International audienceIn the context of web-scale taxonomies such as Directory Mozilla(www.dmoz.org), previous works have shown the existence of power law distribution in the size of the categories for every level in the taxonomy. In this work, we analyse how such high-level semantics can be leveraged to evaluate accuracy of hierarchical classifiers which automati- cally assign the unseen documents to leaf-level categories. The proposed method offers computational advantages over k-fold cross-validation
Hierarchical classifications are concept hierarchies used to organize arge amounts of documents. Fil...
In the era of Big Data, we need efficient and scalable machine learning algorithms which can perform...
In this paper, we propose an automatic and unsupervised methodology to obtain taxonomies of terms fr...
Abstract. In the context of web-scale taxonomies such as Mozilla and Yahoo! 1 directories, previous ...
International audienceIn many of the large-scale physical and social complex systems phenomena fat-t...
In many of the large-scale physical and social complex sys-tems phenomena fat-tailed distributions o...
For large-scale category systems, such as Directory Mozilla, which consist of tens of thousand categ...
In this work we implement and evaluate a methodology to classify multi-labeled web documents into la...
International audienceWe study in this paper flat and hierarchical classification strategies in the ...
Taxonomies of the Web typically have hundreds of thousands of categories and skewed category distrib...
Abstract. Matching hierarchical structures, like taxonomies or web di-rectories, is the premise for ...
Text documents in the web are in hierarchy, increase in the content, information grows over the year...
growing interest due to the widespread proliferation of topic hierarchies for text documents. The wo...
Hierarchical classifications are concept hierarchies used to organize large amounts of documents. Fi...
Elsevier use only: Received date here; revised date here; accepted date here We address the problem ...
Hierarchical classifications are concept hierarchies used to organize arge amounts of documents. Fil...
In the era of Big Data, we need efficient and scalable machine learning algorithms which can perform...
In this paper, we propose an automatic and unsupervised methodology to obtain taxonomies of terms fr...
Abstract. In the context of web-scale taxonomies such as Mozilla and Yahoo! 1 directories, previous ...
International audienceIn many of the large-scale physical and social complex systems phenomena fat-t...
In many of the large-scale physical and social complex sys-tems phenomena fat-tailed distributions o...
For large-scale category systems, such as Directory Mozilla, which consist of tens of thousand categ...
In this work we implement and evaluate a methodology to classify multi-labeled web documents into la...
International audienceWe study in this paper flat and hierarchical classification strategies in the ...
Taxonomies of the Web typically have hundreds of thousands of categories and skewed category distrib...
Abstract. Matching hierarchical structures, like taxonomies or web di-rectories, is the premise for ...
Text documents in the web are in hierarchy, increase in the content, information grows over the year...
growing interest due to the widespread proliferation of topic hierarchies for text documents. The wo...
Hierarchical classifications are concept hierarchies used to organize large amounts of documents. Fi...
Elsevier use only: Received date here; revised date here; accepted date here We address the problem ...
Hierarchical classifications are concept hierarchies used to organize arge amounts of documents. Fil...
In the era of Big Data, we need efficient and scalable machine learning algorithms which can perform...
In this paper, we propose an automatic and unsupervised methodology to obtain taxonomies of terms fr...