Carlos A. Iglesias

Universidad Politécnica de Madrid | UPM · Departamento de Ingeniería de Sistemas Telemáticos

Background: Frailty in older people is a syndrome related to aging that is becoming increasingly common and problematic as the average age of the world population increases. Detecting frailty in its early stages or, even better, predicting its appearance can greatly benefit health in later years of life and save the healthcare system from high cos...

Whether consciously or inadvertently, our messages can include toxic language which contributes to the polarization of social networks. Intelligent techniques can help us detect these expressions and even change them into kinder expressions by applying style transfer techniques. This work aims to advance detoxification style transfer techniques usi...

Green areas play an important role in people’s well-being in urban areas. However, traditional survey methods hinder understanding their actual impact. Fortunately, social networking analysis provides valuable information that city planners can use to transform cities and improve city life. This research studies geolocated tweets published in parks...

Understanding radicalization pathways, drivers, and factors is essential for the effective design of prevention and counter-radicalization programs. Traditionally, the primary methods used by social scientists to detect these drivers and factors include literature reviews, qualitative interviews, focus groups, and quantitative methods based on surv...

GSITK is a framework to perform a wide variety of sentiment analysis tasks, including dataset acquisition, text preprocessing, model design, and performance evaluation. The framework is oriented to both researchers and practitioners, easing the replication of previous sentiment models, as well as offering implementations of common tasks. This is ac...

The analysis of the content of posts written on social media has established an important line of research in recent years. The study of these texts, as well as their relationship with each other and their dependence on the platform on which they are written, enables the behavior analysis of users and their opinions with respect to different domain...

The dramatic growth of the Web has motivated researchers to extract knowledge from enormous repositories and to exploit the knowledge in myriad applications. In this study, we focus on natural language processing (NLP) and, more concretely, the emerging field of affective computing to explore the automation of understanding human emotions from text...

Nowadays, we are witnessing a shift in the way emergencies are being managed. On the one hand, the availability of big data and the evolution of geographical information systems make it possible to manage and process large quantities of information that can hugely improve the decision-making process. On the other hand, digital humanitarianism has s...

Museums play a crucial role in preserving cultural heritage. However, the forms in which they display cultural heritage might not be the most effective at piquing visitors’ interest. Therefore, museums tend to integrate different technologies that aim to create engaging and memorable experiences. In this context, the emerging Internet of Things (Io...

Intelligent Environments (IEs) aims to empower users by enriching their experience, raising their awareness and enhancing their management of their surroundings. The term IE is used to describe the physical spaces where ICT and pervasive technologies are used to achieve specific objectives for the user and/or the environment. The growing IE communi...

Bike-Sharing Systems (BSSs) have been implemented in numerous cities around the world to reduce the traffic generated by motorized vehicles, due to the benefits they bring to the city, such as reducing congestion or decreasing pollution generation. Caused by their impact on urban mobility, the research community has increased their interest in thei...

Bike-sharing systems (BSS) have been implemented in numerous cities around the world to reduce the traffic generated by motorized vehicles, due to the benefits they bring to the city, such as reducing congestion or decreasing pollution generation. Caused by their impact on urban mobility, the research community has increased their interest in their...

Recent works have shown that sentiment analysis on social media can be improved by fusing text with social context information. Social context is information such as relationships between users and interactions of users with content. Although existing works have already exploited the networked structure of social context by using graphical models o...

The Internet has become an important tool for modern terrorist groups as a means of spreading their propaganda messages and recruitment purposes. Previous studies have shown that the analysis of social signs can help in the analysis, detection, and prediction of radical users. In this work, we focus on the analysis of affect signs in social media a...

The application of natural language to improve students’ interaction with information systems is demonstrated to be beneficial. In particular, advances in cognitive computing enable a new way of interaction that accelerates insight from existing information sources, thereby contributing to the process of learning. This work aims at researching the...

