Yong Shi's research while affiliated with Chinese Academy of Sciences and other places

Publications (94)

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Technical analysis indicators are widely used in the field of quantitative investment, and they are usually utilized to assist in the search for profitable buy and sell points. In order to make better use of technical indicators, a method of trying to improve the performance of technical indicators by using neural network models is proposed in this...
Article
Due to the contradiction between the finiteness of resources and people’s infinite demand for them, we cannot deny the impact of the limited resources on human behavior. To this end, we construct a novel resource-based conditional interaction model from a tiny perspective, in which not only can limited resources be redistributed among the populatio...
Article
Herding has a great impact on stock market fluctuations, and it is possible for researchers to analyze the herding effect due to the recent popularity of mobile Internet and the development of big data analysis technology. In this paper, we propose both investor-based and stock-based sentiment propagation networks of Chinese stock markets based on...
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Most existing algorithms of anomaly detection are suitable for static data where all data are available during detection but are incapable of handling dynamic data streams. In this study, we proposed an improved iLOF (incremental local outlier factor) algorithm based on the landmark window model, which provides an efficient method for anomaly detec...
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Literature is prolific with metaheuristics for solving continuous optimisation problems. But, in practice, it is difficult to choose one appropriately for several reasons. First and foremost, ‘new’ metaheuristics are being proposed at an alarmingly fast rate, rendering impossible to know them all. Moreover, it is necessary to determine a good enoug...
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In stock trading markets, trade duration (i. e., inter-arrival times of trades) usually exhibits high uncertainty and excessive zero values. To forecast conditional distribution of trade duration, this study proposes a hybrid model called “DL-ZIACD” for short, which addresses the problem of excessive zero values by a zero-inflated distribution. Mea...
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The analysis of intraday financial time series is the basis of constructing intraday trading strategies which are usually less risky than overnight trading strategies. Correlations existed in intraday financial series may imply there are some potential patterns of price movements. In this work, we propose a clustering framework based on multi-scale...
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Stock market serves as an important indicator of today’s economy. Predicting the price fluctuation of stocks and acquiring the maximum gains has been the main concern of investors. In recent years, deep learning models are widely applied to stock market prediction and have achieved good performances. However, the majority of these deep learning bas...
Preprint
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Artificial stock market simulation based on agent is an important means to study financial market. Based on the assumption that the investors are composed of a main fund, small trend and contrarian investors characterized by four parameters, we simulate and research a kind of financial phenomenon with the characteristics of pyramid schemes. Our sim...
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The liquidity risk factor of security market plays an important role in the formulation of trading strategies. A more liquid stock market means that the securities can be bought or sold more easily. As a sound indicator of market liquidity, the transaction duration is the focus of this study. We concentrate on estimating the probability density fun...
Preprint
The liquidity risk factor of security market plays an important role in the formulation of trading strategies. A more liquid stock market means that the securities can be bought or sold more easily. As a sound indicator of market liquidity, the transaction duration is the focus of this study. We concentrate on estimating the probability density fun...
Article
With the development of Internet and big data, it is more convenient for investors to share opinions or have a discuss with others via the web, which creates massive unstructured data. These data reflect investors' emotions and their investment intentions, and it will further affect the movement of the stock market. Although researchers have been a...
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There is a colourful palette of metaheuristics for solving continuous optimisation problems in the literature. Unfortunately, it is not easy to pick a suitable one for a specific practical scenario. Moreover, oftentimes the selected metaheuristic must be tuned until finding adequate parameter settings. Therefore, this work presents a framework base...
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Metaheuristics have become a widely used approach for solving a variety of practical problems. The literature is full of diverse metaheuristics based on outstanding ideas and with proven excellent capabilities. Nonetheless, oftentimes metaheuristics claim novelty when they are just recombining elements from other methods. Hence, the need for a stan...
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Based on the authors’ previous work on the research on the evaluation of artificial intelligence (AI) intelligence quotient and the Standard Intelligent Model, this paper proposes three laws of intelligence for interpreting the concepts of intelligence, wisdom, consciousness, life and non-life. The first law is called “M Law of Intelligence” where...
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The design of fusion engines is a subject of great importance in a variety of fields. In this paper, we focus on the problem of linear fusion at the feature level for multiple signal matrices with noises, with the features being extremal eigenvectors. When given multiple similarity matrices, the objective is to find an estimate of the latent signal...
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The outbreak of COVID-19 seriously challenges every government for its capacity and management of public health systems facing the catastrophic emergency. Culture and anti-epidemic policy do not necessarily conflict each other. All countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcom...
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Deep learning-based sentiment analysis (SA) methods have drawn more attention in recent years, which calls for more precise word embedding methods. This article proposes SentiVec, a kernel optimization function system for sentiment word embedding, which is based on two phases. The first phase is a supervised learning method, and the second phase co...
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The rapid development of artificial intelligence has brought the artificial intelligence threat theory as well as the problem about how to evaluate the intelligence level of intelligent products. Both need to find a quantitative method to evaluate the intelligence level of intelligence systems, including human intelligence. Based on the standard in...
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The stock market is a complex system with unpredictable stock price fluctuations. When the positive feedback in the market amplifies, the systemic risk will increase rapidly. During the last 30 years of development, the mechanism and governance system of China’s stock market have been constantly improving, but irrational shocks have still appeared...
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In many disciplines, the evaluation of algorithms for processing massive data is a challenging research issue. However, different algorithms can produce different or even conflicting evaluation performance, and this phenomenon has not been fully investigated. The motivation of this paper aims to propose a solution scheme for the evaluation of clust...
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Concepts have been adopted in concept-cognitive learning (CCL) and conceptual clustering for concept classification and concept discovery. However, the standard CCL algorithms are incapable of tackling continuous data directly, and some standard conceptual clustering methods mainly focus on the attribute information, ignoring the object information...
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Background COVID-19 has spread to 6 continents. Now is opportune to gain a deeper understanding of what may have happened. The findings can help inform mitigation strategies in the disease-affected countries. Methods In this work, we examine an essential factor that characterizes the disease transmission patterns: the interactions among people. We...
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Traffic prediction is a complex, nonlinear spatiotemporal relationship modeling task with the randomness of traffic demand, the spatial and temporal dependency between traffic flows, and other recurrent and nonrecurrent factors. Based on the ability to learn generic features from history information, deep learning approaches have been recently appl...
Preprint
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There are various types of pyramid schemes which have inflicted or are inflicting losses on many people in the world. We propose a pyramid scheme model which has the principal characters of many pyramid schemes appeared in recent years: promising high returns, rewarding the participants recruiting the next generation of participants, and the organi...
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Text is a typical example of unstructured and heterogeneous data in which massive useful knowledge is embedded. Sentiment analysis is used to analyze and predict sentiment polarities of the text. This paper provides a survey and gives comparative analyses of the latest articles and techniques pertaining to lexicon-based, traditional machine learnin...
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With the explosion of social media networks, many modern applications are concerning about people's connections, which leads to the so-called social computing. An elusive question is to study how opinion communities form and evolve in real-world networks with great individual diversity and complex human connections. In this paper, we attempt to mod...
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Financial data forecasting is one of the most important areas in financial markets. In the stock market, if the stock falls or rises to a point and then rises or falls for a long time, these points are turning points (TPs). Everyone wants to buy or sell stocks at the TP to maximize profits. This paper integrates the piecewise linear representation...
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This paper uses an agent-based model to study the sentiment contagion of interacting investors in China. We use text mining techniques to identify investor sentiment in stock forum, and then estimate the parameters of the sentiment contagion model to analyze sentiment formation from individual perspective. The empirical results suggest that the int...
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Concept-cognitive learning (CCL) is an emerging field of concerning incremental concept learning and dynamic knowledge processing in the context of dynamic environments. Although CCL has been widely researched in theory, the existing studies of CCL have one problem: the concepts obtained by CCL systems do not have generalization ability. In the mea...
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Blockchains have attracted worldwide attention in recent years. With the increasing number of public blockchains, the evaluation of public blockchains becomes meaningful. This paper aims to make a comprehensive evaluation of public blockchains from multiple dimensions. Three first-level indicators and eleven second-level indicators are designed to...
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Word representation is one foundational research in natural language processing which full of challenges compared to other fields such as image and speech processing. It embeds words to a dense low-dimensional vector space and is able to learn syntax and semantics at the same time. But this representation only get one single vector for a word no ma...
Preprint
The unclear development direction of human society is a deep reason for that it is difficult to form a uniform ethical standard for human society and artificial intelligence. Since the 21st century, the latest advances in the Internet, brain science and artificial intelligence have brought new inspiration to the research on the development directio...
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Networked systems with high computational efficiency are desired in many applications ranging from sociology to engineering. Generally, the performance of the network computation can be enhanced by two ways: rewiring and weighting. In this paper, we proposed a new two-modes weighting strategy based on the concept of communication neighbor graph, wh...
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This paper studies a broad sample of investors’ online opinion posts on the largest stock forum in China. Using text mining methods with data cleaning, text representation, feature extraction, and two-step sentiment classification, the paper identifies individual investor sentiment and complies an index. Further, the investor sentiment index is app...
