Trading agent concept is very useful for tradingstrategy design and market mechanism design. In thispaper, we introduce the use of trading agent for marketsurveillance. Market surveillance agents can bedeveloped for market surveillance officers andmanagement teams to present them alerts and...

The aims and objectives of data mining is to discover actionable knowledge of maininterest to real user needs, which is one of Grand Challenges in KDD. Most extant data miningis a data-driven trial-an-error process. Patterns discovered via predefined models in the aboveprocess are often of...

From a data mining perspective, sequence classification is to build a classifier using frequent sequential patterns. However, mining for a complete set of sequential patterns on a large dataset can be extremely time-consuming and the large number of patterns discovered also makes the pattern...

Activity data accumulated in real life, such as terrorist activities and governmental customer contacts, present special structural and semantic complexities. Activity data may lead to or be associated with significant business impacts, and result in important actions and decision making leading...

Recently, a new data mining methodology, Domain Driven Data Mining (D3M), has been developed. On top of data-centered pattern mining, D3M generally targets the actionable knowledge discovery under domain-specific circumstances. It strongly appreciates the involvement of domain intelligence in...

Stock trading plays an important role for supporting profitable stock investment. In particular, more and more data mining-based technical trading rules have been developed and used in stock trading systems to assist investors with their smart trading decisions. However, many mined trading rules...

Trading agents are very useful for developing andback-testing quality trading strategies to support smarttrading actions in the market. However, the existingtrading agent research mainly focuses on simple andsimulated strategies. As a result, there exists a big gapbetween academia and business...

Fully taking into account the hints possibly hidden in the absent data,this paper proposes a new criterion when selecting attributes for splitting tobuild a decision tree for a given dataset. In our approach, it must pay a certaincost to obtain an attribute value and pay a cost if a prediction...

This paper applies Bayesian network tecbnique tomodel and inference tbe uncertain relationsbips among costfactors and benefit factors in E-services. A cost-benefitfactor-relation modelproposed in our previous study is consideredas domain knowledgeand tbe data collectedtbrougb a survey is...