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Deep Natural Language Processing for LinkedIn Search

2021-08-16 · Weiwei Guo, Xiaowei Liu, Sida Wang, Michaeel Kazi, Zhiwei Wang, Zhoutong Fu, Jun Jia, Liang Zhang, Huiji Gao, Bo Long

Many search systems work with large amounts of natural language data, e.g., search queries, user profiles, and documents. Building a successful search system requires a thorough understanding of textual data semantics, where deep learning based natural language processing techniques (deep NLP) can be of great help. In this paper, we introduce a comprehensive study for applying deep NLP techniques to five representative tasks in search systems: query intent prediction (classification), query tagging (sequential tagging), document ranking (ranking), query auto completion (language modeling), and query suggestion (sequence to sequence). We also introduce BERT pre-training as a sixth task that can be applied to many of the other tasks. Through the model design and experiments of the six tasks, readers can find answers to four important questions: (1). When is deep NLP helpful/not helpful in search systems? (2). How to address latency challenges? (3). How to ensure model robustness? This work builds on existing efforts of LinkedIn search, and is tested at scale on LinkedIn's commercial search engines. We believe our experiences can provide useful insights for the industry and research communities.

📄 PDF Abstract BibTeX arXiv:2108.13300

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Document RankingLanguage ModelingLanguage Modelling

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Multi-Head Attention 설명 없음

Attention 설명 없음

Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.

Weight Decay 설명 없음

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Adam 설명 없음

Dropout Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability $p$ (a common value is…

Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…

Deep Natural Language Processing for LinkedIn Search Systems

2021-07-30 · Weiwei Guo, Xiaowei Liu, Sida Wang, Michaeel Kazi 외

Many search systems work with large amounts of natural language data, e.g., search queries, user profiles and documents, where deep learning based natural language processing techniques (deep NLP) can be of great help. I…

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