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Hybrid modelling of the RED algorithm in the Julia language 7

Hybrid modelling of the RED algorithm in the Julia language

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7th international Young Scientists conference on information technology, Telecommunications and Control Systems, ITTCS 2020

作者： Apreutesey, A M Yu Korolkova, A.V. Kulyabov, D.S. 6 Miklukho-Maklaya St. Moscow117198 Russia Joint Institute for Nuclear Research 6 Joliot-Curie Moscow regionDubna141980 Russia

this work is devoted to studying the possibilities of hybrid modeling of communication network algorithms in the Julia programming language. A simulation of the system, which consists of an incoming stream processed according to the Transmission Control Protocol (TCP) and a router processing traffic according to the Random Early Detection (RED) algorithm, is carried out. this model contains both continuous and discrete elements, for example, a discrete probability function of random packet dropping in the case of queue congestion. © Published under licence by IOP Publishing Ltd.

关键词： Transmission control protocol

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Spatialization Method of Atmospheric Quality Public Opinion Based on Natural language processing 7th

Spatialization Method of Atmospheric Quality Public Opinion ...

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7th international conference on Geoinformatics in Sustainable Ecosystem and Society, GSES 2019, and 1st international conference on Geospatial Artificial Intelligence for Urban Computing, GeoAI 2019

作者： Sun, Yong Song, Pengfei Ji, Min Zheng, Yan Zhang, Liguo Shandong University of Science and Technology Qingdao266590 China Shandong Institute of Land Surveying and Mapping Jinan250102 China

ISBN: (纸本)9789811561054

With the increasing environmental awareness of the country and the people and the implementation of strong environmental protection measures, China’s atmospheric quality was improved obviously, but local atmospheric pollution events still occurred frequently. In order to make up for the missing detection of local atmospheric pollution events caused by sparse fixed State-controlled monitoring stations, the paper proposed a spatialization method for atmospheric quality public opinion information based on natural language processing. Using Chinese word segmentation, part of speech tagging and other methods, the paper extracted addresses from public atmospheric pollution complaints data. through an effective combination of those addresses, the paper realized address matching of those complaint points, and spatialized those key complaint areas in Shandong Province in the form of heat map. through comparison and analyzing with the atmospheric quality monitoring data of national control stations, it showed that the key areas of public complaints were highly consistent with the key pollution areas which were monitored by national control stations. the research result showed that the public could perceive the atmospheric quality directly, and reflect the local atmospheric pollution at a smaller space-time scale effectively, which was a robust supplementation to the monitoring data of the national control station. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Monitoring

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Cross-language generative automatic summarization based on attention mechanism 1

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17th international conference on web information Systems and Applications, WISA 2020

作者： Yang, Feiyang Cui, Rongyi Yi, Zhiwei Zhao, Yahui Department of Computer Science and Technology Yanbian University 977 Gongyuan Road Yanji133002 China

ISBN: (数字)9783030600297

ISBN: (纸本)9783030600280

Generative automatic summarization is a basic problem in natural language processing. We propose a cross-language generative automatic summarization model. Unlike the traditional methods that have to go through machine translation, our model can directly generate a text summary of another language from a text body in one language. We use the RNNLM(Recurrent Neural Network based language Model) structure to pre-train word vectors to obtain semantic information in different languages. We combined the Soft Attention mechanism in the Seq2Seq model, using Chinese, Korean and English to build a parallel corpus to train the model, thereby, cross-language automatic summarization can be achieved without the help of machine translation technology. Experiments show that the improvement of our proposed model on ROUGE-1, ROUGE-2 and ROUGE-L indicators reached 6%, 2.46%, and 5.13%, respectively. the experimental effect is friendly. © Springer Nature Switzerland AG 2020.

关键词： Recurrent neural networks

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the Crawl and Analysis of Recruitment Data Based on the Distributed Crawler 7th

The Crawl and Analysis of Recruitment Data Based on the Dist...

