Learn More
In electronic commerce applications, prospective buyers may be interested in receiving recommendations to assist with their purchasing decisions. Previous research has described two main models for automated recommender systems-collaborative filtering and the knowledge-based approach. In this paper, we present an architecture for designing a hybrid(More)
The Machine Learning (ML) field has gained its momentum in almost any domain of research and just recently has become a reliable tool in the medical domain. The empirical domain of automatic learning is used in tasks such as medical decision support, medical imaging, protein-protein interaction, extraction of medical knowledge, and for overall patient(More)
Often in multi-agent systems, agents interact with other agents to fulfill their own goals. Trust is, therefore, considered essential to make such interactions effective. This work describes a trust model that augments fuzzy logic with Q-learning to help trust evaluating agents select beneficial trustees for interaction in uncertain, open, dynamic, and(More)
As online social networks (OSN) attempt to mimic real life social networks, we have made progress towards using OSNs to provide us with data to allow for richer and more robust online communications. In this paper, we present a novel approach towards socially-aware email. Currently, email provides too little control to the recipient. Our approach, dubbed(More)
Often in open multiagent systems, agents interact with other agents to meet their own goals. Trust is, therefore, considered essential to make such interactions effective. However, trust is a complex, multifaceted concept and includes more than just evaluating others’ honesty. Many trust evaluation models have been proposed and implemented in different(More)
Social network popularity continues to rise as they broaden out to more users. Hidden away within these social networks is a valuable set of data that outlines everyone's relationships. Networks have created APIs such as the Facebook Development Platform and OpenSocial that allow developers to create applications that can leverage user information. However,(More)
In electronic commerce applications, prospective buyers may be interested in receiving recommendations to assist with their purchasing decisions. Previous research has described two main models for automated recommender systems: collaborative filtering and knowledge-based approaches. In this paper, we present an architecture for designing a hybrid(More)
The ability of the rapid-capacitive discharge approach to access optimal viscosity ranges in metallic glasses for thermoplastic processing is explored. Using high-speed thermal imaging, the heating uniformity and stability against crystallization of Zr35Ti30Cu7.5Be27.5 metallic glass heated deeply into the supercooled region is investigated. The method(More)
In any e-commerce application, the recommender systems play a vital role as they assist the prospective buyers in making proper decisions on the basis of the recommendations that the system provides. Recommender systems aim at providing the users with effective recommendations based on their intuitions and preferences. The two very old techniques commonly(More)
This paper examines the collaborative process of developing Arc, a computer numerical controlled (CNC) engraving tool for ceramics that offers a new window onto traditional forms of craft. In reflecting on this case and scholarship from the social sciences, we make two contributions. First, we show that fabrication tools may integrate multiple and distinct(More)