Augmenting end-to-end dialogue systems with commonsense knowledge
Building dialogue systems that can converse naturally with humans is a challenging yet
intriguing problem of artificial intelligence. In open-domain human-computer conversation …
intriguing problem of artificial intelligence. In open-domain human-computer conversation …
[PDF][PDF] Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis
We present a novel way of extracting features from short texts, based on the activation
values of an inner layer of a deep convolutional neural network. We use the extracted …
values of an inner layer of a deep convolutional neural network. We use the extracted …
Sentic LSTM: a hybrid network for targeted aspect-based sentiment analysis
Sentiment analysis has emerged as one of the most popular natural language processing
(NLP) tasks in recent years. A classic setting of the task mainly involves classifying the …
(NLP) tasks in recent years. A classic setting of the task mainly involves classifying the …
Commonsense for generative multi-hop question answering tasks
Reading comprehension QA tasks have seen a recent surge in popularity, yet most works
have focused on fact-finding extractive QA. We instead focus on a more challenging multi …
have focused on fact-finding extractive QA. We instead focus on a more challenging multi …
A comprehensive survey of handwritten document benchmarks: structure, usage and evaluation
Handwriting has remained one of the most frequently occurring patterns that we come
across in everyday life. Handwriting offers a number of interesting pattern classification …
across in everyday life. Handwriting offers a number of interesting pattern classification …
[图书][B] Sentic computing: Techniques, tools, and applications
In this book common sense computing techniques are further developed and applied to
bridge the semantic gap between word-level natural language data and the concept-level …
bridge the semantic gap between word-level natural language data and the concept-level …
AffectiveSpace 2: Enabling affective intuition for concept-level sentiment analysis
Predicting the affective valence of unknown multi-word expressions is key for concept-level
sentiment analysis. AffectiveSpace 2 is a vector space model, built by means of random …
sentiment analysis. AffectiveSpace 2 is a vector space model, built by means of random …
Concept-level sentiment analysis with dependency-based semantic parsing: a novel approach
Sentiment analysis from unstructured natural language text has recently received
considerable attention from the research community. In the frame of biologically inspired …
considerable attention from the research community. In the frame of biologically inspired …
Twitter sentiment analysis for large-scale data: an unsupervised approach
R Pandarachalil, S Sendhilkumar… - Cognitive …, 2015 - Springer
Millions of tweets are generated each day on multifarious issues. Topical diversity in content
demands domain-independent solutions for analysing twitter sentiments. Scalability is …
demands domain-independent solutions for analysing twitter sentiments. Scalability is …
A neural word embeddings approach for multi-domain sentiment analysis
M Dragoni, G Petrucci - IEEE Transactions on Affective …, 2017 - ieeexplore.ieee.org
Multi-domain sentiment analysis consists in estimating the polarity of a given text by
exploiting domain-specific information. One of the main issues common to the approaches …
exploiting domain-specific information. One of the main issues common to the approaches …