Bing applies AI and natural language models to autosuggest, People Also Ask

Intelligent answers and semantic highlighting are also rolling out to more markets.

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Bing is now using natural language generation models (models that generate text) to improve its autosuggest and People Also Ask (PAA) features, the company announced Wednesday. It is also expanding the use of natural language representation models to extend its question answering and semantic highlighting features globally.

Real-time phrase suggestions. Bing’s automatically generated search suggestions now make use of Microsoft Turing Natural Language Generation (T-NLG) Next Phase Prediction to present full phrase suggestions in real-time. This expands the scope of autosuggestions, which may also improve the user experience.

Bing Autosuggest Natural Language Models
Bing uses Next Phase Prediction to make suggestions beyond what users have historically searched for. Source: Bing.

In the example above, Bing suggests an entire word to complete the user’s query. As part of Microsoft’s AI at Scale initiative, the company has been building deep learning models that enable Bing to suggest queries on the fly. Previously, autosuggestions were constrained to information from previous queries asked by users and confined to the current word being typed.

Generating question-answer pairs for PAA. Bing is also using a generative model to identify question-answer pairs within documents. When those documents appear on the search results, it then uses the generated question-answer pairs to bolster the PAA box (in addition to data from similar questions that have previously been asked by users), as seen below.

Bing People Also Ask Example
Bing’s People Also Ask (PAA) box uses a generative model to supplement data from similar questions that have previously been asked by users. Source: Bing.

Other features rollout globally thanks to AI language models. Using its Turing Universal Language Representation (T-ULR) model, Bing has also expanded its intelligent answers to over 100 languages.

Semantic highlighting, which presents relevant information from meta descriptions in search listings in bold text, can now identify and highlight answers in all languages as well. This feature was previously highly dependent on matching keywords within a search query, which was an issue when the query was presented in the form of a question.

Why we care. The improved PAA box and autosuggest features are two more examples of AI being applied to natural language processing and understanding on the search results page. As models are developed and improved, search engines will be able to better understand content and how it relates to a user’s query, and those improvements will be present within both the search listings as well as the features that populate the search results page.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

About the author

George Nguyen
George Nguyen is the Director of SEO Editorial at Wix, where he manages the Wix SEO Learning Hub. His career is focused on disseminating best practices and reducing misinformation in search. George formerly served as an editor for Search Engine Land, covering organic and paid search.

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