Use of Action History Views for Indexing Continuous Media Objects

SummaryThis paper describes a method for extracting importance of slides in a lecture review system. We introduce "index of importance" to quantitatively evaluate importance of slides. The index of importance is subjective evaluation value that is attached to each slide by lecturers. Firstly, the lecture review system extracts the index of importance of the slide by using a multi-layer neural network (MLN). In a MLN learning process, eight types of nonlinguistic informations, such as the presentation time of the slide, are used as inputs and the index of importance given by lecturers are set as outputs. Secondly, the index of importance is modified by using the other MLN which has two types of inputs; one is the index of importance and the other is similarities between the slide and adjacent slides. The similarities are calculated with key-word vectors extracted by linguistic informations in slides. The experimental results showed that the index of importance extracted by the system is highly correlated with the index attached by lecturers. As a result, the lecture review system with the proposed extraction method can properly detect key slides and helps students to learn the contents of a lecture effectively. 1.[

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A Method for Keyword Extraction Using Retrieval Information from Students in Lectures

Shinohara

Iribe

Kawashima

et al. 2007

Transactions of the Japanese Society for Artificial Intelligenc

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keywords: learning support system, retrieval information, keyword extraction, lecture information, technical term SummaryRecently, e-learning systems for self-learning with various types of retrieval functions have been developed. This paper describes a method for keyword extraction using retrieval information stored from many students through the retrieval functions. Firstly, we show that (1) teachers tend to consider technical terms as important, while students unfamiliar with the technical terms tend to retrieve the terms, therefore (2) there is a clear correlation between keywords extracted by the teachers and the retrieval words by the students. Secondly, we propse a method utilizing retrieval information from the students for keyword extraction, and show that the mehod can achieve quite better performance than a method extracting keywords using only lecture information.

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Use of Action History Views for Indexing Continuous Media Objects

Cited by 3 publications

References 6 publications

Multiple dynamic view support for cooperative work

Multiple dynamic view support for cooperative work

Extracting Importance of Slides in a Lecture Review System

A Method for Keyword Extraction Using Retrieval Information from Students in Lectures

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