This book elaborates on the six pillars of a healthy and standardized real-estate brokerage industry: the generation, distribution and matching of information; the transaction system; circulation finance; mobile Internet; the supervision system; and professional brokers. With each of these pillars playing a role, they also mutually interact to constitute an integrated framework that regulates the brokerage industry. Presenting practicable, extensive and cutting-edge research that encompasses various areas of the industry and detailed case studies from around the globe, the book provides a number of suggestions that have already been adopted and have begun to take effect. It also explores the frontiers of the real-estate brokerage industry - the incorporation of the internet, the blurred boundary between online and offline service where brokerages are moving online, client acquisition is via the internet, and benchmark companies are focusing more on their trading service capacity, each building their own controllable trading environment.

In an article for Wired Magazine in 2006, Jeff Howe defined crowdsourcing as an idea for outsourcing a task that is traditionally performed by a single employee to a large group of people in the form of an open call. Since then, by modifying crowdsourcing into different forms, some of the most successful new companies on the market have used this idea to make people's lives easier and better. On the other hand, software testing has long been recognized as a time-consuming and expensive activity. Mobile application testing is especially difficult, largely due to compatibility issues: a mobile application must work on devices with different operating systems (e.g. iOS, Android), manufacturers (e.g. Huawei, Samsung) and keypad types (e.g. virtual keypad, hard keypad). One cannot be 100% sure that, just because a tested application works well on one device, it will run smoothly on all others.Crowdsourced testing is an emerging paradigm that can improve the cost-effectiveness of software testing and accelerate the process, especially for mobile applications. It entrusts testing tasks to online crowdworkers whose diverse testing devices/contexts, experience, and skill sets can significantly contribute to more reliable, cost-effective and efficient testing results. It has already been adopted by many software organizations, including Google, Facebook, Amazon and Microsoft. This book provides an intelligent overview of crowdsourced testing research and practice. It employs machine learning, data mining, and deep learning techniques to process the data generated during the crowdsourced testing process, to facilitate the management of crowdsourced testing, and to improve the quality of crowdsourced testing.

In an article for Wired Magazine in 2006, Jeff Howe defined crowdsourcing as an idea for outsourcing a task that is traditionally performed by a single employee to a large group of people in the form of an open call. Since then, by modifying crowdsourcing into different forms, some of the most successful new companies on the market have used this idea to make people’s lives easier and better. On the other hand, software testing has long been recognized as a time-consuming and expensive activity. Mobile application testing is especially difficult, largely due to compatibility issues: a mobile application must work on devices with different operating systems (e.g. iOS, Android), manufacturers (e.g. Huawei, Samsung) and keypad types (e.g. virtual keypad, hard keypad). One cannot be 100% sure that, just because a tested application works well on one device, it will run smoothly on all others.Crowdsourced testing is an emerging paradigm that can improve the cost-effectiveness of software testing and accelerate the process, especially for mobile applications. It entrusts testing tasks to online crowdworkers whose diverse testing devices/contexts, experience, and skill sets can significantly contribute to more reliable, cost-effective and efficient testing results. It has already been adopted by many software organizations, including Google, Facebook, Amazon and Microsoft. This book provides an intelligent overview of crowdsourced testing research and practice. It employs machine learning, data mining, and deep learning techniques to process the data generated during the crowdsourced testing process, to facilitate the management of crowdsourced testing, and to improve the quality of crowdsourced testing.

This book elaborates on the six pillars of a healthy and standardized real-estate brokerage industry: the generation, distribution and matching of information; the transaction system; circulation finance; mobile Internet; the supervision system; and professional brokers. With each of these pillars playing a role, they also mutually interact to constitute an integrated framework that regulates the brokerage industry. Presenting practicable, extensive and cutting-edge research that encompasses various areas of the industry and detailed case studies from around the globe, the book provides a number of suggestions that have already been adopted and have begun to take effect. It also explores the frontiers of the real-estate brokerage industry - the incorporation of the internet, the blurred boundary between online and offline service where brokerages are moving online, client acquisition is via the internet, and benchmark companies are focusing more on their trading service capacity, each building their own controllable trading environment.

