News

2017-07-06 new paper

Measuring Traffic Congestion

Measuring traffic congestion: An approach based on learning weighted inequality, spread and aggregation indices from comparison data has been accepted for publication in Applied Soft Computing. Assigned DOI is 10.1016/j.asoc.2017.07.014. Simon James did a wonderful work leading this research project. The paper was written in collaboration with researchers from Deakin University, namely: Gleb Beliakov, Shannon Pace, Nicola Pastorello, Elodie Thilliez, and Rajesh Vasa.
Abstract. As cities increase in size, governments and councils face the problem of designing infrastructure and approaches to traffic management that alleviate congestion. The problem of objectively measuring congestion involves taking into account not only the volume of traffic moving throughout a network, but also the inequality or spread of this traffic over major and minor intersections. For modelling such data, we investigate the use of weighted congestion indices based on various aggregation and spread functions. We formulate the weight learning problem for comparison data and use real traffic data obtained from a medium-sized Australian city to evaluate their usefulness.
2017-06-21 invited talk

Invited Tutorial @ AGOP 2017

Today I gave a tutorial at the 9th International Summer School on Aggregation Operators – AGOP 2017 held at University of Skövde, Sweden.

Abstract. Aggregation theory classically deals with functions to summarize a sequence of numeric values, e.g., in the unit interval. Since the notion of componentwise monotonicity plays a key role in many situations, there is an increasingly growing interest in methods that act on diverse ordered structures.

However, as far as the definition of a mean or an averaging function is concerned, the internality (or at least idempotence) property seems to be of a relatively higher importance than the monotonicity condition. In particular, the Bajraktarević means or the mode are among some well-known non-monotone means.

The concept of a penalty-based function was first investigated by Yager in 1993. In such a framework, we are interested in minimizing the amount of "disagreement" between the inputs and the output being computed; the corresponding aggregation functions are at least idempotent and express many existing means in an intuitive and attractive way.

In this talk I focus on the notion of penalty-based aggregation of sequences of points in Rd, this time for some d≥1. I review three noteworthy subclasses of penalty functions: componentwise extensions of unidimensional ones, those constructed upon pairwise distances between observations, and those defined by measuring the so-called data depth. Then, I discuss their formal properties, which are particularly useful from the perspective of data analysis, e.g., different possible generalizations of internality or equivariances to various geometric transforms. I also point out the difficulties with extending some notions that are key in classical aggregation theory, like the monotonicity property.

2017-05-23 new paper

EUSFLAT'17: Fitting symmetric fuzzy measures for discrete Sugeno integration

A paper by Simon James and I entitled Fitting symmetric fuzzy measures for discrete Sugeno integration has been accepted for publication in the Proceedings of EUSFLAT conference.
2017-04-20 invited talk

rOpenSci Text Workshop

This week I'm at the rOpenSci Text Workshop organized by Ken Benoit from the London School of Economics and Political Science. This workshop is designed to bring the R text package developers' community, to share experiences and knowledge, and hopefully foster cooperation.
2017-04-07 software

stringi 1.1.5 released

Another bugfix release of the stringi package for R is on its way to CRAN. The package provides powerful string processing facilities to R users and developers and is ranked as one of the most often downloaded R extensions.

Changelog:

* [GENERAL] `stringi` now requires ICU4C >= 52.

* [GENERAL] `stringi` now requires R >= 2.14.

* [BUGFIX] Fixed errors pointed out by `clang-UBSAN` in `stri_brkiter.h`.

* [BUILD TIME] #238, #220: Try "standard" ICU4C build flags if a call
to `pkg-config` fails.

* [BUILD TIME] #258: Use `CXX11` instead of `CXX1X` on R >= 3.4.

* [BUILD TIME, BUGFIX] #254: `dir.exists()` is R >= 3.2.
2017-03-21 software

stringi 1.1.3 released

I have submitted a new (bugfix) release of the stringi package to CRAN.

Changelog:

* [REMOVE DEPRECATED] `stri_install_check()` and `stri_install_icudt()`
marked as deprecated in `stringi` 0.5-5 are no longer being exported.

* [BUGFIX] #227: Incorrect behavior of `stri_sub()` and `stri_sub<-()`
if the empty string was the result.

* [BUILD TIME] #231: The `./configure` (*NIX only) script now reads the
following environment varialbes: `STRINGI_CFLAGS`, `STRINGI_CPPFLAGS`,
`STRINGI_CXXFLAGS`, `STRINGI_LDFLAGS`, `STRINGI_LIBS`, `STRINGI_DISABLE_CXX11`,
`STRINGI_DISABLE_ICU_BUNDLE`, `STRINGI_DISABLE_PKG_CONFIG`, `PKG_CONFIG`,
see `INSTALL` for more information.

* [BUILD TIME] #253: call to `R_useDynamicSymbols` added.

* [BUILD TIME] #230: icudt is now being downloaded by
`./configure` (*NIX only) *before* building.

* [BUILD TIME] #242: `_COUNT/_LIMIT` enum constants have been deprecated
as of ICU 58.2, stringi code has been upgraded accordingly.
2017-03-15 new paper

FUZZ-IEEE'17: Two Papers Accepted

Two papers I co-author have been accepted for publication in Proceedings of the FUZZ-IEEE'17 conference that will be held in Naples, Italy.
  • Bartoszuk M., Gagolewski M., Binary aggregation functions in software plagiarism detection
  • Cena A., Gagolewski M., OWA-based linkage and the Genie correction for hierarchical clustering
2016-12-12 new paper

Penalty-Based Aggregation of Multidimensional Data

My paper Penalty-Based Aggregation of Multidimensional Data has been accepted for publication in Fuzzy Sets and Systems (Special Issue on Aggregation Functions).
Abstract. Research in aggregation theory is nowadays still mostly focused on algorithms to summarize tuples consisting of observations in some real interval or of diverse general ordered structures. Of course, in practice of information processing many other data types between these two extreme cases are worth inspecting. This contribution deals with the aggregation of lists of data points in Rd for arbitrary d≥1. Even though particular functions aiming to summarize multidimensional data have been discussed by researchers in data analysis, computational statistics and geometry, there is clearly a need to provide a comprehensive and unified model in which their properties like equivariances to geometric transformations, internality, and monotonicity may be studied at an appropriate level of generality. The proposed penalty-based approach serves as a common framework for all idempotent information aggregation methods, including componentwise functions, pairwise distance minimizers, and data depth-based medians. It also allows for deriving many new practically useful tools.