Senpy is a framework to develop, evaluate and publish web services for sentiment and emotion analysis in text. The framework is aimed towards both developers and users. For developers, it is a means to evaluate their classifiers and easily publish them as web services. For users, it is a way to consume sentiment analysis from different providers th...

Fault Management is a vital issue for any network operator since the beginning of the telecommunications era. As networks have become more and more complex, their management systems are crucial for any operator company. In this ecosystem, the Software‐Defined Networking (SDN) approach has appeared as a possible solution for different networking iss...

Traditionally, fault diagnosis in telecommunication network management is carried out by humans who use software support systems. The phenomenal growth in telecommunication networks has nonetheless triggered the interest in more autonomous approaches, capable of coping with emergent challenges such as the need to diagnose faults’ root causes under...

This work presents an agent-based model of radicalization growth based on social theories. The model aims at improving the understanding of the influence of social links on radicalism spread. The model consists of two main entities, a Network Model and an Agent Model. The Network Model updates the agent relationships based on proximity and homophil...

Sentiment analysis in social media is harder than in other types of text due to limitations such as abbreviations, jargon, and references to existing content or concepts. Nevertheless, social media provides more information beyond text, such as linked media, user reactions, and relations between users. We refer to this information as social context...

The impact of online reviews on businesses has grown significantly during last years, being crucial to determine business success in a wide array of sectors, ranging from restaurants, hotels to e-commerce. Unfortunately, some users use unethical means to improve their online reputation by writing fake reviews of their businesses or competitors. Pre...

Unfortunately, news regarding tragedies involving crowd evacuations are becoming more and more common. Understanding disasters and crowd emergency evacuation behaviour is essential to define effective evacuation protocols. This paper proposes an agent-based model of egress behaviour consisting of three complementary models: (i) model of people movi...

Lexical resources are widely popular in the field of Sentiment Analysis, as they represent a resource that directly encodes sentimental knowledge. Usually sentiment lexica are used for polarity estimation through the matching of words contained in a text and their associated lexicon sentiment polarities. Nevertheless, such resources have limitation...

Social media generates a massive amount of data at a very fast pace. Objective information such as news, and subjective content such as opinions and emotions are intertwined and readily available. This data is very appealing from both a research and a commercial point of view, for applications such as public polling or marketing purposes. A complet...

Deep learning techniques for Sentiment Analysis have become very popular. They provide automatic feature extraction and both richer representation capabilities and better performance than traditional feature based techniques (i.e., surface methods). Traditional surface approaches are based on complex manually extracted features, and this extraction...

The evolution of the Internet of Things leads to new opportunities for the contemporary notion of smart offices, where employees can benefit from automation to maximize their productivity and performance. However, although extensive research has been dedicated to analyze the impact of workers’ emotions on their job performance, there is still a lac...

With the increasing popularity of large scale Knowledge Graph (KG)s, many applications such as semantic analysis, search and question answering need to link entity mentions in texts to entities in KGs. Because of the polysemy problem in natural language, entity disambiguation is thus a key problem in current research. Existing disambiguation method...

The application of natural language to improve the interaction of human users with information systems is a growing trend in the recent years. Advances in cognitive computing enable a new way of interaction that accelerates insight from existing information sources. In this paper, we propose a modular cognitive agent architecture for question answe...

Recently, there is an increasing tendency to embed the functionality of recognizing emotions from the user generated contents, to infer richer profile about the users or contents, that can be used for various automated systems such as call-center operations, recommendations, and assistive technologies. However, to date, adding this functionality wa...

Social networks have a great impact in our lives. While they started to improve and aid communication, nowadays they are used both in professional and personal spheres, and their popularity has made them attractive for developing a number of business models. Agent-based Social Simulation (ABSS) is one of the techniques that has been used for analys...

The application of Agent-based Social Simulation (ABSS) for modeling social networks requires specific facilities for modeling, simulation and visualization of network structures. Moreover, ABSS can benefit from interactive shell facilities that can assist the model development process. We have addressed these problems through the development of a...

