Understanding temporal aspects in document classification

  title={Understanding temporal aspects in document classification},
  author={Fernando Mour{\~a}o and Leonardo C. da Rocha and Renata Braga Ara{\'u}jo and Thierson Couto and Marcos Andr{\'e} Gonçalves and Wagner Meira},
Due to the increasing amount of information present on the Web, Automatic Document Classification (ADC) has become an important research topic. ADC usually follows a standard supervised learning strategy, where we first build a model using preclassified documents and then use it to classify new unseen documents. One major challenge for ADC in many scenarios is that the characteristics of the documents and the classes to which they belong may change over time. However, most of the current… CONTINUE READING
Highly Cited
This paper has 43 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 27 extracted citations

Dealing with temporal variation in patent categorization

Information Retrieval • 2014
View 10 Excerpts
Highly Influenced

Connecting Opinions to Opinion-Leaders: A Case Study on Brazilian Political Protests

2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA) • 2016
View 2 Excerpts

Machine learning approach to recognize subject based sentiment values of reviews

2016 Moratuwa Engineering Research Conference (MERCon) • 2016
View 2 Excerpts


Publications referenced by this paper.
Showing 1-4 of 4 references

Automatic Document Classification

J. ACM • 1963
View 16 Excerpts
Highly Influenced

Training linear SVMs in linear time

KDD • 2006
View 8 Excerpts
Highly Influenced

Making large-scale support vector machine learning practical

T. Joachims
View 8 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…