scispace - formally typeset
Proceedings ArticleDOI

On the resemblance and containment of documents

Andrei Z. Broder
- 11 Jun 1997 - 
- pp 21-29
TLDR
The basic idea is to reduce these issues to set intersection problems that can be easily evaluated by a process of random sampling that could be done independently for each document.
Abstract
Given two documents A and B we define two mathematical notions: their resemblance r(A, B) and their containment c(A, B) that seem to capture well the informal notions of "roughly the same" and "roughly contained." The basic idea is to reduce these issues to set intersection problems that can be easily evaluated by a process of random sampling that can be done independently for each document. Furthermore, the resemblance can be evaluated using a fixed size sample for each document. This paper discusses the mathematical properties of these measures and the efficient implementation of the sampling process using Rabin (1981) fingerprints.

read more

Content maybe subject to copyright    Report

Citations
More filters
Dissertation

Real-time event detection in massive streams

Sasa Petrovic
TL;DR: A modern approach to event detection that scales to unbounded streams of text, without sacrificing accuracy is proposed, which enables us to detect events from large streams like Twitter, which none of the previous approaches were able to do.
Patent

Granular control over the authority of replicated information via fencing and unfencing

TL;DR: In this article, a method and system for controlling which content gets precedence and is replicated in a replica set is presented. But this method is not suitable for file-based systems.
Proceedings ArticleDOI

Fast Similarity Sketching

TL;DR: In this article, the authors present a new sketch which obtains essentially the best of both worlds: a fast O(t log t + |A|) expected running time while getting the same strong concentration bounds as MinHash, and demonstrate the power of their new sketch by considering popular applications in large-scale classification with linear SVM as introduced by Li et al.
Journal ArticleDOI

AccountTrade: Accountability Against Dishonest Big Data Buyers and Sellers

TL;DR: A uniqueness index is defined and proposed, which is a new rigorous measurement of the data uniqueness for this purpose, and several accountable trading protocols are presented to enable data brokers to blame the misbehaving entities when misbehavior is detected.
Journal ArticleDOI

Overlap graphs and de Bruijn graphs: data structures for de novo genome assembly in the big data era

TL;DR: The most recent advances in the problem of constructing, representing and navigating assembly graphs, focusing on very large datasets are discussed, and some computational techniques to compactly store graphs while keeping all functionalities intact are explored.
References
More filters
Book

The Probabilistic Method

Joel Spencer
TL;DR: A particular set of problems - all dealing with “good” colorings of an underlying set of points relative to a given family of sets - is explored.
Journal ArticleDOI

Syntactic clustering of the Web

TL;DR: An efficient way to determine the syntactic similarity of files is developed and applied to every document on the World Wide Web, and a clustering of all the documents that are syntactically similar is built.
Journal ArticleDOI

Min-Wise Independent Permutations

TL;DR: This research was motivated by the fact that such a family of permutations is essential to the algorithm used in practice by the AltaVista web index software to detect and filter near-duplicate documents.
Proceedings Article

Finding similar files in a large file system

TL;DR: Application of sif can be found in file management, information collecting, program reuse, file synchronization, data compression, and maybe even plagiarism detection.
Proceedings ArticleDOI

Copy detection mechanisms for digital documents

TL;DR: This paper proposes a system for registering documents and then detecting copies, either complete copies or partial copies, and describes algorithms for such detection, and metrics required for evaluating detection mechanisms (covering accuracy, efficiency, and security).