Sematch is an integrated framework for the development, evaluation and application of semantic similarity for Knowledge Graphs. The framework provides a number of similarity tools and datasets, and allow users to compute semantic similarity scores of concepts, words, and entities, as well as to interact with Knowledge Graphs through SPARQL queries....

The growing popularity of public APIs and technologies such as web hooks is changing online services drastically. It is easier now than ever to interconnect services and access them as a third party. The next logical step is to use intelligent agents to provide a better user experience across services, connecting services with smart automatic behav...

Deep learning techniques for Sentiment Analysis have become very popular. They provide automatic feature extraction and both richer representation capabilities and better performance than traditional feature based techniques (i.e., surface methods). Traditional surface approaches are based on complex manually extracted features, and this extraction...

Language resource interoperability is still a major challenge in sentiment analysis. One of the current trends for solving this issue is the adoption of a linked data perspective for semantically modeling, interlinking, and publishing lexical and other linguistic resources. This chapter contributes to the development of the linguistic linked open d...

This paper presents a method for measuring the semantic similarity between concepts in Knowledge Graphs (KGs) such as WordNet and DBpedia. Previous work on semantic similarity methods have focused on either the structure of the semantic network between concepts (e.g. path length and depth), or only on the Information Content (IC) of concepts. We pr...

Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation co...

A number of marketing phenomena are too complex for conventional analytical or empirical approaches. This makes marketing a costly process of trial and error: proposing, imagining, trying in the real world, and seeing results. Alternatively, Agent-based Social Simulation (ABSS) is becoming the most popular approach to model and study these phenomen...

The Live Web is characterised by a new way of interacting with the Web through dynamic streams of relevant real-time contextual information to users. These sources of massive data usually overwhelm them, because they are not able to consume that amount of data. Task Automation Services (TASs) are platforms or apps that allow their users to author a...

Viral marketing, marketing techniques that use pre-existing social networks, has experienced a significant encouragement in the last years. In this scope, Twitter is the most studied social network in viral marketing and the rumor spread is a widely researched problem. This paper contributes with a survey of research works which study rumor diffusi...

There exists a growing trend in using NLIs (Natural Language Interfaces) that ranges from research to commercial products. Conversational agents beneath these interfaces have become more sophisticated, being able to either perform a task in behalf of the user or give a precise response to a question as Question Answering systems do. When combining...

The ability to build arguments that express thoughts is crucial for intelligent interactions among human beings. Thus, argumentation techniques have been applied for years in fields, such as rhetoric or artificial intelligence. More specifically, the agents paradigm fits into the use of these types of techniques because agents shape a society in wh...

Fault Diagnosis is an essential management task for any telecommunication network and it is even more crucial for Wireless Sensor Networks due to their dynamic nature. Based on Agent Technology, this paper presents an architecture that combines different network and diagnosis models to carry out a Fault Diagnosis process: a Causal Model to relate f...

Viral marketing, marketing techniques that use pre-existing social networks, has experienced a significant encouragement in the last years. In this scope, Twitter is the most studied social network in viral marketing and the rumor spread is a widely researched problem. This paper contributes with a (1) novel agent-based social simulation model for...

Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition...

A simple model of mashup technology for combining services and connected devices is now becoming popular. This model is frequently referred to as task automation based on Event-Condition-Action (ECA) rules. The most popular online services that follow this approach are Ifttt and Zapier. In addition, this model is being followed by several mobile fr...

There are a great number of situations in Ambient Intelligence systems which involve users trying to access shared resources such as: music, TVs, decoration, gym machines, air conditioning, etcetera. The use of Social Choice theory can be employed in these situations to reach consensus while the social welfare is maximized. This paper proposes a mu...

The primary hypothesis stated by this paper is that the use of social choice theory in Ambient Intelligence systems can improve significantly users’ satisfaction when accessing shared resources. A research methodology based on agent based social simulations is employed to support this hypothesis and to evaluate these benefits. The result is a sixfo...

