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Personality Recognition Applying Machine Learning Techniques on Source Code Metrics

Hugo A. Castellanos
2016 Forum for Information Retrieval Evaluation  
In this paper source code metrics are used to consolidate programmers profiles with the purpose to identify different personality traits using machine learning algorithms.  ...  This work was done as part of the Personality Recognition in SOurce COde (PR-SOCO) shared task in the Forum for Information Retrieval Evaluation 2016 (FIRE 2016).  ...  In addition, machine learning methods are used to predict the personality traits based on the extracted source code metrics. The rest of this paper is organized as follows.  ... 
dblp:conf/fire/Castellanos16 fatcat:n6tlknsa6ngibhamgl26vfagnq

Survey of biometric pattern recognition via machine learning techniques

Nicolas Ortiz, Ruben Dario Hernandez, Robinson Jimenez, Mauricio Mauledeoux, Oscar Aviles
2018 Contemporary Engineerng Sciences  
In this sense, in this paper it is presented an overview of some Machine Learning approaches for biometric pattern recognition.  ...  However, some of these characteristics are hard to obtain in a properly way and it is necessary to use several algorithms both to process them and to use them on a security systems.  ...  The authors are grateful to the Nueva Granada Military University, which, through its Vice chancellor for research, finances the present project with code IMP-ING-2290 and titled "Prototype of robot assistance  ... 
doi:10.12988/ces.2018.84166 fatcat:hxerqowhvvhbblfbjehw222sdu

PRHLT at PR-SOCO: A Regression Model for Predicting Personality Traits from Source Code

Maite Giménez, Roberto Paredes
2016 Forum for Information Retrieval Evaluation  
This paper describes our participation in the PAN@FIRE Personality Recognition in Source Code (PR-SOCO) 2016 shared task.  ...  Regardless of the approach, a regression model was trained to classify the personality traits of the author of a sample of source code.  ...  Our results confirm that the preprocessing phase also has a negative impact on the personality recognition task from source code.  ... 
dblp:conf/fire/GimenezP16 fatcat:73n7qi5hzrba3jpnh5tmfsighy

The Right Tool for the Job: Open-Source Auditing Tools in Machine Learning [article]

Cherie M Poland
2022 arXiv   pre-print
The ability to freely access open-source auditing tools removes barriers to fairness assessment at the most basic levels of machine learning.  ...  The exemplary tools highlighted herein are open-source with software or code-base repositories available that can be used immediately by anyone worldwide.  ...  TECHNIQUES In recent years several machine learning interpretability techniques have emerged that can be used to explain the machine learning model results in terms of individual input feature contributions  ... 
arXiv:2206.10613v1 fatcat:cesbmgmdpzc6xpzkjwgb7aka3q

Personality Classification from Online Text using Machine Learning Approach

Alam Sher Khan, Hussain Ahmad, Muhammad Zubair, Furqan Khan, Areeba Arif, Hassan Ali
2020 International Journal of Advanced Computer Science and Applications  
In this proposed work, Machine Learning Technique, XGBoost classifier is used to predict four personality traits based on Myers-Briggs Type Indicator (MBTI) model, namely Introversion-Extroversion(I-E)  ...  The skewness of the dataset is the main issue associated with the prior work, which is minimized by applying Re-sampling technique namely random over-sampling, resulting in better performance.  ...  The existing works on personality recognition from social media text is based on supervised machine learning techniques applied on benchmarks dataset [6] , [7] , [8] .  ... 
doi:10.14569/ijacsa.2020.0110358 fatcat:f4rmhrl2yffm7bm3jeq6gsgwym


Sakshi .
2018 International Journal of Advanced Research in Computer Science  
Named Entity Recognition (NER) is the part of Information Extraction which is used to extract important information from the code-mixed and informal data and then classifies these extracting named entities  ...  This paper provides a survey of various methods and techniques which are being used in the extraction of proper nouns appeared in the document.  ...  Results are based on the performance metrics.  ... 
doi:10.26483/ijarcs.v9i3.6093 fatcat:dul72z4x3rgmngtsmy4vjourny

Real Time Face Detection using Improvised Machine Learning Algorithm

Prachi Satpute
2020 International Journal for Research in Applied Science and Engineering Technology  
Open-CV uses machine learning algorithms to search for faces within a picture. In this system we already store some images of the person in our database along with his details.  ...  In this work, to identify a face, we are using Machine learning algorithms and python as the programming language.  ...  OpenCV is the huge open-source library for the computer vision, machine learning, and image processing.  ... 
doi:10.22214/ijraset.2020.32477 fatcat:w5olxhtqo5ailgrw5hd5qlovoi

Attendance System Using Face Recognition

Ojus Arora, Ravi Purohit, Hemashree Samant, Archana Gulati
2020 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
Authentication is one of the significant issues in the era of information system. Among other things, human face recognition is one of known techniques which can be used for user authentication.  ...  record (facial metrics).  ...  Sawarkar [11],in their work deal with the different deep learning or machine learning techniques requires or useful in face recognition.  ... 
doi:10.32628/cseit206243 fatcat:dr22xqngerasxerir5wwqenmbq

