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Metadata domain-knowledge driven search engine in "hypermanymedia " e-learning resources.
| Content Provider | CiteSeerX |
|---|---|
| Author | Zhuhadar, Leyla Nasraoui, Olfa Wyatt, Robert |
| Abstract | In this paper, we exploit the synergies between Information Retrieval and E-learning by describing the design of a system that uses “Information Retrieval ” in the context of the Web and “E-learning”. With the exponential growth of the web, we noticed that the “general-purpose ” of web applications started to diminish and more domain-specific or personal aspects started to rise, e.g., the trend of personalized web pages, a user’s history of browsing and purchasing, and topical/focused search engines. The huge explosion of the amount of information on the web makes it difficult for online students to find specific information with a specific media format unless a prior analysis has been made. In this paper, we present a metadata domain-driven search engine that indexes text, powerpoint, audio, video, podcast, and vodcast lectures. These lectures are stored in a prototype “HyperManyMedia ” E-learning web-based platform. Each lecture in this platform has been tagged with metadata using the domain-knowledge of these resources. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Hypermanymedia E-learning Resource Metadata Domain-knowledge Driven Search Engine Information Retrieval Exponential Growth Prototype Hypermanymedia E-learning Web-based Platform Huge Explosion Specific Information Online Student Personalized Web Page Metadata Domain-driven Search Engine Specific Medium Format Vodcast Lecture User History Search Engine Web Application Prior Analysis Personal Aspect |
| Content Type | Text |
