Sequential Document Representations and Simplicial Curves
Information Retrieval
2012-07-02 v1 Machine Learning
Abstract
The popular bag of words assumption represents a document as a histogram of word occurrences. While computationally efficient, such a representation is unable to maintain any sequential information. We present a continuous and differentiable sequential document representation that goes beyond the bag of words assumption, and yet is efficient and effective. This representation employs smooth curves in the multinomial simplex to account for sequential information. We discuss the representation and its geometric properties and demonstrate its applicability for the task of text classification.
Cite
@article{arxiv.1206.6858,
title = {Sequential Document Representations and Simplicial Curves},
author = {Guy Lebanon},
journal= {arXiv preprint arXiv:1206.6858},
year = {2012}
}
Comments
Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006)