Name
Title | ||
|---|---|---|
Automatically Detecting and Organizing Documents into Topic Hierarchies: A Neural Network Based Approach to Bookshelf Creation and Arrangement |
Abstract | ||
|---|---|---|
With the increasing amount of information available in electronic document collections, methods for organizing these collections to allow topic-oriented browsing and orientation gain importance. The SOMLib Digital Library System provides such an organization based on the self-organizing map, a popular neural network model. In this paper, we present the GHSOM, which, based on the same concepts, allows an automatic hierarchical decomposition and organization of documents, which very intuitively reflects the organization typically found in (manually organized) conventional libraries. We present a case study based on a 3-month article collection from an Austrian daily newspaper. |
Year | DOI | Venue |
|---|---|---|
2000 | 10.1007/3-540-45268-0_37 | ECDL3 |
Keywords | Field | DocType |
topic hierarchies,3-month article collection,increasing amount,automatic hierarchical decomposition,conventional library,popular neural network model,case study,electronic document collection,organizing documents,austrian daily newspaper,orientation gain importance,automatically detecting,neural network,somlib digital library system,bookshelf creation,digital library,neural network model | World Wide Web,Digital library system,Information retrieval,Computer science,Self-organization,Newspaper,Electronic document,Digital library,Hierarchy,Artificial neural network | Conference |
Volume | ISSN | ISBN |
1923 | 0302-9743 | 3-540-41023-6 |
Citations | PageRank | References |
5 | 1.01 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreas Rauber | 1 | 1925 | 216.21 |
| Michael Dittenbach | 2 | 297 | 26.48 |
| Dieter Merkl | 3 | 846 | 115.65 |