Font attributes enrich knowledge maps and information retrieval

详细信息    查看全文

• 作者：Richard Brath ; Ebad Banissi
• 关键词：Font attributes ; Text visualization ; Information density ; Alphanumeric glyphs ; Quantitative typography
• 刊名：International Journal on Digital Libraries
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：18
• 期：1
• 页码：5-24
• 全文大小：6339KB
• 刊物类别：Computer Science
• 刊物主题：Database Management; Information Systems and Communication Service;
• 出版者：Springer Berlin Heidelberg
• ISSN：1432-1300
• 卷排序：18

文摘

Typography is overlooked in knowledge maps (KM) and information retrieval (IR), and some deficiencies in these systems can potentially be improved by encoding information into font attributes. A review of font use across domains is used to itemize font attributes and information visualization theory is used to characterize each attribute. Tasks associated with KM and IR, such as skimming, opinion analysis, character analysis, topic modelling and sentiment analysis can be aided through the use of novel representations using font attributes such as skim formatting, proportional encoding, textual stem and leaf plots and multi-attribute labels.