Рейтерс 21578

material ID: reuters21578

Related Papers

Category Levels in Hierarchical Text Categorization

Authors: nan

Publication: TIPSTER (1998)

DOI: nan

We consider the problem of assigning level numbers (weights) to hierarchically organized categories during text categorization. These levels control the ability of the categories to attract documents during the catego- …...

33222

A mixture-of-experts framework for text classification

Authors: nan

Publication: TIPSTER (2001)

DOI: nan

One of the particular characteristics of text classification tasks is that they present large class imbalances. Such a problem can easily be tackled using re- sampling methods. However, although these …...

41337

Building Semantic Perceptron Net for Topic Spotting

Authors: nan

Publication: TIPSTER (2001)

DOI: nan

This paper presents an approach to automatically build a semantic perceptron net (SPN) for topic spotting. It uses context at the lower layer to select the exact meaning of key …...

35223

Soft-Supervised Learning for Text Classification

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

We propose a new graph-based semi- supervised learning (SSL) algorithm and demonstrate its application to document categorization. Each document is represented by a vertex within a weighted undirected graph and …...

44024

Learning Latent Word Representations for Domain Adaptation using Supervised Word Clustering

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Domain adaptation has been popularly stud- ied on exploiting labeled information from a source domain to learn a prediction model in a target domain. In this paper, we develop a …...

34965

Balancing Methods for Multi-label Text Classification with Long-Tailed Class Distribution

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractMulti-label text classification is a challenging task because it requires capturing label dependencies. It becomes even more challenging when class distribution is long-tailed. Resampling and re-weighting are common approaches used …...

31232