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- W2156367747 abstract "In this paper, we exploit the synergies between 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." @default.
- W2156367747 created "2016-06-24" @default.
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- W2156367747 date "2008-01-01" @default.
- W2156367747 modified "2023-09-27" @default.
- W2156367747 title "Metadata domain-knowledge driven search engine in HyperManyMedia E-learning resources" @default.
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- W2156367747 doi "https://doi.org/10.1145/1456223.1456298" @default.
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