An on-line library of design patterns

This project is to develop an on-line library to help software engineers who utilize design patterns for developing e-commerce applications it translates generic design patterns to concrete design patterns. The graphical user interface was developed to allow the user to develop their own design patterns by modifying or changing stored design patterns

Using Intelligent Agents to Build E-Business Software

Agent architectures are gaining popularity for building open, distributed, and evolving software required by e-commerce applications. Unfortunately, despite considerable work in software architecture during the last decade, few research efforts have aimed at truly defining patterns and languages for agent architectural design. This paper proposes a modern approach based on organizational structures and architectural description languages to define and specify agent architectures notably in the case of e-commerce system design

Three Essays on Big Data Consumer Analytics in E-Commerce

Consumers are increasingly spending more time and money online. Business to consumer e-commerce is growing on average of 20 percent each year and has reached 1.5 trillion dollars globally in 2014. Given the scale and growth of consumer online purchase and usage data, firms\u27 ability to understand and utilize this data is becoming an essential competitive strategy. But, large-scale data analytics in e-commerce is still at its nascent stage and there is much to be learned in all aspects of e-commerce. Successful analytics on big data often require a combination of both data mining and econometrics: data mining to reduce or structure (from unstructured data such as text, photo, and video) large-scale data and econometric analyses to truly understand and assign causality to interesting patterns. In my dissertation, I study how firms can better utilize big data analytics and specific applications of machine learning techniques for improved e-commerce using theory-driven econometrical and experimental studies. I show that e-commerce managers can now formulate data-driven strategies for many aspect of business including cross-selling via recommenders on sales sites to increasing brand awareness and leads via social media content-engineered-marketing. These results are readily actionable with far-reaching economical consequences

Digital Transformation in Europe: An Analysis of the Digital Divide in e-Commerce and e-Government

The study analyzes the digital divide across 29 European countries using data from Eurostat in the context of EU policy to promote digital transformation in e-commerce and e-government. Using multivariate statistical methods, findings show continuing digital performance asymmetries with countries clustered into three groupings: leaders, followers, and laggards. As access to information and communications technology increases among Europe’s citizens, the drive towards digital transformation will only be achieved by increasing patterns of use through the development of fit-for-purpose digital platforms, websites, and applications

A Topic Modeling Guided Approach for Semantic Knowledge Discovery in e-Commerce

The task of mining large unstructured text archives, extracting useful patterns and then organizing them into a knowledgebase has attained a great attention due to its vast array of immediate applications in business. Businesses thus demand new and efficient algorithms for leveraging potentially useful patterns from heterogeneous data sources that produce huge volumes of unstructured data. Due to the ability to bring out hidden themes from large text repositories, topic modeling algorithms attained significant attention in the recent past. This paper proposes an efficient and scalable method which is guided by topic modeling for extracting concepts and relationships from e-commerce product descriptions and organizing them into knowledgebase. Semantic graphs can be generated from such a knowledgebase on which meaning aware product discovery experience can be built for potential buyers. Extensive experiments using proposed unsupervised algorithms with e-commerce product descriptions collected from open web shows that our proposed method outperforms some of the existing methods of leveraging concepts and relationships so that efficient knowledgebase construction is possible