This project aims to explore the possibilities of one of the most state of the art problem in Data Mining which is Authorship Attribution. In this research, we use word networks to create graphs of different texts by multiple authors. Then the comparison happens in these word networks to see various attributes associated with authorship attribution and how similar or different they are for texts from same authors for example. The project aims to use this data to evaluate the suitability of word networks as an appropriate data structure for this problem and if it is, then find suitable algorithms for this problem.Bachelor of Engineering (Computer Science
Paper and data on Authorship attribution with supervised machine-learning, applied on web and social...
The relative frequencies of letter pairs within text samples can be used in authorship studies. Neur...
We apply the integrated syntactic graph feature extraction methodology to the task of automatic auth...
This project aims to explore the possibilities of one of the most state of the art problem in Data M...
In this paper, it aims to explore authorship attribution through a set of features that are extracte...
In this paper, we explore a set of novel fea-tures for authorship attribution of documents. These fe...
Network data analysis is an emerging area of study that applies quantitative analysis to complex dat...
This paper covers a text classification problem: the identification of the author of a text. It is n...
Automatic identification of authorship in disputed documents has benefited from complex network theo...
<div><p>The authorship attribution is a problem of considerable practical and technical interest. Se...
Abstract—A method for authorship attribution based on func-tion word adjacency networks (WANs) is in...
This is the author accepted manuscript. The final version is available from Springer nature via the ...
Many features of texts and languages can now be inferred from statistical analyses using concepts fr...
The world is generating more and more network data in many different areas (e.g., sensor networks, s...
The paper addresses two problems: (a) whether and how tools developed to analyze network structures ...
Paper and data on Authorship attribution with supervised machine-learning, applied on web and social...
The relative frequencies of letter pairs within text samples can be used in authorship studies. Neur...
We apply the integrated syntactic graph feature extraction methodology to the task of automatic auth...
This project aims to explore the possibilities of one of the most state of the art problem in Data M...
In this paper, it aims to explore authorship attribution through a set of features that are extracte...
In this paper, we explore a set of novel fea-tures for authorship attribution of documents. These fe...
Network data analysis is an emerging area of study that applies quantitative analysis to complex dat...
This paper covers a text classification problem: the identification of the author of a text. It is n...
Automatic identification of authorship in disputed documents has benefited from complex network theo...
<div><p>The authorship attribution is a problem of considerable practical and technical interest. Se...
Abstract—A method for authorship attribution based on func-tion word adjacency networks (WANs) is in...
This is the author accepted manuscript. The final version is available from Springer nature via the ...
Many features of texts and languages can now be inferred from statistical analyses using concepts fr...
The world is generating more and more network data in many different areas (e.g., sensor networks, s...
The paper addresses two problems: (a) whether and how tools developed to analyze network structures ...
Paper and data on Authorship attribution with supervised machine-learning, applied on web and social...
The relative frequencies of letter pairs within text samples can be used in authorship studies. Neur...
We apply the integrated syntactic graph feature extraction methodology to the task of automatic auth...