Name
Abstract | ||
|---|---|---|
In this work we study the task of term extraction for word cloud generation. We present a folksonomy-based term extraction method, called tag-boost, which boosts terms that are frequently used by the public to tag content. Our experiments with tag-boost-based term extraction over different domains demonstrate tremendous improvement in word cloud quality, as reflected by the agreement between extracted terms and manually assigned tags of the testing items. Additionally, we show that tag-boost can be effectively applied even in non-tagged domains, by using an external rich folksonomy borrowed from a well-tagged domain. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1145/2337542.2337545 | ACM Transactions on Intelligent Systems and Technology (TIST) |
Keywords | DocType | Volume |
word cloud quality,data sparseness,term extraction,word cloud generation,manual tag,folksonomy-based term extraction,external rich folksonomy,non-tagged domain,tag-boost-based term extraction,tremendous improvement,high robustness,high sensitivity,alternative cloud generation method,testing item,folksonomy-based term extraction method,different domain | Journal | 3 |
Issue | ISSN | Citations |
4 | 2157-6904 | 10 |
PageRank | References | Authors |
0.56 | 37 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| David Carmel | 1 | 2530 | 156.30 |
| Erel Uziel | 2 | 478 | 16.21 |
| Ido Guy | 3 | 1444 | 85.72 |
| Yosi Mass | 4 | 574 | 60.91 |
| Haggai Roitman | 5 | 314 | 32.07 |