Exploratory topic modeling with distributional semantics

As we continue to collect and store textual data in a multitude of domains, we are regularly confronted with material whose largely unknown thematic structure we want to uncover. With unsupervised, exploratory analysis, no prior knowledge about the content is required and highly open-ended tasks can be supported. In the past few years, probabilistic topic modeling has emerged as a popular approach to this problem. Nevertheless, the representation of the latent topics as aggregations of semi-coherent terms limits their interpretability and level of detail. This paper presents an alternative approach to topic modeling that maps topics as a network for exploration, based on distributional semantics using learned word vectors. From the granular level of terms and their semantic similarity relations global topic structures emerge as clustered regions and gradients of concepts. Moreover, the paper discusses the visual interactive representation of the topic map, which plays an important role in supporting its exploration.Comment: Conference: The Fourteenth International Symposium on Intelligent Data Analysis (IDA 2015

Modality-specific attention in foraging bumblebees

V.N. was funded by a Marie Curie Incoming International Fellowship. L.C. was funded by a Royal Society Wolfson Research Merit Award and an ERC Advanced Grant

Visual search for featural singletons: No top-down modulation, only bottom-up priming.

The present study investigated the effect of top-down knowledge on search for a feature singleton (a "pop-out target"). In a singleton detection task, advance cueing of the dimension of upcoming singleton resulted in cueing costs and benefits (Experiment 1). When the search for the singleton stayed the same but only the response requirements were changed, advance cueing failed to have an effect (Experiments 2 and 3). In singleton search only bottom-up priming plays a role (Experiments 4 and 5). We conclude that expectancy-based, top-down knowledge cannot guide the search for a featural singleton. Bottom-up priming that does facilitate search for a featural singleton cannot be influenced by top-down control. The study demonstrates that effects often attributed to early top-down guidance may represent effects that occur later in processing or represent bottom-up priming effects. © 2006 Psychology Press Ltd

Deployment of spatial attention towards locations in memory representations: an EEG study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics

Dozens of new models on fixation prediction are published every year and compared on open benchmarks such as MIT300 and LSUN. However, progress in the field can be difficult to judge because models are compared using a variety of inconsistent metrics. Here we show that no single saliency map can perform well under all metrics. Instead, we propose a principled approach to solve the benchmarking problem by separating the notions of saliency models, maps and metrics. Inspired by Bayesian decision theory, we define a saliency model to be a probabilistic model of fixation density prediction and a saliency map to be a metric-specific prediction derived from the model density which maximizes the expected performance on that metric given the model density. We derive these optimal saliency maps for the most commonly used saliency metrics (AUC, sAUC, NSS, CC, SIM, KL-Div) and show that they can be computed analytically or approximated with high precision. We show that this leads to consistent rankings in all metrics and avoids the penalties of using one saliency map for all metrics. Our method allows researchers to have their model compete on many different metrics with state-of-the-art in those metrics: "good" models will perform well in all metrics.Comment: published at ECCV 201

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio

Contextual cropping and scaling of TV productions

This is the author's accepted manuscript. The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-011-0804-3. Copyright @ Springer Science+Business Media, LLC 2011.In this paper, an application is presented which automatically adapts SDTV (Standard Definition Television) sports productions to smaller displays through intelligent cropping and scaling. It crops regions of interest of sports productions based on a smart combination of production metadata and systematic video analysis methods. This approach allows a context-based composition of cropped images. It provides a differentiation between the original SD version of the production and the processed one adapted to the requirements for mobile TV. The system has been comprehensively evaluated by comparing the outcome of the proposed method with manually and statically cropped versions, as well as with non-cropped versions. Envisaged is the integration of the tool in post-production and live workflows

Women and Illegal Activities: Gender Differences and Women's Willingness to Comply Over Time

In recent years the topics of illegal activities such as corruption or tax evasion have attracted a great deal of attention. However, there is still a lack of substantial empirical evidence about the determinants of compliance. The aim of this paper is to investigate empirically whether women are more willing to be compliant than men and whether we observe (among women and in general) differences in attitudes among similar age groups in different time periods (cohort effect) or changing attitudes of the same cohorts over time (age effect) using data from eight Western European countries from the World Values Survey and the European Values Survey that span the period from 1981 to 1999. The results reveal higher willingness to comply among women and an age rather than a cohort effect. Working Paper 06-5

Acute effects of nicotine on visual search tasks in young adult smokers

Rationale Nicotine is known to improve performance on tests involving sustained attention and recent research suggests that nicotine may also improve performance on tests involving the strategic allocation of attention and working memory. Objectives We used measures of accuracy and response latency combined with eye-tracking techniques to examine the effects of nicotine on visual search tasks. Methods In experiment 1 smokers and non-smokers performed pop-out and serial search tasks. In experiment 2, we used a within-subject design and a more demanding search task for multiple targets. In both studies, 2-h abstinent smokers were asked to smoke one of their own cigarettes between baseline and tests. Results In experiment 1, pop-out search times were faster after nicotine, without a loss in accuracy. Similar effects were observed for serial searches, but these were significant only at a trend level. In experiment 2, nicotine facilitated a strategic change in eye movements resulting in a higher proportion of fixations on target letters. If the cigarette was smoked on the first trial (when the task was novel), nicotine additionally reduced the total number of fixations and refixations on all letters in the display. Conclusions Nicotine improves visual search performance by speeding up search time and enabling a better focus of attention on task relevant items. This appears to reflect more efficient inhibition of eye movements towards task irrelevant stimuli, and better active maintenance of task goals. When the task is novel, and therefore more difficult, nicotine lessens the need to refixate previously seen letters, suggesting an improvement in working memory

Reducing bias in auditory duration reproduction by integrating the reproduced signal

Duration estimation is known to be far from veridical and to differ for sensory estimates and motor reproduction. To investigate how these differential estimates are integrated for estimating or reproducing a duration and to examine sensorimotor biases in duration comparison and reproduction tasks, we compared estimation biases and variances among three different duration estimation tasks: perceptual comparison, motor reproduction, and auditory reproduction (i.e. a combined perceptual-motor task). We found consistent overestimation in both motor and perceptual-motor auditory reproduction tasks, and the least overestimation in the comparison task. More interestingly, compared to pure motor reproduction, the overestimation bias was reduced in the auditory reproduction task, due to the additional reproduced auditory signal. We further manipulated the signal-to-noise ratio (SNR) in the feedback/comparison tones to examine the changes in estimation biases and variances. Considering perceptual and motor biases as two independent components, we applied the reliability-based model, which successfully predicted the biases in auditory reproduction. Our findings thus provide behavioral evidence of how the brain combines motor and perceptual information together to reduce duration estimation biases and improve estimation reliability