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 (11)
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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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