Duplicate Detection in Documents and WebPages Using Improved Longest Common Subsequence and Documents Syntactical Structures
Abstract
This paper reports on experiments performed to investigate the use of a combined part of speech (POS) and an improved longest common subsequence (LCS) in the analysis and calculation of similarity between texts. The text's syntactical structures were used as a representation for documents. An improved LCS algorithm was applied to such a representation to compare and rank the documents according to the similarity of their representative string. The approach was applied in detecting duplicate documents within a corpus, and in the filtering of search engine results. Results obtained were encouraging.
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In contrast to many existing plagiarism detection systems that reduce the text into a set of tokens by removing stop words and stemming, the approach in [6], [12], and [13] reduces the text into a smaller set of syntactical tags, thus making use of most of the content.
“In contrast to many existing plagiarism detection systems that reduce the text into a set of tokens by removing stop words and stemming, the approach in [6], [12], and [13] reduces the text into a smaller set of syntactical tags, thus making use of most of the content.”
From Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods (2012) · cites this paper as [6]
SYN methods are based on decomposing documents into statements and extracting POS features.
“SYN methods [6], [12] are based on decomposing documents into statements and extracting POS features.”
From Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods (2012) · cites this paper as [6]
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Schleimer, S., S, W. D., & Aiken, A. (2003) · Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data · doi:10.1145/872757.872770 · Cited by 1,099 · see citing works
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Understanding Plagiarism Linguistic Patterns, Textual Features, and Detection Methods
Alzahrani, S. M., Salim, N., & Abraham, A. (2012) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2134847 · Cited by 299 · see citing works
- Authors
- Elhadi, M., & Al-Tobi, A.
- Affiliations
- Sultan Qaboos University (OM)
- ORCID
- Elhadi, Mohamed
- Venue
- 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology
- Publisher
- IEEE
- Published
- 2009
- Pages
- 679-684
- OpenAlex
- W2124185477
- Cited by
- 32
- References
- 1
- Citations by year
- 2022: 1 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 3 · 2017: 2 · 2016: 4 · 2015: 2 · 2014: 1 · 2013: 5 · 2012: 4
- FWCI
- 5.47
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Computer Sciences and Convergence Information Technology (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Data Quality and Management
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Text Analysis Techniques
- Keywords
- duplicate detection, longest common subsequence, part-of-speech tagging, syntactic structure, text similarity, document representation, document ranking, search result filtering, web pages
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