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Automatic Seed Word Selection for Unsupervised Sentiment Classification of Chinese Text

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

We describe and evaluate a new method of automatic seed word selection for un- supervised sentiment classification of product reviews in Chinese. The whole method is unsupervised and does not …...

6203

Grouping Product Features Using Semi-Supervised Learning with Soft-Constraints

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

In opinion mining of product reviews, one of- ten wants to produce a summary of opinions based on product features/attributes. Howev- er, for the same feature, people can express it …...

6169

Sentiment Learning on Product Reviews via Sentiment Ontology Tree

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierar- chical relationships of products attributes is not fully utilized. (2) Reviews or …...

36169

Detection of Product Comparisons - How Far Does an Out-of-the-Box Semantic Role Labeling System Take You?

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

This short paper presents a pilot study in- vestigating the training of a standard Seman- tic Role Labeling (SRL) system on product reviews for the new task of detecting com- …...

34498

Exploiting Domain Knowledge in Aspect Extraction

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Aspect extraction is one of the key tasks in sentiment analysis. In recent years, statistical models have been used for the task. However, such models without any domain knowledge often …...

34559

Instance Selection Improves Cross-Lingual Model Training for Fine-Grained Sentiment Analysis

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

Scarcity of annotated corpora for many languages is a bottleneck for training fine- grained sentiment analysis models that can tag aspects and subjective phrases. We pro- pose to exploit statistical …...

42099

Learning to Generate Product Reviews from Attributes

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractAutomatically generating product reviews is a meaningful, yet not well-studied task in sentiment analysis. Traditional natural language generation methods rely extensively on hand-crafted rules and predefined templates. This paper presents …...

43109

Aspect-based summarization of pros and cons in unstructured product reviews

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractWe developed three systems for generating pros and cons summaries of product reviews. Automating this task eases the writing of product reviews, and offers readers quick access to the most …...

5331

Rethinking Attribute Representation and Injection for Sentiment Classification

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractText attributes, such as user and product information in product reviews, have been used to improve the performance of sentiment classification models. The de facto standard method is to incorporate …...

8952

Bayes-enhanced Lifelong Attention Networks for Sentiment Classification

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractThe classic deep learning paradigm learns a model from the training data of a single task and the learned model is also tested on the same task. This paper studies …...

4301

CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractNLP models are shown to suffer from robustness issues, i.e., a model’s prediction can be easily changed under small perturbations to the input. In this work, we present a Controlled …...

30256

Human Value Detection from Bilingual Sensory Product Reviews

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractWe applied text classification methods on a corpus of product reviews we created with the help of a questionnaire. We found that for certain values, “traditional” deep neural networks like …...

20001