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Integrating Lexical and Temporal Signals in Neural Ranking Models for Searching Social Media Streams
To our knowledge, we are the first to integrate lexical and temporal signals in an end-to-end neural network architecture, in which existing neural ranking models are used to generate query-document similarity vectors that feed into a bidirectional LSTM layer for temporal modeling.
Exploring the Effectiveness of Convolutional Neural Networks for Answer Selection in End-to-End Question Answering
Most work on natural language question answering today focuses on answer selection: given a candidate list of sentences, determine which contains the answer.
Estimating Code-Switching on Twitter with a Novel Generalized Word-Level Language Detection Technique
Word-level language detection is necessary for analyzing code-switched text, where multiple languages could be mixed within a sentence.
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