Gotcha: Academic Paper Retrieval System Using Visual Layout Manipulation
Date Issued
2014
Date
2014
Author(s)
Chang, Eugene
Abstract
In recent years, there is an increase of documents containing graphical contents. With the abundance of these non-textual content inside the documents, it will be harder for the document viewer to describe the content only in textual words. This will increase the difficulty of text-based searching, raising a demand for searching the documents by describing the content visually instead of using text. In this paper, we propose Gotcha, a novel system of searching academic papers by analyzing and recording the visual layout of document pages to allow its users to retrieve these papers by using a query based on visual clues instead of keyword. We were able to achieve these goals by using the following method: First, we utilize a modified version of the Running Length Smoothing Algorithm (RLSA) to segment a document page into blocks of content. Second, we extract the visual features of these blocks and classify them into different types of content using the Support Vector Machine (SVM) classifier with 86% accuracy. Finally, we design a novel user interface to enable the users to sketch a simple query based on the visual layout of their desired document, and retrieve all the document pages with content blocks that matches the user query in terms of shape and position. From the result of our user study, we corroborate that our system is better than document retrieval by looking through thumbnail images in a traditional file finder in terms of task completion time, with a confidence level of 95% (t =2.89). Our system nearly improves the document retrieval time by 4 times.
Subjects
學術論文搜尋
圖像搜尋與檢索
多媒體系統
Type
thesis
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