[PDF] Top 20 N-gram Based Text Classification According To Authorship
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N-gram Based Text Classification According To Authorship
... level n- ...level n- grams. Despite the fact that a great number of n- grams will contain both bytes we can benefit from this approach in aspect of more efficient memory ... See full document
5
Text Categorization for Authorship based on the Features of Lingual Conceptual Expression
... the text authorship identification is treated as text categorization as the researchers can accomplish the work according the text categorization ...punctuation, n-Gram ... See full document
7
A New Approach to Automated Text Readability Classification based on Concept Indexing with Integrated Part-of-Speech n-gram Features
... of text readability could outperform those measures based solely on one of the ...evaluate text readability. Results of their study showed that vocabulary-based ap- proach alone is better than ... See full document
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Text Classification and Threat Intelligence Generation for Industrial Control System Security
... paper, according to the classification of security events in the threat intelligence platform, we classify ICS security topic texts as information leakage, security vulnerabilities, network security, ... See full document
7
Authorship Attribution based on Data Compression for Telugu Text
... unknown text documents to the correct known author from a set of known author ...in authorship attribution becomes more important. The problem of authorship attribution is different from text ... See full document
5
Evaluation of N-gram Text Representations for Automated Essay-Type Grading Systems
... Computer Based Test [18] has been applied to academic assessment in order to ease the stress of evaluating student ...three n- gram text representations unigram, bigram and “unigram + bigram” ... See full document
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Language Independent n-Gram-Based Text Categorization with Weighting Factors: A Case Study
... new n-gram TC technique that is presented in this article is an improved variant of the basic n- gram technique, presented and used by Keselj et ...the authorship attribution problem. ... See full document
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Maximum Likelihood Text Classification Algorithm Using Machine Learning For Authorship Attribution
... ABSTRACT: Authorship attribution is a powerful technique and can be useful for forensic ...results. According to F-measure writeprints(limited) provide better generalization performance than ...KEYWORDS: ... See full document
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Hierarchical vs. flat n-gram-based text categorization: can we do better?
... The use of the Reuters hierarchies in the field of HTC dates back to at least 1997, when Koller and Sahami [20] proposed the use of a local classifier per parent node approach. Six years later Sun and his colleges [36] ... See full document
20
Language Identification of Short Text Segments with N-gram Models
... long text samples, but identification of very short strings still presents a ...classifier based on character n-gram models, and the ranking method by Cavnar and Trenkle ...the ... See full document
8
N gram based Machine Translation
... and text to speech synthesis (TTS) made it possible to envision the challenge of spoken language translation (SLT) (Kay, Gawron, and Norvig ...1992). According to this, SMT has also been approached from a ... See full document
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Identifying the L1 of non native writers: the CMU Haifa system
... general text classification and authorship identification, those used in identifying so-called translationese (Volansky et ...an n-gram language ... See full document
9
Comparative Analysis of N-gram Text Representation on Igbo Text Document Similarity
... of text such as resources and news articles online. Text similarity is of great importance in any text-based ...of n-gram text representation on Igbo text document ... See full document
7
Automated essay scoring with string kernels and word embeddings
... approach based on combining string kernels and word em- beddings for automatic essay ...strings based on counting common character n- grams, which are a low-level yet powerful type of feature, ... See full document
7
Delta vs N Gram Tracing: Evaluating the Robustness of Authorship Attribution Methods
... a text of unknown or disputed authorship based on quantitatively measured linguistic evidence (Juola, 2006; Koppel et ...is based on the assumption that individual writers have idiosyncratic ... See full document
6
Author Verification Using Common N Gram Profiles of Text Documents
... with authorship verification being the extreme case of an open-set problem with only one ...for authorship verification (Koppel and Schler, 2004) is successful for novel-length ...known authorship ... See full document
11
Incremental N gram Approach for Language Identification in Code Switched Text
... rule based classification system that can also be used for named entities and non-alphanumeric language ...built based on these ideas, I achieved an accuracy of above 94% for English-Nepali and above ... See full document
6
Domain Based Categorisation Using Adaptive Pre processing
... Abstract: As the number users accessing network for various purposes increases and simultaneously size of the Network and Internet traffic increase so, there is need for categorization web pages according to ... See full document
8
Domain Based Classification of Punjabi Text Documents
... Punjabi text documents as input and classify them into its corresponding classes using classification algorithm selected by ...Ontology Based Classification and Hybrid Approach. For Ontology ... See full document
8
A Joint Model of Text and Aspect Ratings for Sentiment Summarization
... Standard aspect-based summarization consists of two problems. The first is aspect identification and mention extraction. Here the goal is to find the set of relevant aspects for a rated entity and extract all ... See full document
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