Development of generic e-learning frame work and semantic search engine

Abstract

Web engineering promotes systematic, disciplined and quantifiable approaches for the successful development of high-quality web-based systems and applications. It focuses on the methodologies, techniques and tools for the development of web applications. They are Generic E-Learning Framework and Semantic Search Engine System. E-Learning has transformed the traditional premise of educational theorists. Analysis model is based on newly proposed E-Learning architecture. Moreover, it includes the guidelines to deploy this framework. The entire work is standing on the basement of proven pedagogies suggested by various authors (Paris 2004, Benmohamed et al 2005, Yang et al 2007). In addition to this, the isolated efforts on E-Learning are aggregated and given as one single perfect solution. Each layer consists of different process components such as standard interface, content management system, delivery specification component, evaluation management component, user data repository, content repository etc. The proposed work comprises three vital elements known as content authoring, content delivery and control and management. This framework can be developed using three fundamental methodologies such as Use-case Driven, Architecture Driven and Iterative and Incremental technique. Use cases provide a means for capturing requirements, organizing activities and focusing the team. Architecture is developed and validated by early prototypes, and then the rest of the system is built around it. The second part of the thesis is the development of semantic search engine. Finally, documents are ranked in the ranker module. The performance of the system is measured using precision and recall methods. In the proposed system, two types of documents are considered for analysis. They are HTML documents and XML documents. Among them, XML documents have taken less time for retrieving documents than HTML documents. Also, XML concepts are used for efficient semantic information retrieval.