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Online travel and online travel culture developed fast in China recently years while useful knowledge still hidden under a large number of tourism reviews. Therefore, we need effective sentiment analysis methods to mine useful knowledge which can help tourism websites make decisions and improve their travel products. Some data-driven sentiment lexi...
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Online travel has developed dramatically during the past three years in China. This results in a large amount of unstructured data like tourism reviews from which it is hard to extract useful knowledge. In this paper, a DWWP system consisting of domain-specific new words detection (DW) and word propagation (WP) is presented. DW deals with the negli...
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Concept-cognitive learning (CCL) is a hot topic in recent years, and it has attracted much attention from the communities of formal concept analysis, granular computing and cognitive computing. However, the relationship among cognitive computing (CC), concept-cognitive computing (CCC), CCL and concept-cognitive learning model (CCLM) is not clearly...
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This paper applies sequence alignment method of bioinformatics to financial analysis to find hidden pattern from financial markets. Results of simulation suggest that sequence alignment method can be used to identify key points to inset, delete and replace data in time series, to find lead-lag relationship between two time series, and to analyze ma...
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In this paper, we propose the method based on sequence alignment to find patterns of stock returns. We use 5 minutes high frequency data of CSI 300 index to test this method, and find we can predict the sharply rise or drop for the stock returns according to patterns of the sample symbol sequence. The empirical analysis suggests it is possible to f...
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Intelligent Manufacturing has attracted global and continuous attention recent years, with more and more intelligent devices and systems applied in production. In this paper, we take China’s manufacturing listed firms to investigate the productivity difference between intelligent and general manufacturing firms. By the Cobb-Douglas production funct...
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Chinese segmentation has attracted amounts of attention in natural language processing in recent years and is the basis of web text mining. The article improved statistics-based method EMI, then we use improved approach to detect new words in tourism field. The result demonstrates that our method can detect new words significantly, especially in de...
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On September 5, 2015, the State Council of Chinese Government, China’s cabinet formally announced its Action Framework for Promoting Big Data (www.gov.cn, 2015). This is the milestone for China to catch up the global wave of big data. Since 2012 big data became a hot issue for scientific communities as well as the governments of many countries (Laz...
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Data is growing faster than ever before and is changing our daily life. However it is rather challenging to manage the big data [F. H. Cate, The big debate, Science 346 (2014) 810, J. Manyika, M. Chui, B. Brown, J. Bughin, R. Dobbs, C. Roxburgh and A. H. Byers, Big Data: The Next Frontier for Innovation, Competition, and Productivity (Mckinsey glob...
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Although artificial intelligence (AI) is currently one of the most interesting areas in scientific research, the potential threats posed by emerging AI systems remain a source of persistent controversy. To address the issue of AI threat,this study proposes a “standard intelligence model” that unifies AI and human characteristics in terms of four as...
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This paper focuses on overall and sub-process supply chain efficiency evaluation using a network slacks-based measure model and an undesirable directional distance model. Based on a case analysis of a leading Chinese B2C firm W, a two-stage supply chain structure covering procurementstock and inventory-sale management is constructed. The research s...
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Sentiment analysis in tourism domain has drawn much attention in past few years, which calls for more precise sentiment word embedding method. The article proposes a kernel optimization function for sentiment word embedding. And the method aims at integrating the semantic information, statistics information and sentiment information and maintains t...
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This research examines what affects operations efficiency and explains the paradox of high efficiency and low profits using a two-stage analytic framework. It provides a brief overview of efficiency evaluation research for e-commerce, and establishes a set of efficiency evaluation criteria, with the application of data envelopment analysis (DEA). T...
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Mining communities or clusters in networks is valuable in analyzing, designing, and optimizing many natural and engineering complex systems, e.g., protein networks, power grid, and transportation systems. Most of the existing techniques view the community mining problem as an optimization problem based on a given quality function(e.g., modularity),...
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Information technology outsourcing in China has developed fast, it plays a more and more important role in economic development of China. Economic analysis and early warning system of information technology outsourcing, which reflect the status of ITO, can promote the healthy development of the industry. This paper constructed the indicator system...
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To deal with the challenge of information overload, in this paper, we propose a financial news recommendation algorithm which help users find the articles that are interesting to read. To settle the ambiguity problem, a new presented OF-IDF method is employed to represent the unstructured text data in the form of key concepts, synonyms and synsets...
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This paper explores the relationship of search engine marketing, financing ability and e-commerce firm performance by the empirical research on China's B2C e-commerce firms. Results show that search engine marketing and business model has a strong positive relation with firm performance while financing ability has a negative effect on firm performa...