One of the challenges facing the current web is the efficient use of all the available information. The Web 2.0 phenomenon has favored the creation of contents by average users, and thus the amount of information that can be found for diverse topics has grown exponentially in the last years. Initiatives such as linked data are helping to build the...

We present a methodology for legacy language resource adaptation that generates domain-specific sentiment lexicons organized around domain entities described with lexical information and sentiment words described in the context of these entities. We explain the steps of the methodology and we give a working example of our initial results. The resul...

Sentiment analysis has recently gained popularity in the financial domain thanks to its capability to predict the stock market based on the wisdom of the crowds. Nevertheless, current sentiment indicators are still silos that cannot be combined to get better insight about the mood of different communities. In this article we propose a Linked Data a...

Sentiment and Emotion Analysis strongly depend on quality language resources, especially sentiment dictionaries. These resources are usually scattered, heterogeneous and limited to specific domains of application by simple algorithms. The EUROSENTIMENT project addresses these issues by 1) developing a common language resource representation model f...

Many different open information sources currently exist for protecting the environment in Europe, mainly focused on Natura 2000 network, and areas where environmental protection and activities like tourism need to be balanced. Managing these data and integrating them for supporting decision makers and for novel uses is a challenging task. The Smart...

This paper presents a testing methodology to apply Behaviour Driven Development (BDD) techniques while developing Multi-Agent Systems (MASs), termed BEhavioural Agent Simple Testing (BEAST) Methodology. This methodology is supported by the open source framework (BEAST Tool) which automatically generates test cases skeletons from BDD scenarios speci...

The Idea Management Systems are a tool for collecting ideas for innovation from large communities. One of the problems of those systems is the difficulty to accurately depict the distinctive features of ideas in a rapid manner and use them for judgement of proposed innovations. Our research aims to solve this problem by introducing annotation of id...

Information extraction out of web pages, commonly known as screen scraping, is usually performed through wrapper induction, a technique that is based on the internal structure of HTML documents. As such, the main limitation of these kinds of techniques is that a generated wrapper is only useful for the web page it was designed for. To overcome this...

Textual emotion analysis is a new field whose aim is to detect emotions in user generated content. It complements Sentiment Analysis in the characterization of users subjective opinions and feelings. Nevertheless, there is a lack of available lexical and semantic emotion resources that could foster the development of emotion analysis services. Some...

Given their increasing popularity and novel requirements and characteristics, telco mashups deserve an analysis that goes beyond what's available for mashups in general. Here, the authors cluster telco services into different types, analyze their features, derive a telco mashup reference architecture, and survey how well existing mashup tools can r...

Given that telecommunications networks are constantly growing in complexity and heterogeneity, management systems have to work with incomplete data, handle uncertain situations and deal with dynamic environments. in addition, the high competitiveness in the telecommunications market requires cost cutting and customer retention by providing reliable...

In this paper, we introduce B2DI model that extends BDI model to perform Bayesian inference under uncertainty. For scalability and flexibility purposes, Multiply Sectioned Bayesian Network (MSBN) technology has been selected and adapted to BDI agent reasoning. A belief update mechanism has been defined for agents, whose belief models are connected...

This article proposes a (MAS) architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypotheses generation and hypotheses confirmation. The first process is distributed among several agents based on a (MSBN), while the second one is carried out by agents using semantic reasoning. A diagnosis...

This work proposes an encapsulation scheme aimed at simplifying the reuse process of hardware cores. This hardware encapsulation approach has been conceived with a twofold objective. First, we look for the improvement of the reuse interface associated with the hardware core description. This is carried out in a first encapsulation level by improvin...

The following paper describes the design, architecture and use of a semantic search model in open innovation support systems. We explore the relationships between the user submitted content to improve interaction and simplify the current schemes of analysis of Idea Management System data. In order to accomplish this, we propose a model where users...

Idea Management Systems are an implementation of open innovation notion in the Web environment with the use of crowdsourcing techniques. In this area, one of the popular methods for coping with large amounts of data is duplicate detection. With our research, we answer a question if there is room to introduce more relationship types and in what degr...