2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology最新文献_第8页

Using Multidimensional Clustering Based Collaborative Filtering Approach Improving Recommendation Diversity 基于多维聚类的协同过滤方法提高推荐多样性

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.229

Xiaohui Li, T. Murata

引用次数: 39

Enhancing LOD Complex Query Building with Context 使用上下文增强LOD复杂查询构建

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.94

R. Brandão, P. Maio, Nuno Silva

引用次数: 3

A Simple and Fast Multi-instance Classification via Support Vector Machine 基于支持向量机的简单快速多实例分类

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.50

Zhiquan Qi, Ying-jie Tian, Yong Shi

引用次数: 1

Latent Business Networks Mining: A Probabilistic Generative Model 潜在商业网络挖掘:一个概率生成模型

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.195

Wenping Zhang, Raymond Y. K. Lau, Yunqing Xia, Chunping Li, Wenjie Li

引用次数: 6

Knowledge-Driven Autonomous Commodity Trading Advisor 知识驱动的自主商品交易顾问

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.208

Yee Pin Lim, Shih-Fen Cheng

{"title":"Knowledge-Driven Autonomous Commodity Trading Advisor","authors":"Yee Pin Lim, Shih-Fen Cheng","doi":"10.1109/WI-IAT.2012.208","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.208","url":null,"abstract":"The myth that financial trading is an art has been mostly destroyed in the recent decade due to the proliferation of algorithmic trading. In equity markets, algorithmic trading has already bypass human traders in terms of traded volume. This trend seems to be irreversible, and other asset classes are also quickly becoming dominated by the machine traders. However, for asset that requires deeper understanding of physicality, like the trading of commodities, human traders still have significant edge over machines. The primary advantage of human traders in such market is the qualitative expert knowledge that requires traders to consider not just the financial information, but also a wide variety of physical constraints and information. However, due to rapid technology changes and the \"invasion\" of cash-rich hedge funds, even this traditionally human-centric asset class is crying for help in handling increasingly complicated and volatile environment. In this paper, we propose an adaptive trading support framework that allows us to quantify expert's knowledge to help human traders. Our method is based on a two-state switching Kalman filter, which updates its state estimation continuously with real-time information. We demonstrate the effectiveness of our approach in palm oil trading, which is becoming more and more complicated in recent years due to its new usage in producing biofuel. We show that the two-state switching Kalman filter tuned with expert domain knowledge can effectively reduce prediction errors when compared against traditional single-state econometric models. With a simple back test, we also demonstrate that even a slight decrease in the prediction errors can lead to significant improvement in the trading performance of a naive trading algorithm.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131932224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Self-Adjustable Trust-Based Energy Efficient Routing for Smart Grid Systems 基于自调节信任的智能电网节能路由

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.89

Ming-Sen Xiang, Q. Bai, William Liu

{"title":"Self-Adjustable Trust-Based Energy Efficient Routing for Smart Grid Systems","authors":"Ming-Sen Xiang, Q. Bai, William Liu","doi":"10.1109/WI-IAT.2012.89","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.89","url":null,"abstract":"Smart Grid is the trend of next generation electrical power system which makes the power grid intelligent and energy efficient. It requires high level of network reliability to support two-way communication among electrical services, electrical units such as smart meters, and applications. The wireless mesh network infrastructure can provide redundant routes for the smart grid communication network to ensure the network availability. Also due to its high level of flexibility and scalability features that make it become a promising solution for smart grid. However, wireless mesh network infrastructure are vulnerable to some cyber attacks which need to be addressed. In this paper, we proposed and implemented a new trust-based geographical routing protocol, named as Dynamic Trust Elective Geo Routing (DTEGR), which use the trust factor with a dynamic threshold value to generate a trust forwarding list, then it uses distance factor as routing metric to decide the next hop from the trust forwarding list. The simulation studies have confirmed our new DTEGR algorithm able to achieve better routing performance in different network scenarios, and also to achieve high level of reliable data transmission in smart grid communication network.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130428929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

A Comparative Study of Cross-Lingual Sentiment Classification 跨语言情感分类的比较研究

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.54

Xiaojun Wan

引用次数: 26

A Ubiquitous Image Tagging System Using User Context 基于用户上下文的泛在图像标注系统

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.249

Shatabdi Kundu, S. Chaudhury

引用次数: 1

ABiNeS: An Adaptive Bilateral Negotiating Strategy over Multiple Items ABiNeS:一种多项目的适应性双边谈判策略

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.72

Jianye Hao, Ho-fung Leung

{"title":"ABiNeS: An Adaptive Bilateral Negotiating Strategy over Multiple Items","authors":"Jianye Hao, Ho-fung Leung","doi":"10.1109/WI-IAT.2012.72","DOIUrl":"https://doi.org/10.1109/WI-IAT.2012.72","url":null,"abstract":"Multi-item negotiations surround our daily life and usually involve two parties that share common or conflicting interests. Effective automated negotiation techniques should enable the agents to adaptively adjust their behaviors depending on the characteristics of their negotiating partners and negotiation scenarios. This is complicated by the fact that the negotiation agents are usually unwilling to reveal their information (strategies and preferences) to avoid being exploited during negotiation. In this paper, we propose an adaptive negotiation strategy, called ABiNeS, which can make effective negotiations against different types of negotiating partners. The ABiNeS agent employs the non-exploitation point to adaptively adjust the appropriate time to stop exploiting the negotiating partner and also predicts the optimal offer for the negotiating partner based on reinforcement-learning based approach. Simulation results show that the ABiNeS agent can perform more efficient exploitations against different negotiating partners, and thus achieve higher overall utilities compared with the state-of-the-art negotiation strategies in different negotiation scenarios.","PeriodicalId":220218,"journal":{"name":"2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133794194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 39

A Hybrid Cooperative Behavior Learning Method for a Rule-Based Shout-Ahead Architecture 基于规则的提前喊出体系结构的混合合作行为学习方法

2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Pub Date : 2012-12-04 DOI: 10.1109/WI-IAT.2012.33

Sanjeev Paskaradevan, J. Denzinger

引用次数: 9