Evaluation of recommender systems in streaming environments

Evaluation of recommender systems is typically done with finite datasets. This means that conventional evaluation methodologies are only applicable in offline experiments, where data and models are stationary. However, in real world systems, user feedback is continuously generated, at unpredictable rates. Given this setting, one important issue is how to evaluate algorithms in such a streaming data environment. In this paper we propose a prequential evaluation protocol for recommender systems, suitable for streaming data environments, but also applicable in stationary settings. Using this protocol we are able to monitor the evolution of algorithms' accuracy over time. Furthermore, we are able to perform reliable comparative assessments of algorithms by computing significance tests over a sliding window. We argue that besides being suitable for streaming data, prequential evaluation allows the detection of phenomena that would otherwise remain unnoticed in the evaluation of both offline and online recommender systems.Comment: Workshop on 'Recommender Systems Evaluation: Dimensions and Design' (REDD 2014), held in conjunction with RecSys 2014. October 10, 2014, Silicon Valley, United State

Why musical memory can be preserved in advanced Alzheimer's disease

Musical memory is relatively preserved in Alzheimer's disease and other dementias. In a 7 Tesla functional MRI study employing multi-voxel pattern analysis, Jacobsen et al. identify brain regions encoding long-term musical memory in young healthy controls, and show that these same regions display relatively little atrophy and hypometabolism in patients with Alzheimer's disease.See Clark and Warren (doi:10.1093/brain/awv148) for a scientific commentary on this article. Musical memory is relatively preserved in Alzheimer's disease and other dementias. In a 7 Tesla functional MRI study employing multi-voxel pattern analysis, Jacobsen et al. identify brain regions encoding long-term musical memory in young healthy controls, and show that these same regions display relatively little atrophy and hypometabolism in patients with Alzheimer's disease.See Clark and Warren (doi:10.1093/awv148) for a scientific commentary on this article

The affective modulation of motor awareness in anosognosia for hemiplegia : Behavioural and lesion evidence

© 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).The possible role of emotion in anosognosia for hemiplegia (i.e., denial of motor deficits contralateral to a brain lesion), has long been debated between psychodynamic and neurocognitive theories. However, there are only a handful of case studies focussing on this topic, and the precise role of emotion in anosognosia for hemiplegia requires empirical investigation. In the present study, we aimed to investigate how negative and positive emotions influence motor awareness in anosognosia. Positive and negative emotions were induced under carefully-controlled experimental conditions in right-hemisphere stroke patients with anosognosia for hemiplegia (n = 11) and controls with clinically normal awareness (n = 10). Only the negative, emotion induction condition resulted in a significant improvement of motor awareness in anosognosic patients compared to controls; the positive emotion induction did not. Using lesion overlay and voxel-based lesion-symptom mapping approaches, we also investigated the brain lesions associated with the diagnosis of anosognosia, as well as with performance on the experimental task. Anatomical areas that are commonly damaged in AHP included the right-hemisphere motor and sensory cortices, the inferior frontal cortex, and the insula. Additionally, the insula, putamen and anterior periventricular white matter were associated with less awareness change following the negative emotion induction. This study suggests that motor unawareness and the observed lack of negative emotions about one's disabilities cannot be adequately explained by either purely motivational or neurocognitive accounts. Instead, we propose an integrative account in which insular and striatal lesions result in weak interoceptive and motivational signals. These deficits lead to faulty inferences about the self, involving a difficulty to personalise new sensorimotor information, and an abnormal adherence to premorbid beliefs about the body.Peer reviewedFinal Published versio

