STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Multimedia Technology & Recent Advancements

Multimedia Abstraction in E-learning via LexRank and Latent Semantic Analysis

  1. Madhura M. Lambe
  2. Muneeza Mushtaq
  3. Deepak N. R.
  4. Simran Pal R.

Abstract

In today’s era of abundant online information, it is essential to offer an efficient and precise solution for accessing information. With the growing usage of the Internet and smartphones, there has been a consistent rise in online education, entertainment, and various other activities. However, there are instances when we lack the time to delve into lengthy content like videos or podcasts. Hence, there is a need for a method to condense lengthy materials into brief statements while retaining the original meaning. Automatic summarization comes into play here. Its primary goal is to extract concise summaries from vast amounts of digital data accurately and efficiently. To achieve this, we employ natural language processing techniques, utilizing algorithms like LexRank and latent semantic analysis.

Keywords

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