Natural Language Processing as Feature Extraction Method for Building Better Predictive Models

2017 ◽  
pp. 1913-1937
Author(s):  
Goran Klepac ◽  
Marko Velić
Keyword(s):  
Feature Extraction ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Predictive Models ◽  
Extraction Method ◽  
Feature Extraction Method

scholarly journals DYPLODOC: Dynamic Plots for Document Classification

2021 ◽  
Author(s):  
Anastasia Malysheva ◽  
Alexey Tikhonov ◽  
Ivan P. Yamshchikov
Keyword(s):  
Feature Extraction ◽  
Natural Language Processing ◽  
Language Processing ◽  
Narrative Analysis ◽  
Extraction Method ◽  
Feature Extraction Method ◽  
Narrative Generation ◽  
Modern Natural ◽  
Meta Information ◽  
Tv Shows

Narrative generation and analysis are still on the fringe of modern natural language processing yet are crucial in a variety of applications. This paper proposes a feature extraction method for plot dynamics. We present a dataset that consists of the plot descriptions for thirteen thousand TV shows alongside meta-information on their genres and dynamic plots extracted from them. We validate the proposed tool for plot dynamics extraction and discuss possible applications of this method to the tasks of narrative analysis and generation.

scholarly journals Keyword extraction method for machine reading comprehension based on natural language processing

2021 ◽  
Vol 1955 (1) ◽  
pp. 012072
Author(s):  
Ruiheng Li ◽  
Xuan Zhang ◽  
Chengdong Li ◽  
Zhongju Zheng ◽  
Zihang Zhou ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
Keyword Extraction ◽  
Machine Reading

Natural Language Processing as Feature Extraction Method for Building Better Predictive Models

2015 ◽  
pp. 141-166 ◽  
Author(s):  
Goran Klepac ◽  
Marko Velić
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Case Studies ◽  
Language Processing ◽  
Call Center ◽  
Future Research ◽  
Feature Extraction Method ◽  
First Case ◽  
Grammar Rules ◽  
Mining Projects

This chapter covers natural language processing techniques and their application in predicitve models development. Two case studies are presented. First case describes a project where textual descriptions of various situations in call center of one telecommunication company were processed in order to predict churn. Second case describes sentiment analysis of business news and describes practical and testing issues in text mining projects. Both case studies depict different approaches and are implemented in different tools. Language of the texts processed in these projects is Croatian which belongs to the Slavic group of languages with more complex morphologies and grammar rules than English. Chapter concludes with several points on the future research possible in this domain.

Detection of Cyberbullying on Social Media Using Machine learning

2021 ◽  
Vol 9 (10) ◽  
pp. 1401-1409
Author(s):  
Mitta Roja
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Feature Extraction ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Hate Speech ◽  
Text Data ◽  
Model Based

Abstract: Cyberbullying is a major problem encountered on internet that affects teenagers and also adults. It has lead to mishappenings like suicide and depression. Regulation of content on Social media platorms has become a growing need. The following study uses data from two different forms of cyberbullying, hate speech tweets from Twittter and comments based on personal attacks from Wikipedia forums to build a model based on detection of Cyberbullying in text data using Natural Language Processing and Machine learning. Threemethods for Feature extraction and four classifiers are studied to outline the best approach. For Tweet data the model provides accuracies above 90% and for Wikipedia data it givesaccuracies above 80%. Keywords: Cyberbullying, Hate speech, Personal attacks,Machine learning, Feature extraction, Twitter, Wikipedia

scholarly journals Ocean Coefficient: A Feature Extraction Technique for Five Factor Model based Classifications

2020 ◽  
Vol 9 (4) ◽  
pp. 1841-1844
Keyword(s):  
Feature Extraction ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Factor Model ◽  
Five Factor Model ◽  
Current Paper ◽  
Extraction Technique ◽  
Model Based ◽  
Feature Extraction Technique

Natural Language Processing has opened up several avenues in the field of research and developments. It has supported wide variety of applications, but still the opportunities are enormous for the researchers to look into several other aspects in the discovery of new dimensions. In this regard the current paper is trying to introduce a revolutionary feature extraction technique, particularly for the studies/research corresponding to five factor model based behaviour analysis.

scholarly journals Evaluating an Aspect Extraction Method for Opinion Mining in the Portuguese Language

2020 ◽  
Author(s):  
Breno Cardoso ◽  
Denilson Pereira
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
English Language ◽  
Opinion Mining ◽  
Aspect Extraction ◽  
Automatic Interpretation ◽  
Other Consumers

The opinion issued by consumers of products and services has become increasingly valued, both by other consumers and by companies. The automatic interpretation of review texts to generate information is of paramount importance. With opinion mining at the aspect level, it is possible to extract and summarize opinions about different components of a product or service. This paper evaluates the behavior of a method for extracting aspects using natural language processing tools for the Portuguese language. The aim is to investigate the maturity of the tools for Portuguese compared to the already consolidated tools for the English language. The evaluation was carried out in three datasets from two different domains with original texts in Portuguese and their translations into English, and vice versa, and the results indicate that there is no difference between languages.

Sign in / Sign up

Export Citation Format

Share Document