Realization of a news dissemination agent based on weighted association rules and text mining techniques

Huang, Chenn‐Jung; Liao, Jia-Jian; Yang, Dian-Xiu; Chang, Tun-Yu; Luo, Yun-Cheng

doi:10.1016/j.eswa.2010.02.078

Cited by 36 publications

(19 citation statements)

References 9 publications

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“…Agrawal and Srikant (1995) proposed a wellknown Apriori algorithm to efficiently find useful item sets and to obtain suitable association rules in the complex transaction database [20]. Huang et al (2010) developed the weighted association rule to realize the real-time text mining [21]. In this research, we modify this mechanism and consider the weight value into the personal stock trading recommendation service and modify with investors' preference and their location.…”

Section: Multi-agent Systems and Recommendation Modulementioning

confidence: 98%

“…In this research, we modify this mechanism and consider the weight value into the personal stock trading recommendation service and modify with investors' preference and their location. The weighted association rule could be indicated in the following [21], Let P be a group of m stock trading records as follows,…”

Section: Multi-agent Systems and Recommendation Modulementioning

confidence: 99%

See 1 more Smart Citation

Context-Aware for Smartphone Sensing in Over-the-Counter Market: Ambient Intelligence in Mobile Stock Markets

Chen

2013

2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

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An Ambient Intelligence (AmI) environment is primary developed using intelligent agents and wireless sensor networks. The intelligent agents could automatically obtain contextual information in real time using Near Field Communication (NFC) technique and wireless ad-hoc networks. In this research, we propose a stock trading and recommendation system with mobile devices (Android platform) interface in the over-the-counter market (OTC) environments. The proposed system could obtain the realtime financial information of stock price through a multiagent architecture with plenty of useful features. In addition, NFC is used to achieve a context-aware environment allowing for automatic acquisition and transmission of useful trading recommendations and relevant stock information for investors. Finally, AmI techniques are applied to successfully create smart investment spaces, providing investors with useful monitoring tools and investment recommendation.

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Section: Multi-agent Systems and Recommendation Modulementioning

confidence: 98%

Section: Multi-agent Systems and Recommendation Modulementioning

confidence: 99%

Context-Aware for Smartphone Sensing in Over-the-Counter Market: Ambient Intelligence in Mobile Stock Markets

Chen

2013

2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing

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“…This way the market sentiments were determined using the text analysis. Huang et al [15] proposed a system for financial news headline agent to support the investors through the "Buy" and "Sell" decision making in the stock market of Taiwan. It receives the realtime market news headlines, published by the leading electronic newspapers in Taiwan, and employs optimized text mining techniques along with weighted association rules to predict the fluctuation in the Taiwan Stock Exchange Financial Price Index of the next trading day.…”

Section: Previous Workmentioning

confidence: 99%

An Efficient System for Stock Market Prediction

Hussein

Hamed

Tolba

2015

Advances in Intelligent Systems and Computing

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Abstract. This paper presents an efficient system for accurate, confident, general and responsive stock market prediction, employing Artificial Neural Networks (ANN). For technical indicators, Multi-Layer Perceptron (MLP) ANN is used and trained with Kullback Leibler Divergence (KLD) learning algorithm because it converges fast in addition to offering generalization in the learning mechanism. On the other hand, Radial Basis Function Neural Network (RBFNN) trained with Localized Generalization Error (L-GEM) is used for candlesticks patterns. The accuracy, generalization and statistical-significance of the developed system were confirmed through various local and international data sets. Next, sensitivity analysis was conducted for the different parameters that influence the system efficiency metrics. In order to have responsive prediction, the proposed system was evolved, employing concurrent programming to get benefit from the off-the-shelf multi-core architectures. Then, the performance of the developed system was evaluated to confirm acceptance scalability and utilization.

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“…Some researchers have used social media sources, such as (Antweiler and Frank 2004;Das and Chen, 2007) where they incorporated blog messages and others such as in (Bollen and Mao, 2011;Vu et al, 2012) relied on text from Twitter to predict markets' movements. Another group used less noisy sources (Huang et al, 2010) where they utilised scheduled news announcements e.g. Henry ( Market data collected varied between intraday (5 min to 15 min to 1 hour) intervals (e.g.…”

Section: Summary Of Datasets Usedmentioning

confidence: 99%

News Sentiment Impact Analysis (NSIA) Framework

Qudah

Rabhi

2017

Lecture Notes in Business Information Processing

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The huge increase in online content has rapidly stepped up the challenges facing various entities such as organisations, businesses, governments. Dealing with this immense increase in information is beyond any human ability, as it requires massive efforts to go through huge volumes of posts/news to analyse and understand their content. In responding to this challenge, research has picked up in recent years to automatically analyse, and extract opinions/sentiment from online content. This thesis investigated the area of sentiment analysis and its impact on financial market entities. The thesis includes a review of the sentiment analysis processes, , an overview of sentiment analysis studies and their application to the financial markets domain. The literature shows a gap in defining systematic and reusable evaluation processes, for users to automatically conduct impact analysis of sentiment datasets in different financial contexts. In addressing the research gap the thesis proposes a framework called News Sentiment Impact Analysis (NSIA) which consists of three components which are a conceptual data model, a software architecture, and a set of use cases. The key component which is the conceptual data model captures three sets of parameters: the financial context parameters, the sentiment related parameters, and the impact measure parameters. The CPD model is supported by a software architecture, which consists of a GUI, Business, and Data layers. The main use case allows the analyst to define the CPD parameters using the provided GUI layer and trigger the impact analysis process. To evaluate the proposed framework, a prototype is implemented. Three case studies have been conducted to evaluate the different aspects of the proposed framework. ORIGINALITY STATEMENT 'I hereby declare that this submission is my own work and to the best of my knowledge it contains no materials previously published or written by another person, or substantial proportions of material which have been accepted for the award of any other degree or diploma at UNSW or any other educational institution, except where due acknowledgement is made in the thesis. Any contribution made to the research by others, with whom I have worked at UNSW or elsewhere, is explicitly acknowledged in the thesis. I also declare that the intellectual content of this thesis is the product of my own work, except to the extent that assistance from others in the project's design and conception or in style, presentation and linguistic expression is acknowledged.'

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Realization of a news dissemination agent based on weighted association rules and text mining techniques

Cited by 36 publications

References 9 publications

Context-Aware for Smartphone Sensing in Over-the-Counter Market: Ambient Intelligence in Mobile Stock Markets

Context-Aware for Smartphone Sensing in Over-the-Counter Market: Ambient Intelligence in Mobile Stock Markets

An Efficient System for Stock Market Prediction

News Sentiment Impact Analysis (NSIA) Framework

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