Beyond the user : use and non-use in HCI

For many, an interest in Human-Computer Interaction is equivalent to an interest in usability. However, using computers is only one way of relating to them, and only one topic from which we can learn about interactions between people and technology. Here, we focus on not using computers – ways not to use them, aspects of not using them, what not using them might mean, and what we might learn by examining non-use as seriously as we examine use.

Elicitator : an expert elicitation tool for regression in ecology

Expert elicitation is the process of retrieving and quantifying expert knowledge in a particular domain. Such information is of particular value when the empirical data is expensive, limited, or unreliable. This paper describes a new software tool, called Elicitator, which assists in quantifying expert knowledge in a form suitable for use as a prior model in Bayesian regression. Potential environmental domains for applying this elicitation tool include habitat modeling, assessing detectability or eradication, ecological condition assessments, risk analysis, and quantifying inputs to complex models of ecological processes. The tool has been developed to be user-friendly, extensible, and facilitate consistent and repeatable elicitation of expert knowledge across these various domains. We demonstrate its application to elicitation for logistic regression in a geographically based ecological context. The underlying statistical methodology is also novel, utilizing an indirect elicitation approach to target expert knowledge on a case-by-case basis. For several elicitation sites (or cases), experts are asked simply to quantify their estimated ecological response (e.g. probability of presence), and its range of plausible values, after inspecting (habitat) covariates via GIS.

Population Monte Carlo Algorithm in High Dimensions

The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

Change in colour appearance of small defocused lights

Small long wavelength lights (≤ 1’ arc) change colour appearance with positive defocus, appearing yellow or white. I investigated influences of longitudinal chromatic aberration and monochromatic aberrations on colour appearance of small narrow band lights. Seven cyclopleged participants viewed a small light (1’ arc diameter, λmax range 510 - 628 nm) centred within a 4.6’ black annulus and surrounded by a uniform white field under photopic light levels. An optical trombone varied focus. Participants were required to vary the focus by moving the optical trombone in either positive or negative direction and report when they noticed a change in appearance of the defocused narrow band light. Longitudinal chromatic aberration was controlled using a Powell achromatizing lens and its doublet and triplet components that neutralized, doubled and reversed the eye’s chromatic aberration, respectively. Changes in colour appearance for a 628 nm light occurred without any lens at +0.5 ± 0.2D defocus and with the doublet at +0.6 ± 0.2 D. The achromatizing lens did not affect appearance and the phenomenon was evident with the triplet for negative defocus (-0.5 ± 0.3 D). Adaptive optics correction of astigmatism and higher order monochromatic aberration did not affect magnitude significantly. Colour changes occurred despite a range of participant L/M cone ratios. Direction of change in colour appearance was reversed for short compared to long wavelengths. We conclude that longitudinal chromatic aberrations, but not monochromatic aberrations, are involved in changing appearance of small lights with defocus. Additional neuronal mechanisms that may contribute to the colour changes are considered.

Effective pattern taxonomy mining in text documents

Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

Identification of factors predicting clickthrough in Web searching using neural network analysis

In this research, we aim to identify factors that significantly affect the clickthrough of Web searchers. Our underlying goal is determine more efficient methods to optimize the clickthrough rate. We devise a clickthrough metric for measuring customer satisfaction of search engine results using the number of links visited, number of queries a user submits, and rank of clicked links. We use a neural network to detect the significant influence of searching characteristics on future user clickthrough. Our results show that high occurrences of query reformulation, lengthy searching duration, longer query length, and the higher ranking of prior clicked links correlate positively with future clickthrough. We provide recommendations for leveraging these findings for improving the performance of search engine retrieval and result ranking, along with implications for search engine marketing