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7th international conference on Green Energy and Networking, GreeNets 2020

作者： Wang, Jiancai Shi, Jianting Office of Academic Affairs Hei Longjiang University of Science and Technology Harbin150022 China School of Computer and Information Engineering Hei Longjiang University of Science and Technology Harbin150022 China

ISBN: (纸本)9783030624828

Because of the rapid development of Internet, how to efficiently and quickly obtain useful data has become an importance. In this paper, a distributed crawler crawling system is designed and implemented to capture the recruitment data of online recruitment websites. the architecture and operation workflow of the Scrapy crawler framework is combined with Python, the composition and functions of Scrapy-Redis and the concept of data visualization. Echarts is applied on crawlers, which describes the characteristics of the web page where the employer publishes recruitment information. In the base of Scrapy framework, the middleware, proxy IP and dynamic UA are used to prevent crawlers from being blocked by websites. Data cleaning and encoding conversion is used to make data processing. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： websites

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Question Answering on Structured Data using NLIDB Approach 5

Question Answering on Structured Data using NLIDB Approach

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5th international conference on advanced Computing and Communication Systems (ICACCS)

作者： Wudaru, Vishal Koditala, Nikhil Reddy, Aruneswara Mamidi, Radhika BML Munjal Univ Kapriwas Haryana India Int Inst Informat Technol Hyderabad Telangana India

ISBN: (纸本)9781538695333

In this paper we present our work in building Natural language Interface to Database (NLIDB) system using Intermediate query approach. this approach is demonstrated using Movie domain chatbot and can also be extended to different domains. the need of NLIDB System has increased in this fast paced world where more number of users are accessing databases through their Smart phones and web browsers. NLIDB System maps user's Natural language query to database query allowing user to extract information without any prior experience with databases. Results obtained are very promising and can tackle most of the user queries regarding target database.

关键词： Natural language Interface to Database (NLIDB) Natural language processing (NLP) Database Management System (DBMS) Query language Movie domain Intermediate query approach

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A Survey on Evaluation Methods for Chatbots 2019

A Survey on Evaluation Methods for Chatbots

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7th international conference on information and Education technology (ICIET)

作者： Maroengsit, Wari Piyakulpinyo, thanarath Phonyiam, Korawat Pongnumkul, Suporn Chaovalit, Pimwadee theeramunkong, thanaruk Thammasat Univ SIIT 131 Moo 5Tiwanont Rd Muang 12000 Pathum Thani Thailand NECTEC 112 Phahonyothin Rd Khlong Luang 12120 Pathum Thani Thailand

ISBN: (纸本)9781450366397

Nowadays chatbots have been widely adopted in many industries to automatically answer users' questions and requests via chat interfaces. While it has become much easier to develop a chatbot system, the system itself is a complex system in nature. It is a challenge to evaluate and compare various chatbot systems in terms of effectiveness, efficiency, goal achievability, and the ability to satisfy users. this paper presents a survey, starting from literature review, chatbot architecture, evaluation methods/criteria, and comparison of evaluation methods. Focused on the three subprocesses in the chatbot architecture: text processing, semantic understanding, and response generation. Moreover, the survey is conducted with classification of chatbot evaluation methods and their analysis according to chatbot types and three main evaluation schemes;content evaluation, user satisfaction, and chat function.

关键词： Chatbot Evaluation information Systems Natural language processing Natural language Understanding.

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Ontology-Based Recommender System for Sport Events 13th

Ontology-Based Recommender System for Sport Events

引用

13th international conference on Ubiquitous information Management and Communication (IMCOM)

作者： Quang Nguyen Huynh, Luan N. T. Le, Tuyen P. Chung, TaeChoong Kyung Hee Univ Seoul 17104 Gyeonggi Do South Korea

ISBN: (纸本)9783030190637;9783030190620

Sport event participation has changed much recently with effective support of technology. advanced developments in recommender systems and World Wide web bring chances such as efficiently distantly booking to alone travelers which allows them to enjoy sport events without being dependent on expensive tourist agencies as in the past. However, currently, popular information sources for such a recommender system are isolated and mainly relied on web 2.0 formats which are difficult to stored and processed, especially among different platforms and communities. To utilize huge resources of web 2.0 as well as apply cutting-edge features of web 3.0 and under-developing web 4.0, the authors propose an implementation of a hybrid system which collects data from different sources in the Internet (Mashup), apply machine learning to process raw information (Natural language processing and Unsupervised Clustering), add semantics to the processed data and make it compatible to latest web generation (Ontology), and provide recommendations based on smart content-based filtering and social-network-based user profiles for sport events. Empirical results show promising applications of such a framework to the market portion of alone travelers and also set an example as a demonstration for the authors' expectation toward web 4.0 applications in the future.

