Name
Abstract | ||
|---|---|---|
This paper addresses exploratory search in large collections of historical texts. By way of example, we apply our method to a collection of documents comprising dossiers of the former East-German Ministry for State Security, and classical texts. The bases of our approach are topic models, a class of algorithms that define and infer themes pervading the corpus as probability distributions over the vocabulary. Our topic-centered visual metaphor supports to explore the corpus following an intuitive methodology: First, determine a topic of interest, second, suggest documents that contain the topic with "sufficient" proportion, and third, browse iteratively through related topics and documents. Our main focus lies on providing a suitable bird's eye view onto the data to facilitate an in-depth analysis in terms of the topics contained. |
Year | Venue | Field |
|---|---|---|
2017 | DIGITAL HUMANITIES QUARTERLY | Information retrieval,Computer science,Topic model,Multimedia,Exploratory search |
DocType | Volume | Issue |
Journal | 11 | 2 |
ISSN | Citations | PageRank |
1938-4122 | 0 | 0.34 |
References | Authors | |
12 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Patrick Jähnichen | 1 | 11 | 3.28 |
| P Oesterling | 2 | 48 | 3.37 |
| Gerhard Heyer | 3 | 120 | 9.22 |
| Tom Liebmann | 4 | 7 | 1.47 |
| Gerik Scheuermann | 5 | 1382 | 112.65 |
| Christoph Kuras | 6 | 0 | 0.68 |