Showing papers by "Ahmed Ghoneim published in 2010"

Naive Bayes Classifier based Arabic document categorization

Abstract: Text Categorization aims to assign an electronic document to one or more categories based on its contents. Due to the rapid growth of the number of online Arabic documents, the information libraries and Arabic document corpus, automatic Arabic document classification becomes an important task. This paper suggests the use of rooting algorithm with Naive Bayes Classifier to the problem of document categorization of Arabic language and reports the algorithm performance in terms of error rate, accuracy, and micro-average recall measures. Our experimental study shows that using rooting algorithm with Naive Bayes (NB) Classifier gives ~62.23% average accuracy and decreases the dimensionality of the training documents.

Smart service: SOA business logic connectivity adaptation

Abstract: Nowadays, service connectivity adaptation grows to be one of the most important topic in SOC (Service Oriented Computing). Due to the increasing in accessing the business processes of the information systems, there is a lot of traffic to a specific part of its business logic (BL) that causes Bottlenecked. To solve this traffic problem, we need to adapt the business logic and the services connectivity. The adapted business logic makes the critical services as a common service that can be reached automatically. In this paper, we present a new framework to adapt the connectivity of the business process workflow. The main components of this proposed framework are the workflow parser, the smart service core, and the business logic generator. Finally, we illustrate the usage of the framework and the prototype by using a real case study obtained from a banking system.