A bit-string longest-common-subsequence algorithm

Allison, Lloyd; Dix, Trevor I.

doi:10.1016/0020-0190(86)90091-8

Cited by 103 publications

(81 citation statements)

References 10 publications

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“…The details of these datasets will be described later. Sorted neighborhood (Hernández and Stolfo, 1995) is used as a blocking algorithm and Longest Common Subsequence (LCS) (Allison and Dix, 1986) is utilized as a similarity function. In the next step, SVM, C4.5, Naïve bayes and Bayesian network classifiers are applied on selected training records in order to train and build the models.…”

Section: Methodsmentioning

confidence: 99%

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A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model

Ektefa¹,

Sidi²,

Ibrahim³

et al. 2011

Journal of Computer Science

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Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in different studies. In order to utilize the supervised classification algorithms without consuming a lot of time for labeling data manually, a two step method which selects the training data automatically has been proposed in previous studies. However, the effectiveness of different classification techniques is the issue which should be taken into accounts in record linkage systems in order to classify records more accurately. Approach: To determine and compare the effectiveness of different supervised classification techniques in an unsupervised manner, some of the prominent classification methods are applied in duplicate records detection. Duplicate detection and classification of records in two real world datasets, namely Cora and Restaurant is experimented by Support Vector Machines, Naïve Bayes, Decision Tree and Bayesian Networks which are regarded as some prominent classification techniques. Results: As experimental results show, while Support Vector Machines outperforms with F-measure of 96.27% in Restaurant dataset, for Cora dataset, the effectiveness of Naïve Bayes is the best and it leads to an improvement with F-measure of 89.7%. Conclusion/Recommendation: The result of detecting duplicate records with different classification techniques tends to fluctuate depending on the dataset which is used. Moreover, Support Vector Machines and Naïve Bayes outperform other methods in our experiments.

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Section: Methodsmentioning

confidence: 99%

“…Longest Common Subsequence (LCS) is an algorithm proposed in (Allison and Dix, 1986) and is used to find the longest subsequences which are common in two strings. It has been successfully experimented in several contexts such as record linkage.…”

Section: Methodsmentioning

confidence: 99%

A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model

Ektefa¹,

Sidi²,

Ibrahim³

et al. 2011

Journal of Computer Science

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“…It is important to observe that in all cases even ED 2 .x W y/ is significantly better than either H.x W y/, ED.x W y/, or ID.x W y/ currently in use. generalizations of the edit and insertion-deletion distances, and can be implemented in a computationally efficient way by means of the bit-vector approach to computing a dynamic programming matrix (Allison and Dix, 1986;Myers, 1999;Crochemore et al, 2001;Hyyrö et al, 2005).…”

Section: Hamming Edit and Insertion-deletion Similaritymentioning

confidence: 99%

New, Improved, and Practical k-Stem Sequence Similarity Measures for Probe Design

Macula

Schliep

Bishop

et al. 2008

Journal of Computational Biology

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We define new measures of sequence similarity for oligonucleotide probe design. These new measures incorporate the nearest neighbor k-stem motifs in their definition, but can be efficiently computed by means of a bit-vector method. They are not as computationally costly as algorithms that predict nearest neighbor hybridization potential. Our new measures for sequence similarity correlate significantly better with nearest neighbor thermodynamic predictions than either BLAST or the standard edit or insertion-deletion defined similarities already in use in many different probe design applications.

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“…. , 4]), after stopword removal, using greedy string tiling (Wise, 1996), longest common subsequences (Allison and Dix, 1986), Jaccard coefficient (Jaccard, 1901), word containment (Lyon et al, 2001), and cosine similarity. We also apply partial tree kernels (Moschitti, 2006) on shallow syntactic trees.…”

Section: Baseline Featuresmentioning

confidence: 99%

Thread-Level Information for Comment Classification in Community Question Answering

Barrón-Cedeño¹,

Filice

Martino³

et al. 2015

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Confere

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Community Question Answering (cQA) is a new application of QA in social contexts (e.g., fora). It presents new interesting challenges and research directions, e.g., exploiting the dependencies between the different comments of a thread to select the best answer for a given question. In this paper, we explored two ways of modeling such dependencies: (i) by designing specific features looking globally at the thread; and (ii) by applying structure prediction models. We trained and evaluated our models on data from SemEval-2015 Task 3 on Answer Selection in cQA. Our experiments show that: (i) the thread-level features consistently improve the performance for a variety of machine learning models, yielding state-of-the-art results; and (ii) sequential dependencies between the answer labels captured by structured prediction models are not enough to improve the results, indicating that more information is needed in the joint model.

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A bit-string longest-common-subsequence algorithm

Cited by 103 publications

References 10 publications

A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model

A Comparative Study in Classification Techniques for Unsupervised Record Linkage Model

New, Improved, and Practical k-Stem Sequence Similarity Measures for Probe Design

Thread-Level Information for Comment Classification in Community Question Answering

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