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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Journal ArticleDOI
An Indexing Scheme and Descriptor for 3D Object Retrieval Based on Local Shape Querying
TL;DR: A binary descriptor indexing scheme based on Hamming distance called the Hamming tree for local shape queries is presented and a new binary clutter resistant descriptor named Quick Intersection Count Change Image (QUICCI) is introduced.
Dissertation
Document plagiarism detection algorithm using semantic networks
Ahmed Muftah,Ahmed Jabr +1 more
TL;DR: An algorithm for plagiarism detection over the Web using semantic networks is proposed and results show that an appropriate semantic representation of sentences derived from WordNet’s relations outperforms N-grams with different similarity measures in detecting the plagiarized sentences.
Scalable Private Set Intersection Cardinality for Capture-Recapture with Multiple Private Datasets
TL;DR: This work proposes an improved technique based on commutative encryption and deterministic hash-based sampling that is secure and scalable, and also prevents so-called probing attacks.
Proceedings ArticleDOI
What's Happening and What Happened: Searching the Social Web
TL;DR: The goal is to find links that are relevant on social networks as a mechanism to discover what people are talking about at a given point in time and make such information searchable and persistent.
Journal ArticleDOI
A Near-Duplicate Detection Algorithm to Facilitate Document Clustering
TL;DR: The experimental results show that the algorithm detecting, and optionally removing duplicate and near duplicate documents which are used to perform clustering of documents outperforms in terms of similarity measures.
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).