Due to rapid growth of research articles in various languages, cross-lingual plagiarism detection problem has received increasing interest in recent years. Cross-lingual plagiarism detection is more challenging task than monolingual plagiarism detection. This paper addresses the problem of cross-lingual plagiarism detection (CLPD) by proposing a method that combines keyphrases extraction, monolingual detection methods and machine learning approach. The research methodology used in this study has facilitated to accomplish the objectives in terms of designing, developing, and implementing an efficient Arabic – English cross lingual plagiarism detection.
This paper empirically evaluates five different monolingual plagiarism detection methods namely i)N-Grams Similarity, ii)Longest Common Subsequence, iii)Dice Coefficient, iv)Fingerprint based Jaccard Similarity and v) Fingerprint based Containment Similarity. In addition, three machine learning approaches namely i) naïve Bayes, ii) Support Vector Machine, and iii) linear logistic regression classifiers are used for Arabic-English Cross-language plagiarism detection. Several experiments are conducted to evaluate the performance of the key phrases extraction methods. In addition, Several experiments to investigate the performance of machine learning techniques to find the best method for Arabic-English Cross-language plagiarism detection.
According to the experiments of Arabic-English Cross-language plagiarism detection, the highest result was obtained using SVM classifier with 92% f-measure. In addition, the highest results were obtained by all classifiers are achieved, when most of the monolingual plagiarism detection methods are used.
Review: hindi question answering system using machine learning approach As an upshot of Natural Language Interface to Database (NLIDB), Question Answering System is relatively an Information Retrieval system which is suppose to reflect the user with the correct or closest results to the query being asked to the system in natural language. Information Retrieval and Information Extraction plays vital role in accomplishing the task of interaction between the user and the system. The paper discusses various ways and techniques of interaction between the user and the system along with different approaches. Machine Learning is one of the approaches which is preferred for the Question Answering System. Out of Supervised and unsupervised learning, supervised learning is taken priority here by going through numerous other techniques
