Adopting Web Feed and Agent Technologies for Supporting Asynchronous Web Interactions and Constructing E-Commerce Applications

隨著電子商務的發展以及網路經濟的起飛，越來越多的使用者除了使用網際網路(Internet)取得 所需的資訊外，亦開始透過各式手持裝置進行多樣化的網路交易(如：Amazon/Yahoo!/淘寶網線上 購物、Apple iTunes/App Store 線上數位內容…等等)而獲取各形式之資訊、產品及服務。在使用者進 行網路交易的過程中，若電子商務的服務因為伺服器軟硬體故障或網路連線問題而導致服務中斷， 原可取得的訂單將隨之消失，亦無法取得消費者的信任。本研究以網路供餵技術為基礎，搭配代理 人的使用設計出一套能夠應用在可攜式裝置上，並具有使用簡單、高度可用性、輕量化，可用以支 援非同步式網路互動之電子商務容錯服務架構。採用此架構可以改善企業服務並提高電子商務網站 的彈性及可用性，讓企業把握住每一個可能的交易機會。With the continuous development of e-commerce and Internet economy, more and more people not only obtain necessary information through the Internet but also adopt various portable devices to conduct online transactions (such as Amazon/Yahoo!/Alibaba online shopping, Apple iTunes App Store, etc.) to acquire various information, products, and services. However, if the service is interrupted due to any server or network connectivity or availability problems while performing online transaction tasks, an e-commerce website might lose business opportunities and even their customers’ trust. The main purpose of this study is to utilize the Web Feed technology together with agent technology to design a simple, highly available, and light weight e-commerce fault tolerant service architecture applicable in a multimodal pervasive environment for supporting asynchronous Web interactions. This framework may be utilized to enhance enterprise services and improve the flexibility and availability of e-commerce websites, thus retaining more business opportunities

Forecasting financial markets using high-frequency trading data: Examination with strongly typed genetic programming

Market regulators around the world are still debating whether high-frequency trading (HFT) plays a positive or negative role in market quality. We develop an artificial futures market populated with high-frequency traders (HFTs) and institutional traders using Strongly Typed Genetic Programming (STGP) trading algorithm. We simulate real-life futures trading at the millisecond time frame by applying STGP to E-Mini S&P 500 data stamped at the millisecond interval. A direct forecasting comparison between HFTs and institutional traders indicate the superiority of the former. We observe that the negative implications of high-frequency trading in futures markets can be mitigated by introducing a minimum resting trading period of less than 50 milliseconds. Overall, we contribute to the e-commerce literature by showing that minimum resting trading order period of less than 50 milliseconds could lead to HFTs facing a queuing risk resulting in a less harmful market quality effect. One practical implication of our study is that we demonstrate that market regulators and/or e-commerce practitioners can apply artificial intelligence tools such as STGP to conduct trading behavior-based profiling. This can be used to detect the occurrence of new HFT strategies and examine their impact on the futures market

Agent-based system design for B2B electronic commerce

ABSTRACT: Agent-based systems are increasingly used to support business-to-business (B2B) electronic commerce and other Internet-based transactions. The design complexity resulting from the multiple interconnected systems in these domains has to be managed in order to reduce costs and time to market. This paper introduces the Role-Algebraic Multi-Agent System Design (RAMASD) approach. RAMASD utilizes role models as reusable system-building blocks and a role algebra to capture the basic relations of roles. A two-sorted algebra is used to define the role algebra’s semantics. RAMASD reduces the complexity of designing agent-based B2B e-commerce systems by enabling designers to work at a high level of abstraction and by automatically allocating roles to agents according to applicable role models and design constraints. A case study concerning a B2B electronic market for the automotive industry demon-strates the applicability of RAMASD. The advantages and disadvantages of the proposed approach are discussed, and comparisons with relevant work are made