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
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Book
Digital Forensic Science: Issues, Methods, and Challenges
TL;DR: The goal of this book is to provide a systematic technical overview of digital forensic techniques, primarily from the point of view of computer science, to put the field in the broader perspective of a host of related areas and gain better insight into the computational challenges facing forensics.
Using Sketches to Estimate Two-way and Multi-way Associations
TL;DR: This work generalizes sketches to estimate contingency tables and associations, using a maximum likelihood estimator to find the most likely contingency table given the sample, the margins (document frequencies) and the size of the collection.
Journal ArticleDOI
Sketching and Embedding are Equivalent for Norms
TL;DR: This work states that metric spaces in which distances can be estimated using efficient sketches are characterized by Guha and Indyk in 2006, and says that a sketching of a metric space is a good starting point for estimating distances.
Proceedings ArticleDOI
Structural Clustering of Machine-Generated Mail
Noa Avigdor-Elgrabli,Mark Cwalinski,Dotan Di Castro,Iftah Gamzu,Irena Grabovitch-Zuyev,Liane Lewin-Eytan,Yoelle Maarek +6 more
TL;DR: This work describes novel flexible-matching clustering methods that meet the key requirements of high intra-cluster similarity, adequate clusters size, and relatively small overall number of clusters for automatic mail extraction, and shows that strict structural matching is more adequate.
Proceedings ArticleDOI
Growing a Reduced Set of Mutation Operators
TL;DR: A novel procedure for choosing a reduced set of mutation operators based on a “growth model” is presented, which uses a greedy approach to successively choose the mutation operator that increases the overall mutation score the most, adding mutation operators to the set until the tests that kill all mutants from the reduced set kill all mutant from the complete set of mutants.
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).