Visually Summarizing Semantic Evolution in Document Streams with Topic Table
We propose a visualization technique for summarizing contents of document streams, such as news or scientific archives. The content of streaming documents change over time and so do themes the documents are about. Topic evolution is a relatively new research subject that encompasses the unsupervised...
Saved in:
Published in | Knowledge Discovery, Knowledge Engineering and Knowledge Management pp. 136 - 150 |
---|---|
Main Authors | , , |
Format | Book Chapter |
Language | English |
Published |
Berlin, Heidelberg
Springer Berlin Heidelberg
2013
|
Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get full text |
ISBN | 9783642297632 3642297633 |
ISSN | 1865-0929 1865-0937 |
DOI | 10.1007/978-3-642-29764-9_9 |
Cover
Summary: | We propose a visualization technique for summarizing contents of document streams, such as news or scientific archives. The content of streaming documents change over time and so do themes the documents are about. Topic evolution is a relatively new research subject that encompasses the unsupervised discovery of thematic subjects in a document collection and the adaptation of these subjects as new documents arrive. While many powerful topic evolution methods exist, the combination of learning and visualization of the evolving topics has been less explored, although it is indispensable for understanding a dynamic document collection.
We propose Topic Table, a visualization technique that builds upon topic modeling for deriving a condensed representation of a document collection. Topic Table captures important and intuitively comprehensible aspects of a topic over time: the importance of the topic within the collection, the words characterizing this topic, the semantic changes of a topic from one timepoint to the next. As an example, we visualize content of the NIPS proceedings from 1987 to 1999. |
---|---|
ISBN: | 9783642297632 3642297633 |
ISSN: | 1865-0929 1865-0937 |
DOI: | 10.1007/978-3-642-29764-9_9 |