We found that text autoencoders tend to generate overly generic summaries from simply averaged latent vectors due to an unexpected $L_2$-norm shrinkage in the aggregated latent vectors, which we refer to as summary vector degeneration.
Ranked #1 on Unsupervised Opinion Summarization on Amazon
We present the Quantized Transformer (QT), an unsupervised system for extractive opinion summarization.
We embark on a systematic study to investigate the following question: Are deep models the best performing model for all semantic tagging tasks?
The framework uses an Aspect-based Sentiment Analysis model to extract opinion phrases from reviews, and trains a Transformer model to reconstruct the original reviews from these extractions.
In this paper, we introduce xSense, an effective system for review comprehension using domain-specific commonsense knowledge bases (xSense KBs).
Since it can be expensive to obtain training data to learn to extract implications for each new domain of reviews, we propose an unsupervised KBC system, Sampo, Specifically, Sampo is tailored to build KBs for domains where many reviews on the same domain are available.
A novelty of Snippext is its clever use of a two-prong approach to achieve state-of-the-art (SOTA) performance with little labeled training data through: (1) data augmentation to automatically generate more labeled training data from existing ones, and (2) a semi-supervised learning technique to leverage the massive amount of unlabeled data in addition to the (limited amount of) labeled data.
no code implementations • 4 Mar 2019 • Sara Evensen, Aaron Feng, Alon Halevy, Jinfeng Li, Vivian Li, Yuliang Li, Huining Liu, George Mihaila, John Morales, Natalie Nuno, Ekaterina Pavlovic, Wang-Chiew Tan, Xiaolan Wang
We describe Voyageur, which is an application of experiential search to the domain of travel.
KOKO is novel in that its extraction language simultaneously supports conditions on the surface of the text and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions.