Giancarlo Frison Signals from the Noise

Catalog Entity Extraction for Search

Keyword extraction from search queries is a fundamental aspect of conversational commerce. In this article I illustrate a simple but effective way to get relevant entities from user’s utterances and rank them against an unstructured product catalog and an ontology database.

The primary purpose of a conversational application is to serve user demands, and when an user search in a e-commerce context, he is mostly looking for products. There is one main distinction that characterize a query when it is performed in the website rather than a messaging application. In the website, when users submit a query they already express their search intention, therefore the terms are usually concise and descriptive. Conversely, when inquiring a Chatbot, users use more expressive forms such as: Could you suggest me pale ale beers and ice creams for my party?. While the intention is deducted by a classification task, relevant terms for search, are just a subset of the entire sentence.

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