Helsinki Institute for Information Technology

About: Helsinki Institute for Information Technology is a facility organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Bayesian network. The organization has 630 authors who have published 1962 publications receiving 63426 citations.

Optimal status enforcement in abstract argumentation

Abstract: We present complexity results and algorithms for optimal status enforcement in abstract argumentation. Status enforcement is the task of adjusting a given argumentation framework (AF) to support given positive and negative argument statuses, i.e., to accept and reject specific arguments. We study optimal status enforcement as the problem of finding a structurally closest AF supporting given argument statuses. We establish complexity results for optimal status enforcement under several central AF semantics, develop constraint-based algorithms for NP and second-level complete variants of the problem, and empirically evaluate the procedures.

Quantitative evaluation of the effectiveness of idea generation in the wild

Abstract: New ideas are the primary building blocks in attempts to produce novel interactive technology. Numerous idea generation methods such as Brainstorming have been introduced to support this process, but there is mixed evidence regarding their effectiveness. In this paper we describe an experimental, quantitative methodology from the domain of product design research for evaluating different idea generation methods. We present prominent results from relevant literature and new data from a study of idea generation in the wild. The study focused on the effects of the physical environment, or in other words, the physical context, on designers' capacity to produce ideas. 25 students working in small groups took part in an experiment with two design tasks. Moving from an office environment to the actual surroundings of the intended use, we discovered that the change in resulting ideas was surprisingly small. Of the measured dimensions, the real-world context influenced only the feasibility of ideas, leaving quantity, novelty, utility and level of detail unaffected. This finding questions the value of diving into the context as a design idea generation practice.

Pointing while Looking Elsewhere: Designing for Varying Degrees of Visual Guidance during Manual Input

Abstract: We propose using eye tracking to support interface use with decreased reliance on visual guidance. While the design of most graphical user interfaces take visual guidance during manual input for granted, eye tracking allows distinguishing between the cases when the manual input is conducted with or without guidance. We conceptualize the latter cases as input with uncertainty that require separate handling. We describe the design space of input handling by utilizing input resources available to the system, possible actions the system can realize and various feedback techniques for informing the user. We demonstrate the particular action mechanisms and feedback techniques through three applications we developed for touch interaction on a large screen. We conducted a two stage study of positional accuracy during target acquisition with varying visual guidance, to determine the selection range around a touch point due to positional uncertainty. We also conducted a qualitative evaluation of example applications with participants to identify perceived utility and hand eye coordination challenges while using interfaces with decreased visual guidance.

Linear-in-$$\varDelta $$Δ lower bounds in the LOCAL model

Abstract: By prior work, there is a distributed graph algorithm that finds a maximal fractional matching (maximal edge packing) in $$O(\varDelta )$$O(Δ) rounds, independently of $$n$$n; here $$\varDelta $$Δ is the maximum degree of the graph and $$n$$n is the number of nodes in the graph. We show that this is optimal: there is no distributed algorithm that finds a maximal fractional matching in $$o(\varDelta )$$o(Δ) rounds, independently of?$$n$$n. Our work gives the first linear-in-$$\varDelta $$Δ lower bound for a natural graph problem in the standard $$\mathsf{LOCAL }$$LOCAL model of distributed computing--prior lower bounds for a wide range of graph problems have been at best logarithmic in $$\varDelta $$Δ.

Filter merging for efficient information dissemination

Abstract: In this paper we present a generic formal framework for filter merging in content-based routers The proposed mechanism is independent of the used filtering language and routing data structure We assume that the routing structure computes the minimal cover set It supports merging of filters from local clients, hierarchical routing, and peer-to-peer routing The mechanism is also transparent and does not require modifications in other routers in the distributed system to achieve benefits In addition to content-based routers, the system may also be used in firewalls and auditing gateways We present and analyze experimental results for the system