Statistical Chart Generation from Multiple Documents Based on Numerical Data Supplement and Chart Shape Suggestion

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  • MATSUSHITA Mitsunori
    NTT Communication Science Laboratories, NTT Corporation
  • KATO Tsuneaki
    Language and Information Sciences, Graduate School of Arts and Sciences, University of Tokyo

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  • 数値情報の補填とグラフ概形の示唆による複数文書からの統計グラフ生成
  • スウチ ジョウホウ ノ ホテン ト グラフガイケイ ノ シサ ニ ヨル フクスウ ブンショ カラ ノ トウケイ グラフ セイセイ

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Abstract

The goal of our research is to develop a multimodal summarization system that provides trend information composed by multiple modalities (e.g., texts and visual expressions) based on user interest. For that purpose, this paper proposes a method of statistical chart generation from multiple documents. Since sucsource documents often lack a sufficient number of explicit expressions (e.g., “$15”) to correctly draw statistical charts, a system for generating such a chart must appropriately compensate for such missing information. To satisfy this requirement, our proposed method utilizes background knowledge and two types of expressions: comparison expressions (e.g., “increase by 30%”) and qualitative expressions (e.g., “'stable” and “increase slightly”), along with explicit expressions. Our preliminary study reveals that (1) information for drawing a chart can be doubled or more by using background knowledge and comparison expressions and that (2) user comprehension of a generated chart was improved by using qualitative expressions.

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