Efficient Document Indexing Using Pivot Tree
May 21, 2016 Β· Declared Dead Β· π arXiv.org
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Authors
Gaurav Singh, Benjamin Piwowarski
arXiv ID
1605.06693
Category
cs.IR: Information Retrieval
Cross-listed
cs.LG
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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