Proxemic Feature Recognition for Interactive Robots: Automating Metrics from the Social Sciences [chapter]

Ross Mead, Amin Atrash, Maja J. Matarić
2011 Lecture Notes in Computer Science  
We demonstrate the feasibility of autonomous realtime annotation of these spatial features during multi-person social encounters.  ...  In this work, we discuss a set of metrics for analyzing human spatial behavior (proxemics) motivated by work in the social sciences.  ...  Contemporary machine learning techniques have been applied to socially-appropriate person-aware navigation in dynamic crowded environments [29] and recognition of positive and negative attitudes of children  ... 
doi:10.1007/978-3-642-25504-5_6 fatcat:5fbfo443nbbzdbvl3fzusyogoa

Tutorial on Deep Learning for Human Activity Recognition [article]

Marius Bock, Alexander Hoelzemann, Michael Moeller, Kristof Van Laerhoven
2021 arXiv   pre-print
The tutorial, after a short introduction in the research field of activity recognition, provides a hands-on and interactive walk-through of the most important steps in the data pipeline for the deep learning  ...  All presentation slides shown during the tutorial, which also contain links to all code exercises, as well as the link of the GitHub page of the tutorial can be found on:  ...  [2] , did not yet include deep learning techniques and was solely based on classical Machine Learning approaches.  ... 
arXiv:2110.06663v1 fatcat:oxrfi6bn7bfupmeqnbrnbdjkym

Machine learning for big visual analysis

Jun Yu, Xue Mei, Fatih Porikli, Jason Corso
2018 Machine Vision and Applications  
Many machine learning techniques have already been applied to address the relevant problems.  ...  The article entitled "Person Re-identification by Discriminant Analytical Least Squares Metric Learning" proposed a new metric learning method based on least squares for person re-identification.  ... 
doi:10.1007/s00138-018-0948-5 fatcat:puwirktcpjg5bdfc4wxvuw77ua

Detection of Sweetness Level for Fruits (Watermelon) With Machine Learning

Wan Nurul Suraya Wan Nazulan, Ani Liza Asnawi, Huda Adibah Mohd Ramli, A.Z. Jusoh, S. Noorjannah Ibrahim, N.F.M. Azmin
2020 2020 IEEE Conference on Big Data and Analytics (ICBDA)  
The objective of this work is to investigate the sweetness parameter for the fruit 's detection and classification algorithm in machine learnings. This study  ...  Export  Download  Print  E-mail  Save to PDF ⋆ Add to List ▻ Set citation alert ▻ Date grading using machine learning techniques on a novel dataset Raissouli, H. Aljabri, A.A. Aljudaibi, S.M.  ...  applies image processing techniques to detect the color and shape of watermelon's skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon  ... 
doi:10.1109/icbda50157.2020.9289712 fatcat:d4wh5onngrdjjokp576phnzahi

Data Mining and Machine Learning for Software Engineering [chapter]

Elife Ozturk Kiyak
2020 Data Mining - Methods, Applications and Systems [Working Title]  
This study shows the open issues and presents related solutions and recommendations in software engineering, applying data mining and machine learning techniques.  ...  Various data mining and machine learning studies have been conducted to deal with software engineering tasks such as defect prediction, effort estimation, etc.  ...  Design pattern recognition LRNN, DT - Abstract factory, Source code Dataset with 67 OO metrics, 5-fold CV, ACC, using ML algorithms. adapter patterns extracted by JBuilder tool PR, recall, F-score ACC  ... 
doi:10.5772/intechopen.91448 fatcat:t4sqbohfdzhrdnj643sbkasiqq

A Review of Methods and Techniques used to perform investigation cases of Source Code Forensics

Pramatma Vishwakarma, Akarshan Suryal, Priyanka Maurya, N. Jyotishmaan Sahu, Darla Vijaya Mani Datta
2021 International Journal of Computer Applications Technology and Research  
When the evidence in contention is a source code with its origin and authorship in question, such evidence comes under the sub-branch of Source Code or Software Forensics.  ...  This paper is a review of this discipline and talks about various tools and techniques that may be employed to process a case in this sub-branch.  ...  Also, different methods help to identify authorship by source code analysis those methods are based on statistical and machine learning techniques.  ... 
doi:10.7753/ijcatr1004.1004 fatcat:jxvnq6cxszh4tomzjyptazhyka

Deep Transfer Learning for Cross-domain Activity Recognition [article]

Jindong Wang, Vincent W. Zheng, Yiqiang Chen, Meiyu Huang
2018 arXiv   pre-print
Experiments on three public activity recognition datasets demonstrate that: 1) The USSAR algorithm is effective in selecting the best source domains. 2) The TNNAR method can reach high accuracy when performing  ...  To solve this problem, transfer learning leverages the labeled samples from the source domain to annotate the target domain which has few or none labels.  ...  Conventional machine learning approaches have made tremendous progress on HAR by adopting machine learning algorithms such as similarity-based approach [9, 48] , active learning [19] , crowdsourcing  ... 
arXiv:1807.07963v2 fatcat:s2gmkcwkybfqtc5da32zkzgss4
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