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Reports (Research Report) Year : 2016

Efficient Document Indexing Using Pivot Tree

Gaurav Singh
  • Function : Author
Benjamin Piwowarski


We present a novel method for efficiently searching top-k neighbors for documents represented in high dimensional space of terms based on the cosine similarity. Mostly, documents are stored as bag-of-words tf-idf representation. One of the most used ways of computing similarity between a pair of documents is cosine similarity between the vector representations, but cosine similarity is not a metric distance measure as it doesn't follow triangle inequality, therefore most metric searching methods can not be applied directly. We propose an efficient method for indexing documents using a pivot tree that leads to efficient retrieval. We also study the relation between precision and efficiency for the proposed method and compare it with a state of the art in the area of document searching based on inner product.

Dates and versions

hal-01358681 , version 1 (01-09-2016)



Gaurav Singh, Benjamin Piwowarski. Efficient Document Indexing Using Pivot Tree. [Research Report] Sorbonne Universités, UPMC Univ Paris 06, CNRS, LIP6 UMR 7606. 2016. ⟨hal-01358681⟩
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