Plagiarism detection using document similarity based on distributed representation
| Autor: | Kensuke Baba, Toshiro Minami, Tetsuya Nakatoh |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Document similarity
Basis (linear algebra) Computer science Value (computer science) 02 engineering and technology computer.software_genre Distributed representation Longest common subsequence problem Similarity (network science) Simple (abstract algebra) 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences 020201 artificial intelligence & image processing Plagiarism detection Data mining computer General Environmental Science |
| Zdroj: | Procedia Computer Science. 111:382-387 |
| ISSN: | 1877-0509 |
| Popis: | Accurate methods are required for plagiarism detection from documents. Generally, plagiarism detection is implemented on the basis of similarity between documents. This paper evaluates the validity of using distributed representation of words for defining a document similarity. This paper proposes a plagiarism detection method based on the local maximal value of the length of the longest common subsequence (LCS) with the weight defined by a distributed representation. The proposed method and other two straightforward methods, which are based on the simple length of LCS and the local maximal value of LCS with no weight, are applied to the dataset of a plagiarism detection competition. The experimental results show that the proposed method is useful in the applications that need a strict detection of complex plagiarisms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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