Jekyll2022-04-23T07:20:18+00:00https://wakita.github.io/smartnova/feed.xmlSmartnova: VIS Research GroupSmartnova: Data Visualization and Visual Analytics System Research Group脇田 建 / Ken Wakita2022-04-23T07:20:18+00:002022-04-23T07:20:18+00:00https://wakita.github.io/smartnova/2022/04/23/2020-12-10-vinci-hosokawa<p>Natsuki Hosokawa, Kohei Arimoto and Ken Wakita: “<a href="https://doi.org/10.1145/3430036.3430069">A Scalable ‘Exploranation’ Technique for Hierarchically Indexed Table Data</a>,” The 13th International symposium on Visual Information communication and interaction (VINCI 2020)</p>
<p><em>*Abstract</em>: Data analytics tools that combine automated text generation and visualization techniques suffer from scalability problems. The amount of the generated text explodes with the increase of items and attributes. This study addresses this problem for table data, whose attributes and data items are hierarchically organized. In our approach, the user’s point of view is modeled by the dual focalization axis, which consists of the attribute-based and the data-item-based focal points. The user can refine the two-dimensional focal points to obtain the chart and the text that explain the data facts found in a more focused portion of the dataset. The proposal’s efficacy was assessed through a quantitative and qualitative evaluation using a prototype visual analytics tool that employs the idea.</p>脇田 建 / Ken Wakita第17回WI2研究会で陳雪羿さんが学生奨励賞を受賞しました。2021-12-17T00:00:00+00:002021-12-17T00:00:00+00:00https://wakita.github.io/smartnova/2021/12/17/wi2-chen<p>修士1年生の陳雪羿さんが第17回WI2研究会の<strong>セッション3:可視化</strong>で脇田と共著の論文 “A Visual Exploratory System for Data Facts in Business Reports” に発表し、<a href="https://www.sigwi2.org/report-no17#award">学生奨励賞を受賞しました</a>。彼女の発表については、<a href="https://www.sigwi2.org/report-no17#fukuzatyo">副座長報告</a>に記載があります(セッション3:可視化の第3項)。</p>
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<h1 id="a-visual-exploratory-system-for-data-facts-in-business-reports">A Visual Exploratory System for Data Facts in Business Reports</h1>
<h2 id="xueyi-chen-ken-wakita">Xueyi CHEN Ken WAKITA</h2>
<p><strong>Abstract</strong>: For practitioners working in different fields, reports describing a variety of data facts are authored and analyzed by lots of people every day. To get insights efficiently from such kind of data-rich document, people naturally take notes by using visual marks such as highlights, underlines, circles traditionally. Recently, as business reporting goes electronic gradually, there is a surge of attention and interest in effective support for such kind of report analysis with the power of computer science. In this paper, we design a visual-guided method focusing on business reports exploration, especially, so as to help build visual links among charts and data-facts embedding in the text. The proposed method aims to simplify the authoring of interactive business reports, as well as empower people to comprehend the key information effectively. Several use cases generated by our system based on real business reports are presented to show the usage and capability of the implemented architecture.</p>
<p><strong>Keywords</strong>: Visual Analytics, Data Facts, Business Reports, Exploration, Narratives</p>脇田 建 / Ken Wakita修士1年生の陳雪羿さんが第17回WI2研究会のセッション3:可視化で脇田と共著の論文 “A Visual Exploratory System for Data Facts in Business Reports” に発表し、学生奨励賞を受賞しました。彼女の発表については、副座長報告に記載があります(セッション3:可視化の第3項)。第49回可視化情報シンポジウムで太田 彩さんがベストプレゼンテーション賞を受賞しました。2021-09-11T00:00:00+00:002021-09-11T00:00:00+00:00https://wakita.github.io/smartnova/2021/09/11/vsj-ota<p>修士1年生の太田 彩さんが第49回可視化情報シンポジウムの<strong>セッションOS9:ソーシャルデータの可視化</strong>で脇田と共著の論文 “小説内の動的人物相関図を用いた読書システム” に発表をし、<a href="https://www.vsj.jp/symp2021/program.html#OS9-2">ベストプレゼンテーション賞を受賞しました</a>。</p>
