Automated question answering from lecture videos: NLP vs. pattern matching

Jinwei Cao; Dmitri Roussinov; José Antonio Robles-Flores; Jay F. Nunamaker

Automated question answering from lecture videos: NLP vs. pattern matching

Jinwei Cao, Dmitri Roussinov, José Antonio Robles-Flores, Jay F. Nunamaker

Management Information Systems

Research output: Contribution to journal › Conference article › peer-review

11 Scopus citations

Abstract

This paper explores the feasibility of automated question answering from lecture video materials used in conjunction with PowerPoint slides. Two popular approaches to question answering are discussed, each separately tested on the text extracted from videotaped lectures: 1) the approach based on Natural Language Processing (NLP) and 2) a self-learning probabilistic pattern matching approach. The results of the comparison and our qualitative observations are presented. The advantages and shortcomings of each approach are discussed in the context of video applications for e-learning or knowledge management.

Original language	English (US)
Pages (from-to)	43
Number of pages	1
Journal	Proceedings of the Annual Hawaii International Conference on System Sciences
State	Published - 2005
Event	38th Annual Hawaii International Conference on System Sciences - Big Island, HI, United States Duration: Jan 3 2005 → Jan 6 2005

ASJC Scopus subject areas

General Engineering

Cite this

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title = "Automated question answering from lecture videos: NLP vs. pattern matching",

abstract = "This paper explores the feasibility of automated question answering from lecture video materials used in conjunction with PowerPoint slides. Two popular approaches to question answering are discussed, each separately tested on the text extracted from videotaped lectures: 1) the approach based on Natural Language Processing (NLP) and 2) a self-learning probabilistic pattern matching approach. The results of the comparison and our qualitative observations are presented. The advantages and shortcomings of each approach are discussed in the context of video applications for e-learning or knowledge management.",

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AB - This paper explores the feasibility of automated question answering from lecture video materials used in conjunction with PowerPoint slides. Two popular approaches to question answering are discussed, each separately tested on the text extracted from videotaped lectures: 1) the approach based on Natural Language Processing (NLP) and 2) a self-learning probabilistic pattern matching approach. The results of the comparison and our qualitative observations are presented. The advantages and shortcomings of each approach are discussed in the context of video applications for e-learning or knowledge management.

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Y2 - 3 January 2005 through 6 January 2005

ER -

Automated question answering from lecture videos: NLP vs. pattern matching

Abstract

ASJC Scopus subject areas

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