关键词： Ontology Mashup Natural language processing Content-based filtering Unsupervised clustering

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web platform for learning distributed databases' queries processing 7

Web platform for learning distributed databases' queries pro...

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7th international conference on information technology and Quantitative Management (ITQM) - information technology and Quantitative Management Based on Artificial Intelligence

作者： Herce-Zelaya, Julio Porcel, Carlos Bernabe-Moreno, Juan Tejeda-Lorente, Alvaro Herrera-Viedma, Enrique Univ Granada Dept Comp Sci & Artificial Intelligence Granada Spain Univ Jaen Dept Comp Sci Jaen Spain

A distributed database is a collection of data stored in different locations of a distributed system. the processing of queries in distributed databases is quite complex but of great importance for information management. Students who have to learn that process have serious difficulties for understanding them. On this work we present a web platform for helping the students learning the processing and optimization of queries in distributed databases. the novelty of this platform is that as far as we know, there is no similar graphical tool. It allows to visualize step by step the different phases of distributed query processing, showing how are they forming, making it easier for the students to understand these concepts. Moreover, having this web platform available, always and everywhere, indirectly have an impact on other competences like encouraging students' autonomous work and self-learning, adapting the teaching to its one-time necessities and reinforcing the advantages to apply information techniques in the teaching field. the results of the developed tests to validate the platform's functionalities and student's satisfaction were very positive. (C) 2020 the Authors. Published by Elsevier B.V.

关键词： Learning platform Distributed databases Distributed queries processing

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Experimental Disease Prediction Research on Combining Natural language processing and Machine Learning 7

Experimental Disease Prediction Research on Combining Natura...

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7th IEEE international conference on Computer Science and Network technology (ICCSNT)

作者： Yu, Hong Qing Univ Bedfordshire Sch Comp Sci & Technolgy Luton Beds England

ISBN: (纸本)9781728132990

Nowadays Artificial Intelligent (AI) technologies are applied widely in many different areas to assist knowledge gaining and decision-making tasks. Especially, health information system can get most benefits from the AI advantages. In particular, symptoms based disease prediction research and production became increasingly popular in the healthcare sector recently. Various researchers and organizations have turned their interest in using modern computational techniques to analyze and develop new approaches that can efficiently predict diseases with reasonable accuracy. In this paper, we propose a framework to evaluate the efficiency of applying both Machine Learning (ML) and Nature language processing (NLP) technologies for disease prediction system. As an example, we scraped a disease-symptom dataset with NLP features from one of the UK most trustable National Health Service (NHS) website. In addition, we will exam our data in depth having symptom frequency, similarity and clustering analysis. As result, we can see that the prediction can have a very positive efficient rate but still open issues need to be addressed.

关键词： Artificial Intelligent Data analysis Machine Learning health Nature language processing

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A method for the semantic analysis of documents in a business context in Spanish 7

A method for the semantic analysis of documents in a busines...

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7th international conference on information technology and Quantitative Management (ITQM) - information technology and Quantitative Management Based on Artificial Intelligence

作者： Rodriguez-Cardos, Ruben Romero Chicharro, Francisco Pascual Olivas Varela, Jose Angel Serrano-Guerrero, Jesus Univ Castilla La Mancha Univ Coll Comp Sci Dept Technol & Informat Syst Paseo Univ 4 E-13071 Ciudad Real Spain

Due to the ease of generating and storing written text documents, Natural language processing tools are increasingly integrated into software products on decision making in various fields. In this paper, we work with real requests from customers of a real estate company. the objective of the paper is to design a preliminary approximation of new intelligent algorithms that can carry out a semantic analysis of text documents in the business environment. For this purpose, different prototypes are developed, based on techniques and methods from different disciplines, such as Natural language processing, to process and structure text, Text Mining to find the most relevant terms and Knowledge Engineering, to create an ontology with the objective of measuring semantic similarity in business documents. the prototypes obtained are capable of determining the semantic similarity between simple phrases, structuring existing terms, and determining the subject on which they deal with requests from clients of a real estate company. (C) 2020 the Authors. Published by Elsevier B.V.

关键词： Sentiment Analysis Natural language processing Semantics Ontologies

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