| Using tagflake for condensing navigable tag hierarchies from tag clouds |
| Full text |
Pdf
(450 KB)
|
Source
|
International Conference on Knowledge Discovery and Data Mining
archive
Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
table of contents
Las Vegas, Nevada, USA
DEMONSTRATION SESSION: Demonstrations
table of contents
Pages 1069-1072
Year of Publication: 2008
ISBN:978-1-60558-193-4
|
|
Authors
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 14, Downloads (12 Months): 194, Citation Count: 1
|
|
|
ABSTRACT
We present the tagFlake system, which supports semantically informed navigation within a tag cloud. tagFlake relies on TMine for organizing tags extracted from textual content in hierarchical organizations, suitable for navigation, visualization, classification, and tracking. TMine extracts the most significant tag/terms from text documents and maps them onto a hierarchy in such a way that descendant terms are contextually dependent on their ancestors within the given corpus of documents. This provides tagFlake with a mechanism for enabling navigation within the tag space and for classification of the text documents based on the contextual structure captured by the created hierarchy. tagFlake is language neutral, since it does not rely on any natural language processing technique and is unsupervised.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
http://www.usatoday.com, http://www.abcnews.go.com, http://www.forbes.com, http://www.nytimes.com, http://www.smh.com.au, http://www.guardian.co.uk, http://news.bbc.co.uk, http://www.cbsnews.com, http://www.chron.com, http://www.washingtonpost.com, http://news.com.com, http://www.boston.com, http://www.iht.com.
|
| |
2
|
|
| |
3
|
|
| |
4
|
P. Cimiano, S. Staab, J. Tane. Automatic Acquisition of Taxonomies from Text: FCA meets NLP. ECML/PKDD. Work. on Adaptive Text Extraction and Mining, 2003.
|
| |
5
|
H. Davulcu, S. Vadrevu, S. Nagarajan OntoMiner: Bootstrapping and Populating Ontologies From Domain Specific Web Sites. Semantic Web and Databases Work., 2003
|
 |
6
|
|
| |
7
|
S. Deerwester, S. Dumais, G.Furnas, R. Harshman, T. Landauer, K. Lochbaum and L. Streeter. Computer Information Retrieval using Latent Semantic Structure, US Patent, 1989.
|
| |
8
|
B. Fortuna, D. Mladenic, M. Grobelnik. Visualization of text document corpus. Informatica J., 29 (2005).
|
| |
9
|
B. Fortuna, M. Grobelnik, D. Mladenic System for semi-automatic ontology construction. ESWC, 2006.
|
| |
10
|
B. Fortuna, M. Grobelnik and D. Mladenic. Semi-automatic data-driven ontology construction system SiKDD, 2006.
|
| |
11
|
Eckart, C., Young, G. The approximation of one matrix by another of lower rank. Psychometrika, 1936.
|
 |
12
|
|
| |
13
|
V. Kashyap, C. Ramakrishnan, C. Thomas, D. Bassu, T. C. Rindflesch, A. Sheth TaxaMiner: An Experimentation Framework for Automated Taxonomy Bootstrapping. TR Univ. Georgia, 2004.
|
| |
14
|
Y. Hassan-Montero, V. Herrero-Solana. Improving Tag-Clouds as Visual Information Retrieval Interfaces. InSciT2006.
|
| |
15
|
Y. Hassan-Montero, V. Herrero-Solana. Interfaz visual para recuperación de información basada en análisis de metadatos, escalamiento multidimensional y efecto ojo de pez El Profesional de la Informacion 15(4).
|
 |
16
|
|
| |
17
|
|
| |
18
|
|
|