Predicting Audio Advertisement Quality

Online audio advertising is a particular form of advertising used abundantly in online music streaming services. In these platforms, which tend to host tens of thousands of unique audio advertisements (ads), providing high quality ads ensures a better user experience and results in longer user engagement. Therefore, the automatic assessment of these ads is an important step toward audio ads ranking and better audio ads creation. In this paper we propose one way to measure the quality of the audio ads using a proxy metric called Long Click Rate (LCR), which is defined by the amount of time a user engages with the follow-up display ad (that is shown while the audio ad is playing) divided by the impressions. We later focus on predicting the audio ad quality using only acoustic features such as harmony, rhythm, and timbre of the audio, extracted from the raw waveform. We discuss how the characteristics of the sound can be connected to concepts such as the clarity of the audio ad message, its trustworthiness, etc. Finally, we propose a new deep learning model for audio ad quality prediction, which outperforms the other discussed models trained on hand-crafted features. To the best of our knowledge, this is the first large-scale audio ad quality prediction study.Comment: WSDM '18 Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 9 page

Report on the Information Retrieval Festival (IRFest2017)

The Information Retrieval Festival took place in April 2017 in Glasgow. The focus of the workshop was to bring together IR researchers from the various Scottish universities and beyond in order to facilitate more awareness, increased interaction and reflection on the status of the field and its future. The program included an industry session, research talks, demos and posters as well as two keynotes. The first keynote was delivered by Prof. Jaana Kekalenien, who provided a historical, critical reflection of realism in Interactive Information Retrieval Experimentation, while the second keynote was delivered by Prof. Maarten de Rijke, who argued for more Artificial Intelligence usage in IR solutions and deployments. The workshop was followed by a "Tour de Scotland" where delegates were taken from Glasgow to Aberdeen for the European Conference in Information Retrieval (ECIR 2017

The Limits of Emotion in Moral Judgment

I argue that our best science supports the rationalist idea that, independent of reasoning, emotions aren’t integral to moral judgment. There’s ample evidence that ordinary moral cognition often involves conscious and unconscious reasoning about an action’s outcomes and the agent’s role in bringing them about. Emotions can aid in moral reasoning by, for example, drawing one’s attention to such information. However, there is no compelling evidence for the decidedly sentimentalist claim that mere feelings are causally necessary or sufficient for making a moral judgment or for treating norms as distinctively moral. I conclude that, even if moral cognition is largely driven by automatic intuitions, these shouldn’t be mistaken for emotions or their non-cognitive components. Non-cognitive elements in our psychology may be required for normal moral development and motivation but not necessarily for mature moral judgment

Neurophysiological Mechanisms of Statistical Learning in Adults with and without Reading Disorders

The artificial grammar learning (AGL) task first introduced by Reber (1967) as well as similar paradigms (e.g., Jost et al., 2015) are thought to elicit implicit statistical learning (SL) of underlying patterns in typical readers. However, previous research has shown that individuals with dyslexia often show difficulty with such incidental learning, on AGL and other SL tasks (Kahta & Schiff., 2016; Singh, Walk and Conway, 2018). Because few studies have investigated this link between statistical learning and reading ability, the current study was designed to examine the neurophysiological and behavioral correlates in adults with and without a reading disorder diagnosis. Sixteen reading impaired and thirty-seven typically reading adults were recruited for the study and completed the AGL, and SL (visual-motor; auditory-motor) tasks, followed by completion of questionnaires eliciting awareness of underlying patterns. During these tasks, behavioral measures such as response times and grammaticality classifications were recorded. Additionally, event-related potentials (ERPs) were also acquired during the computerized tasks. Following this, normed assessments indexing cognitive, reading and spelling ability as well as basic musical ability were administered to participants. Prevalence of attention-deficit symptoms was also accounted for by administration of a checklist. The aim was to assess the underlying mechanisms of implicit-statistical learning such as transition-timing and chunking as well as grammaticality (algebraic patterns and ordinal knowledge) via varied task paradigms (SL and AGL respectively) and non-linguistic stimuli. Although behavioral results were comparable across groups, ERP amplitude differences vary in topology across groups – especially for grammaticality and chunk strength, but not so much for the transition timing paradigms. For atypical readers, correlations were only found between symbol search scores and ERP responses for grammaticality. Thus, overall, the current study highlights the need to assess participants in terms of overall learning capacity before investigating the link between implicit-statistical learning capacity and reading ability. Additionally, findings indicate that participants were not as sensitive to non-linguistic items across learning paradigms as they might have been to purely linguistic items