Distant-Supervised Slot-Filling for E-Commerce Queries

by   Saurav Manchanda, et al.

Slot-filling refers to the task of annotating individual terms in a query with the corresponding intended product characteristics (product type, brand, gender, size, color, etc.). These characteristics can then be used by a search engine to return results that better match the query's product intent. Traditional methods for slot-filling require the availability of training data with ground truth slot-annotation information. However, generating such labeled data, especially in e-commerce is expensive and time-consuming because the number of slots increases as new products are added. In this paper, we present distant-supervised probabilistic generative models, that require no manual annotation. The proposed approaches leverage the readily available historical query logs and the purchases that these queries led to, and also exploit co-occurrence information among the slots in order to identify intended product characteristics. We evaluate our approaches by considering how they affect retrieval performance, as well as how well they classify the slots. In terms of retrieval, our approaches achieve better ranking performance (up to 156 Okapi BM25. Moreover, our approach that leverages co-occurrence information leads to better performance than the one that does not on both the retrieval and slot classification tasks.



page 1

page 2

page 3

page 4


Intent term selection and refinement in e-commerce queries

In e-commerce, a user tends to search for the desired product by issuing...

Joint Intent Detection And Slot Filling Based on Continual Learning Model

Slot filling and intent detection have become a significant theme in the...

Distant Supervision for E-commerce Query Segmentation via Attention Network

The booming online e-commerce platforms demand highly accurate approache...

Simple is Better! Lightweight Data Augmentation for Low Resource Slot Filling and Intent Classification

Neural-based models have achieved outstanding performance on slot fillin...

Comparing Convolutional Neural Networks to Traditional Models for Slot Filling

We address relation classification in the context of slot filling, the t...

Slot Filling for Biomedical Information Extraction

Information Extraction (IE) from text refers to the task of extracting s...

Intent Classification and Slot Filling for Privacy Policies

Understanding privacy policies is crucial for users as it empowers them ...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.