Jorge Camargo

• PhD in Systems and Computing Engineering
• Professor at Universidad Nacional de Colombia, Bogotá, Colombia

In many countries, real estate appraisal is based on conventional methods that rely on appraisers’ abilities to collect data, interpret it and model the price of a real estate property. With the increasing use of real estate online platforms and the large amount of information found therein, there exists the possibility of overcoming many drawbacks...

We want to measure the impact of the curriculum learning technique on a reinforcement training setup, several experiments were designed with different training curriculums adapted for the video game chosen as a case study. Then all were executed on a selected game simulation platform, using two reinforcement learning algorithms, and using the mean...

https://www.journal.iberamia.org/index.php/intartif/article/view/532 https://github.com/rsaenzi/master-thesis

https://www.journal.iberamia.org/index.php/intartif/article/view/532 https://github.com/rsaenzi/master-thesis

The increasing use of online hospitality platforms provides firsthand information about clients preferences, which are essential to improve hotel services and increase the quality of service perception. Customer reviews can be used to automatically extract the most relevant aspects of the quality of service for hospitality clientele. This paper pro...

The increasing use of online hospitality platforms provides firsthand information about clients preferences, which are essential to improve hotel services and increase the quality of service perception. Customer reviews can be used to automatically extract the most relevant aspects of the quality of service for hospitality clientele. This paper pro...

In many countries, real estate appraisal is based on conventional methods that rely on appraisers' abilities to collect data, interpret it and model the price of a real estate property. With the increasing use of real estate online platforms and the large amount of information found therein, there exists the possibility of overcoming many drawbacks...

A formal statistical framework is proposed for synthesis of text information into sentiment indicators. Each text document is treated as an exchangeable collection of stems of words (tokens), and used in conjunction with a multinomial inverse regression approach to efficiently synthesize the information content in text documents. The proposed metho...

Social media is a valuable source of information that allows to study people opinions of many events that happen every day. Nowadays social networks are one of the most important communication methods that people use. Feelings towards nations can be measured today thanks to the advances in machine learning and big data. In this paper we present a m...

Students’ perception of classes measured through their opinions on teaching surveys allows to identify deficiencies and problems, both in the environment and in the learning methodologies. The purpose of this paper is to study, through sentiment analysis using natural language processing (NLP) and machine learning (ML) techniques, those opinions in...

Ocular diseases are one of the main causes of irreversible disability in people in productive age. In 2020, approximately 18% of the worldwide population was estimated to suffer of diabetic retinopathy and diabetic macular edema, but, unfortunately, only half of these people were correctly diagnosed. On the other hand, in Colombia, the diabetic pop...

En este documento se plantea el diseño de un videojuego, como herramienta alternativa de aprendizaje de las metodologías para realizar diseños de iluminación. El videojuego se ha diseñado bajo la plataforma Unity y consta de cinco niveles. Los tres primeros están basados en las metodologías de diseño de iluminación interior, el cuarto hace referenc...

Students' perception of classes measured through their opinions on teaching surveys allows to identify deficiencies and problems, both in the environment and in the learning methodologies. The purpose of this paper is to study, through sentiment analysis using natural language processing (NLP) and machine learning (ML) techniques, those opinions in...

We want to measure the impact of the curriculum learning technique on a reinforcement training setup, several experiments were designed with different training curriculums adapted for the video game chosen as a case study. Then all were executed on a selected game simulation platform, using two reinforcement learning algorithms, and using the mean...

https://repositorio.unal.edu.co/handle/unal/78592 https://github.com/rsaenzi/master-thesis

https://repositorio.unal.edu.co/handle/unal/78592 https://github.com/rsaenzi/master-thesis

https://repositorio.unal.edu.co/handle/unal/78592 https://github.com/rsaenzi/master-thesis

Este documento presenta la implementación de un software de reconocimiento de lenguaje de señas colombiano para personas sordas. Para este propósito, el Aprendizaje de Máquina será usado como base del sistema específico. Hoy en día no existe un repositorio público de imágenes o video que contenga estas señas ni la información necesaria para alcanza...