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<h1 id="小説内の動的人物相関図を用いた読書システム-a-reading-system-using-dynamic-character-correlation-in-novels">小説内の動的人物相関図を用いた読書システム (A reading system using dynamic character correlation in novels)</h1>
<h2 id="太田-彩-aya-ota脇田-建-ken-wakita">太田 彩 (Aya OTA)、脇田 建 (Ken WAKITA)</h2>
<p><strong>ABSTRACT</strong>: Books are reliable and excellent sources of information. However, reading requires long time constraints and the need to supplement the information from the text. Therefore, even if you have the desire and need to read, you may give up. For this reason, researches have been conducted to automatically extract information from novels and to assist the reader by representing the content of the story in a single page. However, there is a risk of spoiling. In this study, we propose a method to support reading by presenting a character correlation. In order to reduce the risk of spoilers, we propose a character correlation chart that changes as the reading progresses. We used two methods to add information: automatic extraction using natural language processing techniques and manual addition. In addition, by sharing the input information with others, we were able to reduce the time and effort required to input information. In order to verify the effectiveness of the proposed method, we constructed a reading support system using Aozora Bunko data. Finally, we discussed the degree of achievement and issues in comparison with the objectives.</p>
<p><strong>Keywords</strong>: visualization / dynamic graph / natural language processing</p>脇田 建 / Ken Wakita修士1年生の太田 彩さんが第49回可視化情報シンポジウムのセッションOS9:ソーシャルデータの可視化で脇田と共著の論文 “小説内の動的人物相関図を用いた読書システム” に発表をし、ベストプレゼンテーション賞を受賞しました。牧 修平 & 脇田 建: 時系列データに対する説明的可視化 - 第49回可視化情報シンポジウム2021-09-10T00:00:00+00:002021-09-10T00:00:00+00:00https://wakita.github.io/smartnova/2021/09/10/vsj-maki<h2 id="牧-修平--脇田-建時系列データに対する説明的可視化">牧 修平 & 脇田 建<br />時系列データに対する説明的可視化</h2>
<p><strong>Abstract</strong>: Various visualization methods are used to make data easier to understand, but due to scalability and data structure, it may be difficult to recognize the features of the data we want to convey from the visualization. Therefore, in addition to visualization, research has been done to provide the features of data by words. In this paper, using the Social Progress Index, a time-series data with a large number of items as an example, we propose a system that provides visualizations to support data analysis and template-based summary sentences of the data. In this paper, we also explain how to search for data in the form of time series data and how to construct templates to generate summary text of the data. Finally, we show the usability of the system through a case study.</p>
<p><strong>Keyword</strong>: Time Series Data, Explanatory Visualization</p>
<p>第49回可視化情報シンポジウムのOS9(ソーシャルデータの可視化)で発表</p>脇田 建 / Ken Wakita牧 修平 & 脇田 建時系列データに対する説明的可視化太田 彩 & 脇田 建: 小説内の動的人物相関図を用いた読書システム2021-09-10T00:00:00+00:002021-09-10T00:00:00+00:00https://wakita.github.io/smartnova/2021/09/10/vsj-ota<h2 id="太田-彩--脇田-建-小説内の動的人物相関図を用いた読書システム">太田 彩 & 脇田 建: 小説内の動的人物相関図を用いた読書システム</h2>
