Kviečiame į Informatikos inžinerijos problemų seminarą, kuris vyks kovo 28 d. (ketvirtadienį) 16 val. Duomenų mokslo ir skaitmeninių technologijų institute, Akademijos g. 4-203. Seminaro tema: Dr. Miroslav Hudec (Bratislavos ekonomikos universitetas, Slovakija) „Disjunctive and conjunctive aggregations in the data evaluation and retrieval tasks “.
Be šios temos, bus paliesta ir kita – „Linguistic summaries from the data: Issues and perspectives“, kuria dr. M. Hudec darys pranešimą Informatikos institute ( Didlaukio g. 47, 101 auditorija) kovo 27 d. (trečiadienį) 16 val.
Žemiau pateiktos temų anotacijos ir informacija apie pranešėją (jis atvykęs į VU pagal Erasmus+ mainų programą).
„Disjunctive and conjunctive aggregations in the data evaluation and retrieval tasks“
In evaluation we consider the satisfaction degree for elementary predicates. The disjunctive aggregation is formalized by any aggregation function bounded by the maximal value of elementary predicates and value 1. A convenient way to model disjunction is by t-conorms, which convey variety of algebraic properties and therefore are able to solve diverse tasks. The next class are tasks, where people consider OR operator as the left-right order of predicates, i.e. the first predicate is a full alternative, whereas the other are less relevant ones. This requirement is managed by the asymmetric disjunction, an aggregation of disjunctive and averaging functions. Diverse tasks require disjunctive functions of the desired properties. We should be aware of properties and limitation when recognizing suitable functions and their parameters to the users requirements, which are often expressed linguistically.
Due to duality with the conjunction, the similar observations holds for commutative and asymmetric conjunction. The talk gives also some real-world examples illustrating the situations where a given disjunctive and conjunctive semantics is the most appropriate.
„Linguistic summaries from the data: Issues and perspectives“
Summarization via traditional methods is a convenient approach for providing aggregated information. However, this is usually comprehensible only for users having a considerable level of statistical literacy. A promising alternative is augmenting the summarization linguistically. Summaries including, e.g., “most visits from remote countries are of a short duration” can be immediately understood by diverse users. Furthermore, linguistic summaries are applicable as quantified nested query conditions in data retrieval tasks. We can say that summary is: a more or less accurate textual description (summary) of a data set. This simple definition hides many challenges: construction of fuzzy sets for summarizers, restrictions and quantifiers, sufficient coverage of data and the like.
In cognitive cities we need approaches suitable for all stakeholders. Data dissemination in official statistics is another perspective field. The last but not the least, business intelligence questions can be answered by linguistic summaries. Furthermore, linguistically summarized sentence can be read out by a text-to-speech synthesis system, when the users’ visual attention should not be distracted.
Informacija apie pranešėją:
Miroslav Hudec is an associate professor at the University of Economics in Bratislava (Slovakia) and visiting professor at the University of Belgrade (Serbia). He received the Master and PhD degrees from the University of Belgrade (Serbia) in information science and operations research, respectively. His work is mainly focused on fuzzy logic, aggregation functions, knowledge discovery, and information systems. He is a member of program committees of several international conferences and serves as an editorial board member in several journals including Applied Soft Computing (IF 3.907). He has published more than 50 articles including monograph in Springer. In the FP7 project Blue-ETS focused on the modernising official statistics, he was leader of two working packages. http://www.fhi.sk/sk/kai/zamestnanci-katedry/miroslav-hudec.html