Gordana Ispirova

Jožef Stefan Institute | IJS · Department of Computer systems

A key component of automated algorithm selection and configuration, which in most cases are performed using supervised machine learning (ML) methods is a good-performing predictive model. The predictive model uses the feature representation of a set of problem instances as input data and predicts the algorithm performance achieved on them. Common m...

Although recipe data are very easy to come by nowadays, it is really hard to find a complete recipe dataset - with a list of ingredients, nutrient values per ingredient, and per recipe, allergens, etc. Recipe datasets are usually collected from social media websites where users post and publish recipes. Usually written with little to no structure,...

In the last decades, a great amount of work has been done in predictive modeling of issues related to human and environmental health. Resolution of issues related to healthcare is made possible by the existence of several biomedical vocabularies and standards, which play a crucial role in understanding the health information, together with a large...

Human knowledge about food and nutrition has evolved drastically with time. With food and nutrition-related data being mass produced and easily accessible, the next step is to use Artificial Intelligence (AI) to translate data into knowledge. The majority of AI research is model-driven, and classical Machine Learning (ML) pipelines concentrate on t...

Besides the numerous studies in the last decade involving food and nutrition data, this domain remains low resourced. Annotated corpuses are very useful tools for researchers and experts of the domain in question, as well as for data scientists for analysis. In this paper, we present the annotation process of food consumption data (recipes) with se...

In this paper, we have proposed a new pipeline for landscape analysis of time-series machine learning datasets that enables us to better understand a benchmarking problem landscape, allows us to select a diverse benchmark datasets portfolio, and reduces the presence of performance assessment bias via bootstrapping evaluation. Combining a large mult...

Being both a poison and a cure for many lifestyle and non-communicable diseases, food is inscribing itself into the prime focus of precise medicine. The monitoring of few groups of nutrients is crucial for some patients, and methods for easing their calculations are emerging. Our proposed machine learning pipeline deals with nutrient prediction bas...

BACKGROUND Being both a poison and a cure for many lifestyle and non-communicable diseases, food is inscribing itself into the prime focus of precise medicine, therefore knowing what is in our food has become utmost important. The monitoring of few groups of nutrients has become crucial for some patients, and with that methods for easing their calc...

Food is one of the main health and environmental factors in today’s society. With modernization the food supply is expanding and food-related data is increasing. This type of data comes in many different forms and making it inter-operable is one of the main requirements for using in any kind of analyses. One step towards this goal is data normaliza...

Food is one of the main health and environmental factors in today's society. With modernization the food supply is expanding and food-related data is increasing. This type of data comes in many different forms and making it inter-operable is one of the main requirements for using in any kind of analyses. One step towards this goal is data normaliza...

Human understanding and knowledge about food and nutrition is constantly evolving, and has significantly improved recently, one of the main contributor to this is data. The possibilities of gaining knowledge from food and nutrition-related data are yet to be explored. One of the most important information about food is nutrient content, which is ve...

Assessing nutritional content is very relevant for patients suffering from various diseases, professional athletes, and for health reasons is becoming part of everyday life for many. However, it is a very challenging task as it requires complete and reliable sources. We introduce a machine learning pipeline for predicting macronutrient values of fo...

Missing data are a common problem in most research fields and introduce an element of ambiguity into data analysis. They can arise due to different reasons: mishandling of samples, measurement error, deleted aberrant value or simply lack of analysis. The nutrition domain is no exception to the problem of missing data. This paper addresses the probl...

This paper addresses the problem of missing data in food composition databases (FCDBs). The missing data can be either for selected foods or for specific components only. Most often, the problem is solved by human experts subjectively borrowing data from other FCDBs, for data estimation or imputation. Such an approach is not only time-consuming but...

To link and harmonize different knowledge repositories with respect to isotopic data, we propose an ISO-FOOD ontology as a domain ontology for describing isotopic data within Food Science. The ISO-FOOD ontology consists of metadata and provenance data that needs to be stored together with data elements in order to describe isotopic measurements wit...

Unhealthy diet can lead to diseases such as diabetes, allergies, and some types of cancer, among other health-related problems. In order to help users and clinical dietitians access the relevant knowledge about food and nutrition data in e-health systems that use different data sources, ontologies about food and related domains, such as clinical me...

In an EU-funded project RICHFIELDS, a data platform was designed with the aim to collect, link and harmonize , analyze, store, and deliver food-and nutrition-related data and information to various stakeholders. To integrate heterogenous food data sets, we propose a RICHFIELDS framework for semantic interoperability of food information, which is a...

Food composition data (FCD) are detailed sets of information on the nutritional components of foods, provide values for energy and nutrients, food classifiers and descriptors and are presented in Food Composition Databases (FCDBs). The data contained in currently available FCDBs is of differing quality which depends on the data source. Analytical d...

Obesity is a growing problem in most developed countries and it is responsible for a significant degree of morbidity and mortality. Overweight and obesity are linked to more deaths worldwide than underweight, and globally there are more people who are obese than underweight. This paper focuses on working with medical and health-related data concern...

Judging computational creativity is not a simple task. In order to assess if something behaved creatively first we need a formal and precise definition of the meaning of creativity in the certain area. The next thing would be formalized criteria whose application rates the level of creativity. In the area of computer creativity there is not a lot o...

Data extraction: Data from several national FCDBs of several countries (collected by EuroFIR). Order of data extraction: i) make sure the data is analytical; ii) select food group and foods that belong to that food group; iii) select a nutrient; iv) select a list of countries. Methodology: For a dataset of n instances (foods), we build n-1 models f...

Food composition data are detailed sets of information on food components, providing values for energy and nutrients, food classifiers and descriptors. The data of this kind is presented in food composition databases, which are a powerful source of knowledge. Food composition databases may differ in their structure between countries, which makes it...

In this paper, we present results of the evaluation of a semi-automatic system for classifying and describing foods according to FoodEx2 using datasets from three European countries. The proposed system is an integration of methods from machine learning, natural language processing and probability theory. It obtained an accuracy of 91% for the clas...

Obesity is a growing problem in most developed countries and it is responsible for a significant degree of morbidity and mortality. Overweight and obesity are linked to more deaths worldwide than underweight, and globally there are more people who are obese than underweight. Prevention is better than cure and easier. However, there are many ways to...