education has developed in a blowout manner. Online education mainly refers to a new type of education1 that integrates study activities and teaching activities through modern information machine technologies such as the Internet and artificial intelligence devices. At present, online and offline hybrid teaching has become the main teaching method. The Internet Marketing course hosted by the author of this paper (hereinafter referred to as author) was established as a first-class undergraduate course in Guangdong Province in 2020 (i.e. gold course). This paper uses Internet Marketing as an example to analyze the characteristics, curriculum design, platform construction, and interactive hybrid teaching process of Chaoxing Fanya Learning Platform.
Application of Mobile Learning App in College English ESP Hybrid Teaching in Application-Oriented Universities

The application of mobile learning app in College English ESP mixed teaching provides students with opportunities for learning, learning and practice. These applications are used for different purposes, such as improving academic performance, improving language skills and making it easier to communicate with others. It is also used as a tool to make their courses more interactive and attractive. Application oriented universities are those that attach great importance to the application of knowledge and skills. This is because their goal is to provide students with practical experience in the field of study they choose. Students will be asked to apply what they have learned from lectures, tutorials, seminars or seminars to gain real-world experience. The main goal of these universities is to get students employed after graduation. Should mobile learning applications be used for College English ESP blended teaching?
Evaluation of English Teaching Quality Based on Artificial Intelligence Optimization

The application of artificial intelligence in teaching quality evaluation is an indispensable part. Therefore, student English curriculum evaluation is an important part of College English teaching reform. This paper analyzes the current situation, participation and expectation of students’ utilization of teaching resources. This paper analyzes an intelligent algorithm related to the optimization of teaching quality, and focuses on a well applied genetic algorithm. Genetic algorithm is used to optimize ant parameters, such as typical path optimization model, which verifies the effectiveness of parameter optimization. Objective to establish a quality evaluation model for students’ English curriculum, improve students’ English learning ability and level, improve the English information platform, and provide constructive suggestions for large-scale educational reform in Colleges and universities.
The Influence of VR Technology on Film Creation and Its Development Direction

The creation of film is the combination of art and technology The emergence of modern computer technology has promoted the development of film creation. This way of expression complements the emotional needs of the real world and the sleep space in film creation. At present, the investment related to virtual reality technology and film industry is concentrated in the market. However, due to the unique personality of VR film, it is necessary for the industry to explore a development road different from traditional films on the story content, production technology and exhibition platform.
Research on the Evaluation of Business English Teaching Model Under the Background of Big Data

Frequent set mining is a key step of association rule mining. This greatly determines the effectiveness of making relevant rules. In this paper, we introduce a rule extraction algorithm in E-commerce English, and introduce relevant rules using an improved search algorithm in identifying frequent users and page interest modes, which provides a basis for the personalized recommendation system model. This proves the application of the improved association rule algorithm in E-commerce English.
Big Data Personalized Recommendation Algorithm Based on Hadoop e-Commerce Platform

With the increasing development of Internet technology, the amount of data is increasing, and recommendation system has become the primary way to help users filter effective information from massive data. In the context of big data, how to apply relevant data to optimize recommendation algorithm has become the focus of current research. This paper mainly studies the big data personalized recommendation algorithm based on Hadoop e-commerce platform. This paper optimizes the object-based system filtering recommendation algorithm and builds a recommendation module using Hadoop platform. Hadoop technology is used to design a real-time recommendation system architecture to improve the real-time performance of the recommendation system. It can be seen from the simulation results in this paper that the hadoop-based recommendation algorithm is superior to the traditional recommendation algorithm in terms of accuracy, recall rate and F-score.
The Integration and Construction of Information Education and Teaching Resources Based on Regional Cloud

This paper studies the integration and construction of information-based education and teaching resources based on regional cloud. In the era of big data, the integration of regional education resources has shown a new development trend. Moreover, if we can further integrate the education resources of colleges and universities, we can deliver high-quality talents with the flavor of the times to the society. With the deepening of school information construction, facing the new requirements of global talent training and the promotion needs of the whole process education mode. On the basis of understanding the connotation of information education and teaching resources and integration, this paper constructs the integration construction mode of information education and teaching resources in Colleges and universities, puts forward the implementation guarantee of integration construction, and effectively integrates the digital resources of the whole specialty on the cloud platform. Then, the cloud platform is used to carry out classroom teaching reforms such as flipped classroom and micro class, which has been proved to have a good effect through practice.
Construction of Higher Vocational English Resource Database Based on Computer

The construction of English Resource Bank in higher vocational colleges is a process of providing sufficient and appropriate resources for students’ academic growth. Students have access to high-quality resources that enable them to improve their language skills. This helps them develop an independent learning attitude and build confidence in dealing with new situations. This is an effective way to cultivate communication skills and improve critical thinking ability. Based on the brief introduction of English learning and its characteristics and referring to other studies, this paper summarizes the general process of English learning resource database design. At the same time, taking this process as the framework, this paper analyzes the needs of Higher Vocational English learning resources, and makes an in-depth and detailed analysis and Discussion on the customer design of Higher Vocational English learning resource database.
Deep Learning for FM-Based Recommendation: A Systematic Study on DeepFm and Its Application

