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Document classification

Known as: Topic spotting, Text categorisation, Classification 
Document classification or document categorization is a problem in library science, information science and computer science. The task is to assign a… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
In this work, we address the problem to model all the nodes (words or phrases) in a dependency tree with the dense… 
2010
2010
In this study, we propose a method for encoding documents into string vectors, instead of numerical vectors. A traditional… 
2008
2008
The ability to correctly classify sentences that describe events is an important task for many natural language applications such… 
Highly Cited
2007
Highly Cited
2007
Resumen : Algunas aplicaciones del procesamiento del lenguaje natural, p.ej. la traduccion automatica, requieren una base de… 
Highly Cited
2005
Highly Cited
2005
In this paper, we compare the performance of three classifiers for Arabic text categorization. In particular, the naïve Bayes, k… 
2004
2004
Current document retrieval methods use a vector space similarity measure to give scores of relevance to documents when related to… 
Highly Cited
2004
Highly Cited
2004
This paper presents the clustering algorithm PoBOC (Pole-Based Overlapping Clustering). It has two main characteristics: the… 
Highly Cited
2003
Highly Cited
2003
This paper motivates and presents the Topic-based Vector Space Model (TVSM), a new vector-based approach for document comparison… 
Highly Cited
2002
Highly Cited
2002
This position paper addresses the problem of ontology mapping which is pervasive in context where semantic interoperability is…