GENERATING A VISUAL OVERVIEW OF LARGE DIACHRONIC DOCUMENT COLLECTIONS BASED ON THE DETECTION OF TOPIC CHANGE

被引：0

作者：

Holz, Florian ^{[1
]}

Teresniak, Sven ^{[1
]}

Heyer, Gerhard ^{[1
]}

Scheuermann, Gerik ^{[2
]}

机构：

[1] Univ Leipzig, Inst Comp Sci, Nat Language Proc Grp, Leipzig, Germany

[2] Univ Leipzig, Inst Comp Sci, Image & Signal Proc Grp, Leipzig, Germany

来源：

IMAGAPP & IVAPP 2010: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON IMAGING THEORY AND APPLICATIONS AND INTERNATIONAL CONFERENCE ON INFORMATION VISUALIZATION THEORY AND APPLICATIONS | 2010年

关键词：

Visual analytics; Document collection summarization; Browsing document collections; Topic detection; Change of meaning; Volatility; Time-sliced corpora;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Large digital diachronic document collections are a central source of information in science, business, and for the general public. One challenge for the efficient visualization of these collections is the automatic calculation and visualization of the main topics. These topics can then serve as the basis for an overview of the content and any subsequent interactive visual analysis. We introduce the new language processing concept of volatility of terms measured as the change of the context of terms. We demonstrate that volatility can serve as an excellent basis for the visual overview of large collections using two different examples.

引用

页码：153 / 156

页数：4

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