Two Efficient Algorithms for Linear Time Suffix Array Construction

Nong, Ge; Zhang, Sen; Chan, Wai Hong

doi:10.1109/tc.2010.188

Cited by 145 publications

(148 citation statements)

References 15 publications

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“…These include (gapped) q-grams and a suffix array using a linear time construction algorithm [NZC11].…”

Section: Poster 40mentioning

confidence: 99%

Poster abstracts of GCB 2015

Eisenacher

Rahnenführer

Mosig

et al. 2015

Preprint

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EDITORIALThe poster session is and always has been an important part of the German Conference on Bioinformatics, as it gives an excellent overview of current bioinformatics research topics in Germany and other countries. At GCB 2015, there will be 57 posters on display, whose abstracts (together with the poster number) are collected in the present document. Poster prizes will be presented to the presenting author(s) of the best posters, as selected by the program committee. PrePrintsMining for common reactivity patterns of human autoantibodies against endogenous protein targets using clustered autoantibody reactivities Hans-Dieter Zucht, Daniel Chamrad, Anna Telaar, Martin Gamer, Stefan Vordenbäumen, Peter Schulz-Knappe, Matthias Schneider and Petra

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“…These include (gapped) q-grams and a suffix array using a linear time construction algorithm [NZC11].…”

Section: Poster 40mentioning

confidence: 99%

Poster abstracts of GCB 2015

Eisenacher

Rahnenführer

Mosig

et al. 2015

Preprint

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“…The authors extract maximal substrings, i.e., the substrings each giving a smaller number of occurrences even by appending only one character to its head or tail, as elementary building blocks of documents. The extraction can be efficiently implemented and conducted as is shown in the works related to suffix array or Burrows-Wheeler transform [7,1,14,16]. While Zhang et al [25] also provide a method for extracting a special set of substrings, this is not the set of maximal substrings.…”

Section: Previous Workmentioning

confidence: 99%

Clustering Documents with Maximal Substrings

Masada

Takasu

Shibata

et al. 2012

Enterprise Information Systems

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Abstract. This paper provides experimental results showing that we can use maximal substrings as elementary building blocks of documents in place of the words extracted by a current state-of-the-art supervised word extraction. Maximal substrings are defined as the substrings each giving a smaller number of occurrences even by appending only one character to its head or tail. The main feature of maximal substrings is that they can be extracted quite efficiently in an unsupervised manner. We extract maximal substrings from a document set and represent each document as a bag of maximal substrings. We also obtain a bag of words representation by using a state-of-the-art supervised word extraction over the same document set. We then apply the same document clustering method to both representations and obtain two clustering results for a comparison of their quality. We adopt a Bayesian document clustering based on Dirichlet compound multinomials for avoiding overfitting. Our experiment shows that the clustering quality achieved with maximal substrings is acceptable enough to use them in place of the words extracted by a supervised word extraction.

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“…Itoh e Tanaka [1999], Seward [2000] e Manzini e Ferragina [2004] propuseram algoritmos que utilizam pouca memória auxiliar durante a construção e Maniscalco e Puglisi [2006], Larsson e Sadakane [2007] propuseram algoritmos não lineares, porém rápidas na prática. Por fim, [Nong et al, 2009[Nong et al, , 2011 propuseram os primeiros algoritmos de construção em tempo O(n), rápidos na prática, e que utilizam pouca memória auxiliar. Os trabalhos de Puglisi et al [2007]; Dhaliwal et al [2012] apresentam revisões e comparam muitos desses algoritmos na prática.…”

Section: Etapa De Construçãounclassified

“…Os trabalhos de Puglisi et al [2007]; Dhaliwal et al [2012] apresentam revisões e comparam muitos desses algoritmos na prática. Atualmente o algoritmo proposto por Nong et al [2011] apresenta-se como o algoritmo mais eficiente para construção de vetores de sufixo em memória interna.…”

Section: Etapa De Construçãounclassified

“…Bingmann et al [2013] propuseram o primeiro algoritmo para a construção de vetores de sufixo aumentado com o vetor LCP em memória externa. O algoritmo proposto, chamado de eSAIS, estende o algoritmo de construção de vetores de sufixo em memória interna SAIS [Nong et al, 2011]. De forma resumida, o algoritmo original SAIS seleciona e ordena um subconjunto dos sufixos de T , e utiliza a ordem desses sufixos já ordenados para induzir a ordem dos sufixos ainda não ordenados [Dhaliwal et al, 2012].…”

Section: Dementiev Et Al (2005 2008)unclassified

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Um algoritmo para a construção de vetores de sufixo generalizados em memória externa

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Two Efficient Algorithms for Linear Time Suffix Array Construction

Cited by 145 publications

References 15 publications

Poster abstracts of GCB 2015

Poster abstracts of GCB 2015

Clustering Documents with Maximal Substrings

Um algoritmo para a construção de vetores de sufixo generalizados em memória externa

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