This article proposes the use of computationally efficient inverse regression Bayesian method for analysis of tweet propagation of political messages. Our example focuses on the Colombian case, though our method can be used in any election where social media messaging has a direct impact on political outcomes. We find strong evidence that politicia...

Cultural and social dynamics are important concepts that must be understood in order to grasp what a community cares about. To that end, an excellent source of information on what occurs in a community is the news, especially in recent years, when mass media giants use social networks to communicate and interact with their audience. In this work, w...

This paper presents a model that uses the information that sellers publish in real estate market websites to predict whether a property has higher or lower price than the average price of its similar properties. The model learns the correlation between price and information (text descriptions and features) of real estate properties through automati...

Colombia has a diversity of genres in traditional music, which allows to express the richness of the Colombian culture according to the region. This musical diversity is the result of a mixture of African, native Indigenous, and European influences. Organizing large collections of songs is a time consuming task that requires that a human listens to...

Colombia has a diversity of genres in traditional music, which allows to express the richness of the Colombian culture according to the region. This musical diversity is the result of a mixture of African, native Indigenous, and European influences. Organizing large collections of songs is a time consuming task that requires that a human listens to...

We propose a method to discover latent topics and visualise large collections of tweets for easy identification and interpretation of topics, and exemplify its use with tweets from a Colombian mass media giant in the period 2014--2019. The latent topic analysis is performed in two ways: with the training of a Latent Dirichlet Allocation model, and...

The number of machine learning (ML) applications on networking security has increased recently thanks to the availability of processing and storage capabilities. Combined with new technologies such as Software Defined Networking (SDN) and Network Function Virtualization (NFV), it becomes an even more interesting topic for the research community. In...

This document presents the mobile application EVANI, as a solution to support communities, which allows them in their territories, the identification of cases of malnutrition in children under 60 months of age, as well as the report of the coordinates of the case and the generation of alerts against the risk of mortality derived from this cause. On...

With the increasing use of the Internet and mobile devices, social networks are becoming the most used media to communicate citizens' ideas and thoughts. This information is very useful to identify communities with common ideas based on what they publish in the network. This paper presents a method to automatically detect city communities based on...

Safety perception measurement has been a subject of interest in many cities of the world. This is due to its social relevance, and to its effect on some local economic activities. Even though people safety perception is a subjective topic, sometimes it is possible to find out common patterns given a restricted geographical and sociocultural context...

Safety perception measurement has been a subject of interest in many cities of the world. This is due to its social relevance, and to its effect on some local economic activities. Even though people safety perception is a subjective topic, sometimes it is possible to find out common patterns given a restricted geographical and sociocultural context...

This study analyzes the abstracts and titles of 33,454 business finance, economics, management, and business articles published in ISI (frequently cited) journals during 2013–14. The sample represents 46.4 percent of all papers published in ISI journals in those years, and 52.7 percent of the articles published in the selected categories. The journ...

This paper presents a web system named TBDiagnostic for data acquisition, analysis and diagnosis of pulmonary tuberculosis. With the help of an artificial intelligence model, which generates a prediction of the diagnosis of tuberculosis, the system allows the user to generate a fast and accurate diagnosis of a person with symptoms of tuberculosis....

With the purpose of classifying text based on its sentiment polarity (positive or negative), we proposed an extension of a 68,000 tweets corpus through the inclusion of word definitions from a dictionary of the Real Academia Espa\~{n}ola de la Lengua (RAE). A set of 28,000 combinations of 6 Word2Vec and support vector machine parameters were consid...

Stack Overflow (SO) is an important source of knowledge for developers. It provides authoritative advice as well as detailed technical information about different computer science and software engineering topics. The goal of this paper is to explore mechanisms to extract implicit knowledge, which is present in questions of SO. In particular, we wan...

Text representation has been broadly studied in information retrieval and natural language processing. The process of building a good representation is an aspect to consider because it captures the most important aspects of the text in order to support other tasks such as classification, sentiment analysis, and automatic translation. The most commo...

