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Monitoring geometrical properties of word embeddings for detecting the emergence of new topics.
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
Monitoring geometrical properties of word embeddings for detecting the emergence of new topics
Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution.
Transfer Learning for Linear Regression: a Statistical Test of Gain
Transfer learning, also referred as knowledge transfer, aims at reusing knowledge from a source dataset to a similar target one.
Textual Data for Time Series Forecasting
While ubiquitous, textual sources of information such as company reports, social media posts, etc.
How to detect novelty in textual data streams? A comparative study of existing methods
Since datasets with annotation for novelty at the document and/or word level are not easily available, we present a simulation framework that allows us to create different textual datasets in which we control the way novelty occurs.
