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Resilient Combination of Complementary CNN and RNN Features for Text Classification through Attention and Ensembling
Athanasios Giannakopoulos, Maxime Coriou, Andreea Hossmann +2
State-of-the-art methods for text classification include several distinct steps of pre-processing, feature extraction and post-processing. In this work, we focus on end-to-end neur…
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings
Meryem M'hamdi, Robert West, Andreea Hossmann +2
Most work in text classification and Natural Language Processing (NLP) focuses on English or a handful of other languages that have text corpora of hundreds of millions of words. T…
Embedding Individual Table Columns for Resilient SQL Chatbots
Bojan Petrovski, Ignacio Aguado, Andreea Hossmann +2
Most of the world's data is stored in relational databases. Accessing these requires specialized knowledge of the Structured Query Language (SQL), putting them out of the reach of…
Churn Intent Detection in Multilingual Chatbot Conversations and Social Media
Christian Abbet, Meryem M'hamdi, Athanasios Giannakopoulos +4
We propose a new method to detect when users express the intent to leave a service, also known as churn. While previous work focuses solely on social media, we show that this inten…
Diverse Beam Search for Increased Novelty in Abstractive Summarization
André Cibils, Claudiu Musat, Andreea Hossman +1
Text summarization condenses a text to a shorter version while retaining the important informations. Abstractive summarization is a recent development that generates new phrases, r…
Submodularity-Inspired Data Selection for Goal-Oriented Chatbot Training Based on Sentence Embeddings
Mladen Dimovski, Claudiu Musat, Vladimir Ilievski +2
Spoken language understanding (SLU) systems, such as goal-oriented chatbots or personal assistants, rely on an initial natural language understanding (NLU) module to determine the…