This paper presents a methodology to represent, process and visualize large bird audio recordings. The proposed methodology is based on audio signal processing, image processing, and machine learning techniques. We evaluated the methodology in a collection of 6,856 audio recordings belonging to 560 Colombian bird species. Results show that it is po...

Propagation of political ideologies in social networks has shown a notorious impact on voting behavior. Both the contents of the messages (the ideology) and the politicians' influence on their online audiences (their followers) have been associated with such an impact. Here we evaluate which of these factors exerted a major role in deciding elector...

The paper presents an interactive tool for analysis of a set of source code submissions made by students when solving a programming assignment. The goal of the tool is to give a concise but informative overview of the different solutions submitted by the students, identifying groups of similar solutions and visualizing their relationships in a grap...

Ad hoc networks are spontaneous associations of wireless nodes that can operate without a previously built infrastructure. IEEE 802.11-based ad hoc networks, particularly, are the most common type of ad hoc networks since they can be deployed with ordinary devices such as laptops, tablets or smartphones. An application of ad hoc networks that is fr...

Personality traits influence most, if not all, of the human activities, from those as natural as the way people walk, talk, dress and write to those most complex as the way they interact with others. Most importantly, personality influences the way people make decisions including, in the case of developers, the criteria they consider when selecting...

This paper presents a multimodal latent topic analysis method for the construction of image collection summaries. The method automatically selects a set of prototypical images from a large set of retrieved images for a given query. We define an image collection summary as a subset of images from a collection, which is visually and semantically repr...

Smartphones have opened a new world of opportunities in the context of health care. Particularly, they can be used in behavioral monitoring scenarios. This paper presents a system based on mobile and cloud computing technologies for managing multimodal and unstructured data in an ubiquitous and pervasive platform. The proposed system allows parents...

As the number of elderly people increase in the world age-related diseases are arising public health problems. Particularly, dementia is one of the most challenging diseases that affect not only to patient but also relatives and specially caregivers. Non-pharmacological therapies have shown to be useful to improve life quality of patients and careg...

The Electrocardiogram (ECG) can provide valuable information for medical diagnosis and diseases prevention. This paper presents an algorithm for arrhythmia classification based on frequency domain analysis of ECG biosignals. Our approach includes the use of Support Vector Machines (SVM) to identify seven different types of beats and four types of a...

Objectives: The aim of this paper is to analyze a set of cryptographic algorithms to protect medical records in the context of mobile applications. Methods: We analyzed the use of cryptography in a data set of medical health records taking into account the use of computing memory, processing and time in each studied algorithm. A system prototype wa...

People with some kind of disabilities like blind people, people using a wheelchair and alzheimer patients, lose their independence. Caregivers of people who suffer from occasional memory loss, disorientation or movement problems are afraid of leave them go out alone. The m-Health field has emerged to support health services and information improvin...

Advances in mobile devices and the promise of pervasive/ubiquitous computing have given rise to a vast range of new applications for health care and patient's monitoring. These technologies support the daily life control in patients with some kind disability. This paper presents a pervasive and ubiquitous mobile application for supporting nonpharma...

The increase of child mental disorders in recent years and their increasing impact has generated an alert in mental health. This warning is presented not only at child level but also in the general population. Currently, psychologists use the cognitive-behavioral therapy (CBT) that needs a manual observation process, which generates a large amount...

Electronic medical records are a very important asset that must be secured in such a way that only patients and authorized personal can access them. The HL7 (Health Level 7) is a set of standards to transfer clinical and administrative data among hospital information systems. One of the main concerns of interchanging medical information is related...

Image collection visualization is an important component of exploration-based image retrieval systems. In this paper we address the problem of generating an image collection visualization in which images and text can be projected together. Given a collection of images with attached text annotations, our aim is to find a common representation for bo...

