Title: Controlled Imprecision: Fuzzy Technology for Exploration Processes
Everyday, the users search the web for things of their interest. On multiple occasions they expect precise, as much as possible, results. However, human’s curiosity and a need for being exposed to different things, things that provide some levels of novelty is an important part of the exploration processes.
Existing systems supporting the users in their search activities provide them with some variations, but it is not a controlled process. Diversity is accidental. The users do not have any influence on a degree or extensiveness of this diversity. In this presentation we state that application of fuzziness in systems supporting users in their search will allow them to guide and control mechanisms that identify alternatives, and influence recommendations. The fuzzy-based methodologies are capable of dealing with imprecise and vague statements, and can be applied to scenarios where the users want to relax their requirements. This means the users are able to browse and explore variety of things that do not match the search criteria to the highest possible degree. The two applications of fuzzy methods that ensure controllable selection processes and illustrate benefits of fuzzy-based processing of available information are illustrated. Firstly, we concentrate on social networks. A methodology for selecting groups of individuals that satisfy linguistically described requirements regarding the degree of matching between users’ interests and collective interests of groups is presented. Secondly, we offer a novel recommending approach that provides users with a fuzzy-based process aiming at construction of lists of suggested items. This is accomplished via explicit control of requirements regarding rigorousness of identifying users who become a reference base for generating suggestions. A new way of ranking items rated by multiple users based on Pythagorean fuzzy sets and taking into account not only assigned rates but also their number is described.
Marek Reformat (SM’05) received the
M.Sc. degree (Hons.) from the Technical University of Poznan, Poznan, Poland,
and the Ph.D. degree from the University of Manitoba, Winnipeg, MB, Canada. He
is currently a Professor with the Department of Electrical and Computer
Engineering, University of Alberta, Edmonton, AB, Canada. The goal of his
research activities is to develop methods and techniques for intelligent data
modeling and analysis leading to translation of data into knowledge, as well as
to design systems that possess abilities to imitate different aspects of human
behavior. In this context, the concepts of computational intelligence—with
fuzzy computing and possibility theory in particular—are key elements necessary
for capturing relationships between pieces of data and knowledge, and for
mimicking human ways of reasoning about opinions and facts. He also works on
computational intelligence-based approaches for dealing with information stored
on the web. He applies elements of fuzzy sets to social networks, linked data,
and Semantic Web in order to handle inherently imprecise information, and
provide users with unique facts retrieved from the data. All his activities
focus on introduction of human aspects to web and software systems which will
lead to the development of more human-aware and human-like systems. Dr.
Reformat has been a member of program committees of many international
conferences related to computational intelligence and software engineering. He
is actively involved in the North American Fuzzy Information Processing
Society. He is a member of the Association for Computing Machinery.