Clustering Related Search Queries Based on User Intent, Google Research Paper

People today use search engines for all their information needs, but when they pose a particular search query, they typically have a specific underlying intent. Google in their recent paper (embedded) below presented at the International World Wide Web conference earlier this year, explored the problem of clustering the related search queries as a means […]

People today use search engines for all their information needs, but when they pose a particular search query, they typically have a specific underlying intent. Google in their recent paper (embedded) below presented at the International World Wide Web conference earlier this year, explored the problem of clustering the related search queries as a means of understanding the different intents underlying a given user query. "Our results show that underlying intents (clusters of related queries) almost always correspond to well-understood, high-level concepts.

For e.g., for mars, in addition to re-constructing each of the intents listed earlier, we also find distinct clusters grouping queries about NASA's missions to the planet, about specific interest in life on Mars, as well as a Japanese comic series, and a grocery chain named Mars. We found that our clustering approach yields better results than earlier approaches that either only used document-click or only query-session information," explained Google.

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