<p><strong>Abstract</strong>: Books are reliable and excellent sources of information. However, reading requires long time constraints and the need to supplement the information from the text. Therefore, even if you have the desire and need to read, you may give up. For this reason, researches have been conducted to automatically extract information from novels and to assist the reader by representing the content of the story in a single page. However, there is a risk of spoiling. In this study, we propose a method to support reading by presenting a character correlation. In order to reduce the risk of spoilers, we propose a character correlation chart that changes as the reading progresses. We used two methods to add information: automatic extraction using natural language processing techniques and manual addition. In addition, by sharing the input information with others, we were able to reduce the time and effort required to input information. In order to verify the effectiveness of the proposed method, we constructed a reading support system using Aozora Bunko data. Finally, we discussed the degree of achievement and issues in comparison with the objectives.</p>
<p><strong>Keywords</strong>: Visualization / Dynamic graph / Natural language processing</p>脇田 建 / Ken Wakita太田 彩 & 脇田 建: 小説内の動的人物相関図を用いた読書システム上田 叶 & 脇田 建: 会話データの可視化に関するサーベイ - 第49回可視化情報シンポジウム2021-09-10T00:00:00+00:002021-09-10T00:00:00+00:00https://wakita.github.io/smartnova/2021/09/10/vsj-ueda<h2 id="上田-叶脇田-建会話データの可視化に関するサーベイ">上田 叶、脇田 建<br />会話データの可視化に関するサーベイ</h2>
<p><strong>Abstract</strong>: Various visualization methods are used to make data easier to understand, but due to scalability and data structure, it may be difficult to recognize the features of the data we want to convey from the visualization. Therefore, in addition to visualization, research has been done to provide the features of data by words. In this paper, using the Social Progress Index, a time-series data with a large number of items as an example, we propose a system that provides visualizations to support data analysis and template-based summary sentences of the data. In this paper, we also explain how to search for data in the form of time series data and how to construct templates to generate summary text of the data. Finally, we show the usability of the system through a case study.</p>
<p><strong>Keyword</strong>: Time Series Data, Explanatory Visualization</p>
<p>第49回可視化情報シンポジウムのOS9(ソーシャルデータの可視化)で発表</p>脇田 建 / Ken Wakita上田 叶、脇田 建会話データの可視化に関するサーベイ日本ソフトウェア科学会第37回大会で細川 夏生さんが学生奨励賞を受賞しました。2020-09-10T00:00:00+00:002020-09-10T00:00:00+00:00https://wakita.github.io/smartnova/2020/09/10/jssst-hosokawa<p>修士1年生の細川 夏生さんが日本ソフトウェア科学会第37回大会の一般セッションで脇田と共著の論文<a href="http://jssst.or.jp/files/user/taikai/2020/GENERAL/general3-4.pdf">データの可視化・文章化技術を複合させた大規模表データ探索システム</a>(48-L) を発表し、<a href="https://jssst2020.wordpress.com">学生奨励賞を受賞</a>しました。</p>
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<h2 id="データの可視化文章化技術を複合させた大規模表データ探索システム">データの可視化・文章化技術を複合させた大規模表データ探索システム</h2>
<h3 id="細川-夏生-有本-昂平-脇田-建">細川 夏生 有本 昂平 脇田 建</h3>
<p><strong>概要</strong>: 近年、自然言語生成と可視化を組み合わせたデータ分析システムが増えてきている。ユーザーがデータに埋もれている重要な事実を理解するのに、文章という媒体は可視化単体に比べて特別な知識が必要ないという点で優れている。しかし、データが大きいと当然統計的特徴も多くなってしまうため、大規模なデータを自動的に文章で要約しようとしても長大になってしまう。本研究ではこのスケーラビリティの問題に対処するため、多くの大規模データが項目と属性の両方に顕在的、潜在的に持っている階層構造を利用して、第一にユーザーが興味を持っている部分にのみ焦点を絞って文章化と可視化を行い、第二にユーザーの興味の移り変わりに応じてインタラクティブに焦点を移動させることで、一度に提示する文章の量を抑制しつつもデータ全体をスムーズに探索可能なシステムのアイデアを提案する。また、実際にシステムを実装し、このアイデアが有効であることを示す。</p>脇田 建 / Ken Wakita修士1年生の細川 夏生さんが日本ソフトウェア科学会第37回大会の一般セッションで脇田と共著の論文データの可視化・文章化技術を複合させた大規模表データ探索システム(48-L) を発表し、学生奨励賞を受賞しました。