Ponedeljkov seminar računalništva in informatike - Arhiv

V ponedeljek, 1. junija 2020, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 1. junij 2020 ob 16.00 na daljavo.

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PREDAVATELJ: Nuwan ATTYGALLE
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Nuwan Attygalle is a PhD student in Computer Science in the field of Human-Computer interactions and a teaching assistant at the University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies. He is also a member of the HICUP Lab at the Department of Information Sciences and Technologies.

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NASLOV: Pandemic era app development
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The presenter is going to talk about a technological approach to help slow the spread of SARS-COV-2 by simplifying and accelerating the process of notifying people who might have been exposed to the virus while preserving their privacy.
Key to end, control the spread in an epidemic is rapid identification and quarantine of the infected individuals, determination of whom they have had close contact within the previous days and decontamination of locations the infected individual has visited.
This process is labour intensive, susceptible to memory errors, and fraught with privacy concerns. But the main advantage in this era is the availability of smart-phones, mobile devices, and with the right technology we can overcome above difficulties and track down infected individuals in a much productive way.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://us02web.zoom.us/j/297328207

Vabljeni!

V ponedeljek, 25. maja 2020, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 25. maj 2020 ob 16.00 na daljavo 

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PREDAVATELJ: Jamolbek MATTIEV
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Jamolbek Mattiev has a Master degree in Computer Science from National University of Uzbekistan. He was awarded with first degree diploma at “the best Master Dissertation Work of Uzbekistan” competition in his master studies. He is a Teaching Assistant at the University of Primorska, Faculty of Mathematics, Natural Sciences and Information Technologies and he is the third year PhD student at the Department of Information Sciences and Technologies.
He is doing his PhD in the field of Computer Science (Data Mining). His research fields include Artificial Intelligence, Data Mining, Machine Learning. In particular, the sub-fields of Supervised and Unsupervised Learning, Frequent Pattern Discovery, Association Rule Learning, Classification and Clustering.

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NASLOV: Clustering class association rules to form a Compact and Meaningful Associative Classifier
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Huge amounts of data are being collected and analyzed nowadays. By using the popular rule-learning algorithms, the number of rules discovered on those big datasets can easily exceed thousands of rules. To produce compact and accurate classifiers, such rules have to be grouped and pruned, so that only a reasonable number of them are presented to the end user for inspection and further analysis. To solve this problem researchers have proposed several associative classification approaches that combine two important data mining techniques, namely, classification and association rule mining.

In this research, we propose a new method that is able to reduce the number of class association rules produced by classical class association rule classifiers, while maintaining an accurate classification model that is comparable to the ones generated by state-of-the-art classification algorithms. More precisely, we propose a new associative classifier – CMAC, that uses agglomerative hierarchical clustering as a post-processing step to reduce the number of its rules.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://us02web.zoom.us/j/297328207

Vabljeni!

V ponedeljek, 11. maja 2020, bo ob 16.00 uri prek spletnih orodij na daljavo izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 11. maj 2020 ob 16.00 na daljavo 

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PREDAVATELJICA: Elham MOTAMEDI
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Elham Motamedi is a PhD student at UP FAMNIT. She completed her Master's degree of networked systems at the University of Tehran, Iran and her Bachelor's degree of information technology at the Isfahan University of Technology, Iran. Her research interests include multimedia and recommender systems.

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NASLOV: User-centric multimedia characteristics: A Survey
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The properties of multimedia content are usually represented as content-centered metadata, such as type (e.g. video, audio, text, etc.), duration, resolution, etc. However, in user-centric applications, such as personalized recommender systems, it makes more sense to describe multimedia items with user-centric meta-data, such as genre, emotions, etc. For example, a recommender system would make a better job of explaining recommendations in the form of "You have been recommended this film because you liked comedies" than "You have been recommended this film because you liked 1:30 long films". The problem of such a characterization is that it usually requires humans to annotate with user-centric metadata, which is expensive. Hence,  research efforts have been made to develop automatic methods for mapping multimedia content to user-centric item characteristics.
In this presentation, I present some of the state-of-the-art studies in studying automatic approaches for predicting user-centric characteristics of multimedia contents and some raw ideas of future work.

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Predavanje bo potekalo v angleškem jeziku prek spletnega orodja Zoom.
Do predavanja dostopate tako, da se povežete prek sledeče povezave:

https://us02web.zoom.us/j/297328207

Vabljeni!

On Monday, 4th of May 2020 at 4 PM we kindly invite you to attend the (on-line)  MONDAY COMPUTER SCIENCE SEMINAR organized by the Department of Information Sciences and Technologies at UP FAMNIT and UP IAM, this time joint with the MATHEMATICAL RESEARCH SEMINAR organized by the Department of Mathematics at UP FAMNIT and UP IAM.

TIME and PLACE: 4th of May 2020 at 4 PM on-line 

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PRESENTER: Vladimir BATAGELJ
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Vladimir Batagelj, Professor Emeritus
   IMFM - Institute of Mathematics, Physics, and Mechanics
   Jadranska 19, 1000 Ljubljana, Slovenia and
   University of Primorska, Andrej Marušič Institute, Koper and
   NRU HSE, Applied Network Research Lab, Moscow
W: http://vladowiki.fmf.uni-lj.si/doku.php?id=vlado

RECENT PUBLICATIONS:
On fractional approach to analysis of linked networks
   (https://doi.org/10.1007/s11192-020-03383-y)
Clustering and Generalized ANOVA for Symbolic Data
   (http://www.iste.co.uk/book.php?id=1597)
Temporal bibliographic networks
   (https://authors.elsevier.com/a/1aRuH6EAijpVq-)
Advances in Network Clustering and Blockmodeling (book) 
   (https://www.wiley.com/en-si/Advances+in+Network+Clustering+and+Blockmodeling-p-9781119224709)

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TITLE: NetsJSON - part 2
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ABSTRACT: 

A network consists of a graph and additional data on (properties of) nodes and/or links.
In some applications, the values of properties can be structured objects such us intervals, compositions, sets of keywords, temporal quantities, etc. Standard network description formats do not support such kinds of networks. 
We propose a JSON based format NetsJSON as a general network description option. It is supported in Python by a network analysis library Nets. The NetsJSON descriptions can be used as input data for network visualizations based on D3.js.

REFERENCES:
[1] Batagelj, V.: Python Packages for Networks. Encyclopedia of Social Network Analysis and
    Mining. Reda Alhajj, Jon Rokne (Eds.), Springer, 2017
    https://link.springer.com/referenceworkentry/10.1007%2F978-1-4614-7163-9_110210-1
[2] Batagelj, V., Maltseva, D.: Temporal bibliographic networks. Journal of Informetrics,
    14(2020)1, 101006. https://www.sciencedirect.com/science/article/pii/S1751157719301439
[3] Batagelj, V.: Nets. https://github.com/bavla/Nets
[4] Batagelj, V.: NetsJSON. https://github.com/bavla/netsJSON

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The seminar will be held in English through the videoconferencing tool Zoom.
This seminar is the follow-up of the seminar given on the 6th of April 2020.
You can connect to the seminar using the following link:

https://zoom.us/j/297328207

You are very welcome!