In the last decade the interest in the hierarchical organization of documents is increased. New challenges arise as hierarchical document classification, both unsupervised and supervised. A recognition of the most recent literature on these topics shows that none of the published works refer to the same dataset to enable the experimental phase. Moreover the papers don`t provide enough details to reproduce the same datasets starting from the same information sources. The drawback is twofold: from one hand the waste of time to preprocess suitable datasets, to the other hand the lack of a common testbed to compare alternative solutions. In this paper we propose a dataset extracted from Google and LookSmart web directories to support the experimentation effort in the field of hierarchical document classification. For such a task we aim to provide a kind of reference corpus in analogy with the role that Reuters plays in the scientific community. The paper illustrates the proces! s performed to generate a well defined dataset. This dataset is freely distributed over the web

TaxE: a Testbed for Hierarchical Document Classifiers

Avesani, Paolo;Girardi, Christian;Polettini, Nicola;Sona, Diego
2004-01-01

Abstract

In the last decade the interest in the hierarchical organization of documents is increased. New challenges arise as hierarchical document classification, both unsupervised and supervised. A recognition of the most recent literature on these topics shows that none of the published works refer to the same dataset to enable the experimental phase. Moreover the papers don`t provide enough details to reproduce the same datasets starting from the same information sources. The drawback is twofold: from one hand the waste of time to preprocess suitable datasets, to the other hand the lack of a common testbed to compare alternative solutions. In this paper we propose a dataset extracted from Google and LookSmart web directories to support the experimentation effort in the field of hierarchical document classification. For such a task we aim to provide a kind of reference corpus in analogy with the role that Reuters plays in the scientific community. The paper illustrates the proces! s performed to generate a well defined dataset. This dataset is freely distributed over the web
2004
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/2540
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