An end-to-end Generative Retrieval Method for Sponsored Search Engine --Decoding Efficiently into a Closed Target Domain

by   Yijiang Lian, et al.

In this paper, we present a generative retrieval method for sponsored search engine, which uses neural machine translation (NMT) to generate keywords directly from query. This method is completely end-to-end, which skips query rewriting and relevance judging phases in traditional retrieval systems. Different from standard machine translation, the target space in the retrieval setting is a constrained closed set, where only committed keywords should be generated. We present a Trie-based pruning technique in beam search to address this problem. The biggest challenge in deploying this method into a real industrial environment is the latency impact of running the decoder. Self-normalized training coupled with Trie-based dynamic pruning dramatically reduces the inference time, yielding a speedup of more than 20 times. We also devise an mixed online-offline serving architecture to reduce the latency and CPU consumption. To encourage the NMT to generate new keywords uncovered by the existing system, training data is carefully selected. This model has been successfully applied in Baidu's commercial search engine as a supplementary retrieval branch, which has brought a remarkable revenue improvement of more than 10 percents.


page 1

page 2

page 3

page 4


Exploiting Neural Query Translation into Cross Lingual Information Retrieval

As a crucial role in cross-language information retrieval (CLIR), query ...

ProphetNet-Ads: A Looking Ahead Strategy for Generative Retrieval Models in Sponsored Search Engine

In a sponsored search engine, generative retrieval models are recently p...

Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval

Query translation (QT) is a key component in cross-lingual information r...

Retrieve Synonymous keywords for Frequent Queries in Sponsored Search in a Data Augmentation Way

In sponsored search, retrieving synonymous keywords is of great importan...

Sharp Models on Dull Hardware: Fast and Accurate Neural Machine Translation Decoding on the CPU

Attentional sequence-to-sequence models have become the new standard for...

MobileNMT: Enabling Translation in 15MB and 30ms

Deploying NMT models on mobile devices is essential for privacy, low lat...

A Concept Knowledge-Driven Keywords Retrieval Framework for Sponsored Search

In sponsored search, retrieving synonymous keywords for exact match type...

Please sign up or login with your details

Forgot password? Click here to reset