Visualization guided document reading by citation and text summarization

Publication Type:
Journal Article
Ruan Jian Xue Bao/Journal of Software, 2016, 27 (5), pp. 1163 - 1173
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© Copyright 2016, Institute of Software, the Chinese Academy of Sciences. All rights reserved. With growing volume of publications in recent years, researchers have to read much more literatures. Therefore, how to read a scientific article in an efficient way becomes an importance issue. When reading an article, it's necessary to read its references in order to get a better understanding. However, how to differentiate between the relevant and non-relevant references, and how to stay in topic in a large document collection are still challenging tasks. This paper presents GUDOR (GUidedDOcument Reader), a visualization guided reader based on citation and summarization. It (1) extracts the important sentences from a scientific article with an objective-based summarization technique, and visualizes the extraction results by a multi-resolution method; (2) identifies the main topics of the references with a LDA (Latent Dirichlet Allocation) model; (3) tracks user's reading behavior to keep him or her focusing on the reading objective. In addition, the paper describes the functions and operations of the system in a usage scenario and validates its applicability by a user study.
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