As one of the classic topics in artificial intelligence, the recommender system aims to use historical data to make intelligent data recommendations for users to meet their specific needs. Lately, with the maturity of deep learning-related technology, the introduction of deep learning into recommender systems to improve their performance has gradually become a hot research topic. A representative work is called DeepFm, which can capture both low- and high-order feature interactions as traditional FM models and deep learning networks (DNNs), and thus can improve efficiency and correctness. Although numerous research works around DeepFm have been carried out in recent years, there is a lack of systematic research to allow researchers to grasp the general development of related research. Therefore, we focus on the relevant literature with high citation rates in recent years and provide a comprehensive description of the DeepFm technology, highlighting DeepFm-related research and its improvement. In addition, the modeling principles, methods, advantages, limitations, and suggestions of these studies are discussed in detail from different perspectives. We also discuss the main features of these studies and sort out future development directions.
Research on Sentence Group Division and Its Judgment Rules in Natural Language Processing

In natural language processing, especially in information retrieval and machine translation systems based on grammar and semantic rules, the processing of sentence groups is particularly important. It is an important leap step from understanding isolated word and sentence meaning to understanding the central content of the whole text. As a key step in sentence group understanding, sentence group recognition is particularly important. Starting from the structural characteristics of sentence groups, this paper divides the internal semantic combination of sentence groups, which is suitable for computer processing. According to the research results of “concept space representation of HNC language”, the relevant rules for identifying sentence groups with the above characteristics are formulated. Experiments show that the segmentation method has high sentence group coverage, and the segmentation rules have high accuracy.
Application Analysis of Big Data Technology in Vocational Education Informatization

The scale of China’s vocational training system has been recognized internationally, but on the whole, there is still a certain gap with developed countries. China’s vocational training is still facing a series of problems in the development process, such as uneven distribution of teaching resources, insufficient management system and further improvement of education quality. With the introduction of computer, The big data era has opened up new ways to learn new knowledge and new opportunities for China’s vocational education. Therefore, only when big data is fully combined with vocational training can it play an important role in vocational education innovation. Because most of our vocational schools are backward in technology, vocational schools related to the data age must actively change the traditional educational thinking mode, educational evaluation system and regulation mechanism to adapt to the development of the new era. Only in this way can vocational training be oriented to informatization and personalization, and the trained talents can provide better services for the country and society.
Research on Spoken English Speech Recognition Technology Based on MATLAB

This research paper provides you with some of the most important information about this topic. The main objective of this research paper is to provide you with an in-depth knowledge about what Research on spoken English speech recognition technology based on MATLAB is all about. We hope that after reading this article, you will be able to understand the importance of Research on spoken English speech recognition technology based on MATLAB and how it can help you achieve your academic goals. Based on the online evaluation algorithm and the interactive system, this paper develops the grammar evaluation software, combined with C-SVC and v-svc for data analysis, to improve and promote the oral English evaluation. Finally, the implementation of the interactive system proposed by the algorithm shows that the system has accurate search and comprehensive content, which is conducive to the evaluation of oral English and has strong practicability.
Evaluation of College English Teaching Quality Based on Artificial Intelligence Optimization Network

Which is a technology to help you optimize your website. This will help you increase the number of visitors to your website and improve the conversion rate. There are many ways to do this, but this is a very useful, effective and simple method. College English teaching quality evaluation is a process of evaluating the effect of College English teaching. It also describes the methods used to measure this effectiveness and provides suggestions for improvement. What is evaluation? Assessment is a method to determine how well students learn in a course or project. Assessments can be based on student assignments, teacher feedback, observations, or other evidence in the course or plan. There are many different types of assessments; Some are for testing.
Construction of Multimodal Vocational English Corpus Based on Functional Software

The purpose of this paper is to provide a multi-modal interface for the construction of Vocational English corpus. Multimodal interfaces are not new, but they are mainly used for visual interfaces and in some cases only partially used for other types of applications. The construction principle is the same as that of Oxford English corpus. The purpose of this project is to create a database containing all possible combinations of words and phrases in any given text, regardless of their type or style. Expand Workplace English teaching resources, observe the corpus, select materials and teach based on the corpus. And students complete Workplace English learning tasks, so as to truly realize the goal of Higher Vocational English teaching reform.
Language Learning and Cross-Cultural Function Based on Mobile Digital Platform