This paper presents two different strategies for visualizing multimodal image collections, which are based on a representation strategy that fuses text and visual content in the same latent space. This latent space allows to find semantic groups of images, which are used to select image prototypes to build a semantic visualization. The first strate...

This paper presents a new method to automatically select a set of representative images from a larger set of retrieved images for a given query. We define an image collection summary as a subset of images from the collection, which are visually and semantically representative. To build such a summary we propose MICS, a method that fuses two modalit...

While search engines have been a successful tool to search text information, image search systems still face challenges. The keyword-based query paradigm used to search in image collection systems, which has been successful in text retrieval, may not be useful in scenarios where the user does not have the precise way to express a visual query. Imag...

This paper presents BIGS the Big Image Data Analysis Toolkit, a software framework for large scale image processing and analysis over heterogeneous computing resources, such as those available in clouds, grids, computer clusters or throughout scattered computer resources (desktops, labs) in an opportunistic manner. Through BIGS, eScience for image...

This paper describes the participation of the Bioingenium research group of Universidad Nacional de Colombia in the ImageCLEF2012 Medical Retrieval challenge, specifically in the ad-hoc image-based retrieval task. The methods used for solving textual and visual queries with which we submitted uni-modal runs are described. They were ranked 1st and 3...

The huge amount of biomedical images that are produced every day require of suitable methods to access them in an efficient and effective way. Although there has been an important development in methods to search large information repositories, these methods have been mainly focused on text data, and less work has been devoted to non-text data such...

Histology images are an important resource for research, education and medical practice. The availability of image collections with reference purposes is limited to printed formats such as books and specialized journals. When histology image sets are published in digital formats, they are composed of some tens of images that do not represent the wi...

In this paper we address the problem of generating an image collection visualization in which images and text can be projected together. Given a collection of images with attached text annotations, we aim to find a common representation for both information sources to model latent correlations among the collection. Using the proposed latent represe...

This paper proposes a strategy to interactively explore large collections of images. The strategy is based on kernel methods, which offer a mathematically strong framework to address each stage of an exploratory image collection system: image representation, similarity function calculation, summarization, visualization and exploration. This work al...

Medical images are a very important resource for the clinical practice and operation. Thousands of them are daily acquired in hospitals to diagnose the health state of patients. However, once they have been archived as part of a large image database, it is very difficult to retrieve the same image again since it requires remembering dates or names....

This paper proposes a method for involving domain knowledge in the construction of summaries of large collections of images. This is accomplished by using a multi-class kernel alignment strategy in order to learn a kernel function that incorporates domain knowledge (class labels). The kernel function is the basis of a clustering algorithm that gene...

This paper attempts to provide a comprehensive state-of-the-art of the recent technical achievements in visual-ization of large collections of images. Major recent publications are included in this survey covering different aspects of the research in this area, including visualization, summarization and exploration. In addition, some other related...

This paper presents a strategy for involving domain knowl-edge in the visualization of large collections of medical images. The strat-egy is based on the use of a kernel alignment approximation in order to incorporate medical domain knowledge in the similarity function com-putation. Experimental results show that visualization is improved with resp...

In this paper is showed a content based information retrieval system over a peer to peer network. It was developed a prototype which permitted make experimental tests to evaluate the system efficiency in terms of response time and messages quantity generated in the network when is executed a query. It was possible conclude that it is viable to deve...

In this paper, we propose a machine learning frame-work for summarizing and visualizing large collections of medical images. Because it is not possible to visualize all images of the collection it is necessary to visualize an overview that represents the complete collection. A kernel that involves domain knowledge is used in the visualization and s...

In this paper, we propose a kernel-based framework for summarizing and visualizing large collections of medical images. Due it is not possible to visualize all images of the collection it is necesary to visualize a overview that represent the complete collecton. A kernel that involves domain knowledge is used to improve the visualization and summar...

This paper presents a system for visualization of large col- lection of medical images. The main goal of the system is to automatically generate a 2D representation by a projection that preserves the semantic similarity of the images, i.e, sim- ilar images must be projected to neighbor positions in the visualization. This kind of visualization help...