Proceedings ArticleDOI
On the resemblance and containment of documents
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
Citations
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Mining social media: tracking content and predicting behavior
TL;DR: This thesis develops methods for tracking news content in social media, and predicts user behavior, and develops models for predicting popularity of news articles from several news agents in terms of the volume of comments they receive.
Patent
System for similar document detection
Ophir Frieder,Abdur R. Chowdhury +1 more
TL;DR: In this article, a document is compared to the documents in a document collection using a hash algorithm and collection statistics to detect if the document is similar to any document in the document collection.
Patent
Resource freshness and replication
TL;DR: In this article, a mechanism is described that detects when local resources are stale, i.e., when the time between a last successful synchronization activity and a current time exceeds a staleness value.
Proceedings ArticleDOI
Efficient estimation for high similarities using odd sketches
TL;DR: The Odd Sketch, a compact binary sketch for estimating the Jaccard similarity of two sets, provides a highly space-efficient estimator for sets of high similarity, which is relevant in applications such as web duplicate detection, collaborative filtering, and association rule learning.
Proceedings ArticleDOI
Cluster-based delta compression of a collection of files
TL;DR: This work proposes a framework for cluster-based delta compression that uses text clustering techniques to prune the graph of possible pairwise delta encodings and demonstrates the efficacy of this approach on collections of Web pages.
References
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Book
The Probabilistic Method
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).