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arXiv · 1608.01247

Query Clustering using Segment Specific Context Embeddings

S. K Kolluru·Prasenjit Mukherjee
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Abstract

This paper presents a novel query clustering approach to capture the broad interest areas of users querying search engines. We make use of recent advances in NLP - word2vec and extend it to get query2vec, vector representations of queries, based on query contexts, obtained from the top search results for the query and use a highly scalable Divide & Merge clustering algorithm on top of the query vectors, to get the clusters. We have tried this approach on a variety of segments, including Retail, Travel, Health, Phones and found the clusters to be effective in discovering user's interest areas which have high monetization potential.

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BibTeXRIS

S. K Kolluru, Prasenjit Mukherjee. 2016-08-03. Query Clustering using Segment Specific Context Embeddings. https://arxiv.org/abs/1608.01247

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