  Fashion knowledge plays a pivotal role in helping people in their dressing.
In this paper, we present a novel system to automatically harvest fashion
knowledge from social media. It unifies three tasks of occasion, person and
clothing discovery from multiple modalities of images, texts and metadata. A
contextualized fashion concept learning model is applied to leverage the rich
contextual information for improving the fashion concept learning performance.
At the same time, to counter the label noise within training data, we employ a
weak label modeling method to further boost the performance. We build a website
to demonstrate the quality of fashion knowledge extracted by our system.
