Kasper Knoblauch Christensen has defended his PhD

Kasper Christensen presented his PhD at April 26th.

Title of the thesis is “Detecting ideas in online communities: Utilizing machine learning and text mining for finding ideas in online communities”. The given topic for the trial lecture was ” What is the future of Big Data in Food, Beverage and Personal Products? – A critical perspective.”

In his thesis, Kasper has explored the possibilities of automatic detection of ideas from online communities.by using text mining and machine learning. He also showed that PLS regression in combination with variable selection can be used to identify the words and phrases that define an idea. He used cases from Lego and beer brewing in his work.

Supervisors:

  • Professor Knut Kvaal, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway
  • Dr. Argic Einar Risvik, Senior Research Scientist, Department of Sensory, Consumer and Innovation, Nofima, Ås, Norway
  • Professor Tormod Næs, Senior Research Scientist, Nofima, Ås, Norway and Department of Food Science, Quality and Technology, Faculty of Life Sciences, University of Copenhagen, Copenhagen, Denmark
  • Dr. Torulf Mollestad, Principal consultant, Altran, Norway, Oslo

 

Evaluation committee:

  • Dr. Hal Macfie, Visiting Professor, Universities of Reading, Nottingham, United Kingdom
  • Professor Per B. Brockhoff, Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
  • Associate Professor, Jorge M. Marchetti, Faculty of Science and Technology, Norwegian University of Life Sciences, Ås, Norway

Dutch collaboration

Professor Age K. Smilde and Dr. Frans van der Kloet visited Nofima on December 19th-21st 2016. They are collaborating with us on papers realted to ASCA and data fusion.IMG_6528.JPG

From left: Age K. Smilde, Tormod Næs, Ingrid Måge, Frans van der Kloet and Kristian H. Liland (Picture taken by Reidun Lilleholt)

 

Visit at Radboud University

Ingrid Måge visited Dr. Jeroen Jansen and his group at Radboud University, Netherlands. Ingrid gave a presentation of Nofima’s work on multi-block data modelling, with special focus on the SO-PLS methodology. Several areas of collaboration were discussed, and we  look forward to working more with Jeroen and his group in the future.

Alessandra Biancolillo awarded PhD

Alessandra Biancolillo defended her PhD thesis at the University of Copenhagen on November 18th. Alessandra has been associated with Nofima’s  strategic program “Multiblock Methods for prediction and interpretation”, developing methodology for analyzing and interpreting several blocks of data sequentially (so-called SO-PLS). The thesis is titled “Method development in the area of multi-block analysis focused on food analysis”. Supervisors have been Tormod Næs (Nofima), Ingrid Måge (Nofima) and Rasmus Bro (University of Copenhagen).

Alessandra did a very good job at the defense. Opponents Thomas Skov (University of Copenhagen), El Mostafa Qannari (Oniris, Nantes) and Lars Nørgaard (Roskilde University) were well prepared and contributed to an interesting and fruitful discussion.

ale_opponents

 

 

Nofima at COST Meeting FoodMC

Kristian Hovde Liland and Ingrid Måge participated last week at the second meeting of the COST action FoodMC. The action is led by INRA, and the meeting took place in INRA’s premises in Versailles. The full title is “Mathematical and Computer Science Methods for Food Science and Industry”. The goal is to Support the food sector in facing futures challenges in production and processing, adopting modelling and optimization methods from Maths and Computer Science.

Ingrid leads the working group called “Modelling food products and food Processes.” This is the largest working group, with over 50 members (and growing). The group is composed of researchers with backgrounds from both mathematical and statistical modeling, two fields that traditionally have limited collaboration. The applications range from mathematical-physical modeling of wafer fracture, through quantification of insects in wheat flour using NIR spectroscopy, to decision support models used to select the appropriate packaging machine. It is an interesting and challenging job to coordinate such a diverse group of scientists, with a correspondingly large potential to expand our horizons and acquire new valuable contacts.

For more info about the COST action, see:

https://www6.inra.fr/foodmc

The infamous Måge plot

Some multiblock regression Methods (such as SO-PLS and PO-PLS) allow for different numbers of components in each block. There are two strategies for selecting the numbers of components for these models: sequential and global. With the sequential strategy, the number of components to use for the first block is determined before the second block is introduced, and so on. With the global strategy, all blocks are taken into account from the beginning. Models With all combinations of components from each block are tested, and the combination giving the minimum prediction error is selected. Often, several combinations have approximately equally good prediction ability, and in such cases it is important to also take the total number of components into account. The Måge plot is a valuable tool for evaluating the models and selecting the optimal numbers of components.

The Måge plot shows the prediction error for each combination of components, as a function of the total number of components. From this perspective, it is possible to decide the total dimensionality of the system and the individual dimensionalities of each block at the same time. It is also easy to identify models that are indistinguishable from a prediction point of view. In the figure below, it is obvious that the total complexity is three. The two most predictive components are found in the first block,  and the predictive ability is almost equal whether the third component is taken from the second or third block (combination “210” and “201” are almost equal).

Matlab code for making the plot can be found here: MagePlot

MågePlot

 

References:

Måge, I., Mevik, B. H., & Næs, T. (2008). Regression models with process variables and parallel blocks of raw material measurements. Journal of Chemometrics, 22(8), 443–456.

Næs, T., Tomic, O., Afseth, N. K., Segtnan, V., & Måge, I. (2013). Multi-block regression based on combinations of orthogonalisation, PLS-regression and canonical correlation analysis. Chemometrics and Intelligent Laboratory Systems, 124, 32–42.

Biancolillo, A., Måge, I., & Næs, T. (2015). Combining SO-PLS and linear discriminant analysis for multi-block classification. Chemometrics and Intelligent Laboratory Systems, 141, 58–67.

 

Nofima in COST action FoodMC

KrisIng

Kristian Liland and Ingrid Måge has joined the Management Committee of the COST Action “Mathematical and Computer Science Methods for Food Science and Industry” (FoodMC). The Action is chaired by Dr. Alberto Tonda at INRA (France), and Ingrid is leading the Working Group entitled “Modelling food products and food processes”.

Goal

Support the food sector in facing future challenges in production and processing, adopting modelling and optimization methods from Maths and Computer Science.

Background

The agriculture and food processing sector (agri-food) is facing sustainability challenges of growing complexity, from consumer expectations to concerns over food security, right through to environmental regulations. In such a context, innovation is becoming a decisive factor of competitiveness for companies in this field. Methodologies and tools from Maths and Computer Science (MCS) are emerging as key contributors to modernization and optimization of processes in various disciplines: the agri-food sector, however, is not a traditional domain of application for MCS, and at the moment there is no community organized around solving the issues of this field.

This COST Action brings together scientists and practitioners from MCS and agri-food domains, stimulating the emergence of new research, and structuring a new community to coordinate further investigation efforts. Exploiting approaches originating at different sub-fields of MCS, from applied mathematical models to knowledge engineering, this COST Action will cover two main topics: understanding and controlling agri-food processes; and eco-design of agri-food products.

Links

http://www6.inra.fr/foodmc/

http://www.cost.eu/COST_Actions/ca/CA15118