This book adopted 66 brand crisis events as research samples taking place from 2010 to 2016 on social media (Chinese Weibo), performs research on influence mechanism of brand-crisis information-sharing behavior on social media from contextual perspective. The book explores into the fluctuation characteristics of information-sharing behavior, the contextual influence factors, both the static and dynamic mechanism of information-sharing behavior, and regulation measures of crisis information sharing behavior. The important features of the book are reflected in accurate analysis of the autocorrelation, trend characteristics, periodic characteristics and cluster characteristics of the fluctuation of crisis information sharing behavior, and deep exploration of dynamic mechanism and static mechanism of the time lag characteristics, impulsive disturbance, and marginal influence of the impact of information sharing behavior from perspective of situational factors. The book mainly focuses on the field of brand crisis management, and construct the formation and evolution mechanism of brand crisis information sharing behavior from both vertical and horizontal dimensions through a combination of theoretical exposition and case analysis, so that readers can got a clear understanding of brand crisis information communication and management through dimension reduction. The book can be used as a textbook for undergraduates and postgraduates in economics and management in colleges and universities, can also be a reference for business managers, scientific researchers and others interested in the field of crisis management.

This book adopted 66 brand crisis events as research samples taking place from 2010 to 2016 on social media (Chinese Weibo), performs research on influence mechanism of brand-crisis information-sharing behavior on social media from contextual perspective. The book explores into the fluctuation characteristics of information-sharing behavior, the contextual influence factors, both the static and dynamic mechanism of information-sharing behavior, and regulation measures of crisis information sharing behavior. The important features of the book are reflected in accurate analysis of the autocorrelation, trend characteristics, periodic characteristics and cluster characteristics of the fluctuation of crisis information sharing behavior, and deep exploration of dynamic mechanism and static mechanism of the time lag characteristics, impulsive disturbance, and marginal influence of the impact of information sharing behavior from perspective of situational factors. The book mainly focuses on the field of brand crisis management, and construct the formation and evolution mechanism of brand crisis information sharing behavior from both vertical and horizontal dimensions through a combination of theoretical exposition and case analysis, so that readers can got a clear understanding of brand crisis information  communication and management through dimension reduction. The book can be used as a textbook for undergraduates and postgraduates in economics and management in colleges and universities, can also be a reference for business managers, scientific researchers and others interested in the field of crisis management.

This book constitutes the proceedings of the 21st China National Conference on Computational Linguistics, CCL 2022, held in Nanchang, China, in October 2022. The 22 full English-language papers in this volume were carefully reviewed and selected from 293 Chinese and English submissions. The conference papers are categorized into the following topical sub-headings: Linguistics and Cognitive Science; Fundamental Theory and Methods of Computational Linguistics; Information Retrieval, Dialogue and Question Answering; Text Generation and Summarization; Knowledge Graph and Information Extraction; Machine Translation and Multilingual Information Processing; Minority Language Information Processing; Language Resource and Evaluation; NLP Applications.

General Fractional Derivatives with Applications in Viscoelasticity introduces the newly established fractional-order calculus operators involving singular and non-singular kernels with applications to fractional-order viscoelastic models from the calculus operator viewpoint. Fractional calculus and its applications have gained considerable popularity and importance because of their applicability to many seemingly diverse and widespread fields in science and engineering. Many operations in physics and engineering can be defined accurately by using fractional derivatives to model complex phenomena. Viscoelasticity is chief among them, as the general fractional calculus approach to viscoelasticity has evolved as an empirical method of describing the properties of viscoelastic materials. General Fractional Derivatives with Applications in Viscoelasticity makes a concise presentation of general fractional calculus.