Authorship Verification - An Approach based on Random Forest

07/29/2016
by   Promita Maitra, et al.
0

Authorship attribution, being an important problem in many areas in-cluding information retrieval, computational linguistics, law and journalism etc., has been identified as a subject of increasingly research interest in the re-cent years. In case of Author Identification task in PAN at CLEF 2015, the main focus was given on cross-genre and cross-topic author verification tasks. We have used several word-based and style-based features to identify the dif-ferences between the known and unknown problems of one given set and label the unknown ones accordingly using a Random Forest based classifier.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/26/2021

Vowel-based Meeteilon dialect identification using a Random Forest classifier

This paper presents a vowel-based dialect identification system for Meet...
research
01/22/2018

Siamese Neural Networks with Random Forest for detecting duplicate question pairs

Determining whether two given questions are semantically similar is a fa...
research
09/08/2017

CLaC at SemEval-2016 Task 11: Exploring linguistic and psycho-linguistic Features for Complex Word Identification

This paper describes the system deployed by the CLaC-EDLK team to the "S...
research
03/24/2022

Random Forest Regression for continuous affect using Facial Action Units

In this paper we describe our approach to the arousal and valence track ...
research
10/12/2020

A Lightweight Speaker Recognition System Using Timbre Properties

Speaker recognition is an active research area that contains notable usa...
research
11/26/2019

Random Forest as a Tumour Genetic Marker Extractor

Finding tumour genetic markers is essential to biomedicine due to their ...
research
10/26/2020

Data Segmentation via t-SNE, DBSCAN, and Random Forest

This research proposes a data segmentation technique which is easy to in...

Please sign up or login with your details

Forgot password? Click here to reset