Univerza na Primorskem Fakulteta za matematiko, naravoslovje in informacijske tehnologije

četrtek, 12. september 2019 Tokrat dve predavanji: "Cognitive Load Inference for Ubiquitous Computing Adaptation" in "Determining sentiment of tweets using lexicon and (AnA)-affirmative and non-affirmative words"

V ponedeljek, 16. septembra 2019, se bosta v prostorih Fakultete za matematiko, naravoslovje in informacijske tehnologije Univerze na Primorskem (Glagoljaška 8, Koper) v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM zvrstili dve predavanji.


ČAS/PROSTOR: 16. september 2019 ob 16.00 v FAMNIT-VP2


Veljko Pejović is an assistant professor of computer science at the University of Ljubljana, Slovenia. His interests include mobile computing, HCI, resource-efficient computing, and the interaction of technology and society. His work on modelling user movement and communication behaviour from mobile call records won the 2013 Orange D4D Challenge, while his work on interruptibility modelling resulted in the best paper nomination at the ACM UbiComp'14 conference.

NASLOV: Cognitive Load Inference for Ubiquitous Computing Adaptation

From not disturbing a focused programmer, to entertaining a restless commuter waiting for a train, personal ubiquitous computing devices could greatly enhance their interaction with humans, should they only be aware of the user’s cognitive load. While mobile sensing and machine learning lead to impressive advances in the inference of human movement, physical activity, routines, and other behavioural aspects, inferring cognitive load remains challenging due to a subtle manifestation of a user's mental engagement via vital signal reactions. These signals are often captured with obtrusive, expensive, purpose-built equipment, preventing seamless cognitive load inference for human - ubiquitous computing interaction adaptation. In our work we aim to enable large-scale unobtrusive cognitive load inference. In the talk I will present our experiences from different user studies in which we built and evaluated cognitive load inference models relying on data coming from a commodity smart phone, a wearable sensing device, and a software-defined-radio-based wireless radar. Finally, I will present our guidelines for future efforts in cognitive load inference and argue for closer interdisciplinary collaboration in this exciting research domain.


ČAS/PROSTOR: 16. september 2019 ob 17.00 v FAMNIT-VP2


Sead Jahić studied mathematics in Tuzla, and graduated in 2012. From 2012 to 2016 he was teaching assistant at the University of Tuzla in the field of Applied Mathematics and Computer Science. In the past academic year (2018/2019) he was teaching assistant at UP FAMNIT, where he taught the courses Programming 1, Programming 3 and Language Technologies for 3rd year students of the bachelor program. He is also a PhD student in Computer Science on the same University and his research is in the fields of Sentiment Analysis and Natural Language Processing (NLP).

NASLOV: Determining sentiment of tweets using lexicon and (AnA)-affirmative and non-affirmative words

On the seminar a simple model for sentiment tagging of Tweeter messages based on AnA (affirmative and non-affirmative) words and tagged sentiment dictionary (Kadunc-Šikonja dictionary) will be presented. A lexicon was used in combination with intensifiers, where an intensifier (AnA word), that stands next to a word, produces more powerful (more positive or more negative) sentiment values for that word - tweet at all.


Obe predavanji bosta v angleškem jeziku.