McDonaldRyan x 7

bookRéférences 7

What's great and what's not: learning to classify the scope of negation for improved sentiment analysis

Automatic detection of linguistic negation in free text is a critical need for many text processing ...

2025-09-09 14:37:09

McDonaldRyanCouncillIsaacVelikovichLeonid

Semi-supervised latent variable models for sentence-level sentiment analysis

We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models l...

2025-09-09 14:36:52

McDonaldRyanTäckströmOscar

Structured Models for Fine-to-Coarse Sentiment Analysis

In this paper we investigate a structured model for jointly classifying the sentiment of text at var...

2025-09-09 14:36:50

HannanKerryMcDonaldRyanNeylonTylerReynarJeffWellsMike

A Joint Model of Text and Aspect Ratings for Sentiment Summarization

Online reviews are often accompanied with numerical ratings provided by users for a set of service o...

2025-09-09 14:36:50

McDonaldRyanTitovIvan

Sentiment summarization: evaluating and learning user preferences

We present the results of a large-scale, end-to-end human evaluation of various sentiment summarizat...

2025-09-09 14:36:28

BlairGoldensohnSashaMcDonaldRyanLermanKevin

Building a Sentiment Summarizer for Local Service Reviews

Online user reviews are increasingly becoming the de-facto standard for measuring the quality of ele...

BlairGoldensohnSashaHannanKerryMcDonaldRyanNeylonTylerReisGeorgeReynarJeff

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