CompareLDA: A topic model for document comparison
A number of real-world applications require comparison of entities based on their textual representations. In this work, we develop a topic model supervised by pairwise comparisons of documents. Such a model seeks to yield topics that help to differentiate entities along some dimension of interest,...
Saved in:
Main Authors: | TKACHENKO, Maksim, LAUW, Hady Wirawan |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2019
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/4698 https://ink.library.smu.edu.sg/context/sis_research/article/5701/viewcontent/aaai19b.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
Similar Items
-
Meta-complementing the semantics of short texts in neural topic models
by: ZHANG, Ce, et al.
Published: (2022) -
Topic modeling for multi-aspect listwise comparison
by: ZHANG, Delvin Ce, et al.
Published: (2021) -
Comparative relation generative model
by: TKACHENKO, Maksim, et al.
Published: (2017) -
Generative Modeling of Entity Comparisons in Text
by: TKACHENKO, Maksim, et al.
Published: (2014) -
Probabilistic Latent Document Network Embedding
by: LE, Tuan M. V., et al.
Published: (2014)