From the perspective of linguistics and cross-cultural communication, this paper analyzes three theoretical problems about confusion and anxiety in cross-cultural communication and language learning, namely pragmatic reasoning, cultural hypothesis, and the degree of confusion and anxiety. With the increasing use of digital mobile platform, more and more teachers begin to pay attention to applying the highly interactive course app based on this platform to the actual teaching process. Therefore, cross-cultural communicators and language learners must constantly expand language and cultural knowledge, enhance signal sensitivity and desire for communication and learning, and improve their intercultural adaptation skills. Language teachers should also pay enough attention to confusion and anxiety, and help students control and reduce confusion and anxiety when necessary.
Application of Data Mining Technology Based on Weka in Student Management

Data mining is a process of extracting knowledge from data. Data mining technology is used to discover large data set model and predict future events according to the model. The most common applications in data mining include prediction, diagnosis, pattern recognition and recommendation systems. This paper studies how to combine data mining technology with management technology to mine useful information hidden in massive data. According to the current situation of management, this paper introduces the relevant knowledge of data mining, analyzes and compares the relevant contents of data mining technology in detail, and decides to apply the decision tree method and rough set theory to the student analysis system. According to the actual situation of current management, this paper expounds the functions, current situation and shortcomings of current management, introduces the decision tree algorithm and rough set theory in detail, and expounds its role in management in detail.
Pre-training Meets Clustering: A Hybrid Extractive Multi-document Summarization Model

In this era where a large amount of information has flooded the Internet, manual extraction and consumption of relevant information is very difficult and time-consuming. Therefore, an automated document summarization tool is necessary to excerpt important information from a set of documents that have similar or related subjects. Multi-document summarization allows retrieval of important and relevant content from multiple documents while minimizing redundancy. A multi-document text summarization system is developed in this study using an unsupervised extractive-based approach. The proposed model is a fusion of two learning paradigms: the T5 pre-trained transformer model and the K-Means clustering algorithm. We perform the experiments on the benchmark news article corpus Document Understanding Conference (DUC2004). The ROUGE evaluation metrics were used to estimate the performance of the proposed approach on the DUC2004. Outcomes validate that our proposed model shows greatly enhanced performance as compared to the existent unsupervised state-of-the-art approaches.
BTSAH: Batch Task Scheduling Algorithm Based on Hungarian Algorithm in Cloud Computing Environment

Cloud computing is an on-demand computing service that enables the accessibility of information systems resources, notably data management and computational power, without the user being involved directly in direct active administration. Large clouds frequently contain services that are distributed across numerous locations, each of which is a data centre, also known as a cloud centre. The fundamental reason for cloud computing's appeal is the on-demand processing service, which allows users to pay only for what they use. Thus, cloud computing benefits customers in various ways through the internet. Cloud deployment models include SAAS, IAAS and PAAS. A lot of research is being done on IAAS because all consumers want a complete and appropriate allocation of requirements on the cloud. As a result, a major primary objectives of cloud technology is providing excellent remote access to resources so that advantage or profit may be maximised. The proposed methodology Batch Task Scheduling Algorithm based on Hungarian Algorithm (BTSAH) efficient locates a cloud resource that better suits to the constraint of tasks grouped in batches depending on the availability of cloud resource to achieve better utilization of resource, minimum completion time of tasks termed makespan. The proposed approach gains the advantage of Hungarian algorithm in achieving efficient scheduling technique. This paper compares and contrasts simulation analysis of the most popular and extensively used cloud computing scheduling algorithms Min-Min scheduling methodology.
Analysis and Risk Consideration of Worldwide Cyber Incidents Related to Cryptoassets

Cryptoassets are exposed to a variety of cyber attacks, including exploit vulnerabilities in blockchain technology and transaction systems, in addition to traditional cyber attacks. To mitigate incidents related to cryptoassets, it is important to identify the risk of incidents involving cryptoassets based on actual cases that have occurred. In this study, we investigate and summarize past incidents involving cryptoassets one by one using news articles and other sources. Then, each incident is classified by the “target of damage” and the “cause of damage”, and the changing incident risk was discussed by analyzing the trends and characteristics of the time series of incidents. Our results show that the number of incidents and the amount of economic damage involving cryptoassets are on the increase. In terms of the classification by the target of damage, the damage related to cryptoasset exchanges is very large among all incidents. In terms of the classification by cause of damage, it was revealed that many decentralized exchanges were affected in 2020.
Sentiment Analysis from TWITTER Using NLTK

In the present generation, Social networking sites like Twitter, Face book play a important role for communication. Twitter is one of the Blogging platform with numerous data quantity used as an insight in various functional operations of Sentiment Analysis, elections, reviewing, market, etc. The main intension of the tweet based sentiment analysis is the ability to assess good, pessimistic, or nonpartisan opinion part in the tweet information. Tweet sentiment analysis can assist any association with tracking down individuals' assessments of their organization and items. In this paper, we have applied feeling investigation on twitter informational collection. Our model takes input tweet, feeling, and result chosen text beginning and finishing off with input twee and concluded with accuracy of the model.