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

A comparison of artificial driving sounds for automated vehicles

As automated vehicles currently do not provide sufficient feedback relating to the primary driving task, drivers have no assurance that an automated vehicle has understood and can cope with upcoming traffic situations [16]. To address this we conducted two user evaluations to investigate auditory displays in automated vehicles using different types of sound cues related to the primary driving sounds: acceleration, deceleration/braking, gear changing and indicating. Our first study compared earcons, speech and auditory icons with existing vehicle sounds. Our findings suggested that earcons were an effective alternative to existing vehicle sounds for presenting information related to the primary driving task. Based on these findings a second study was conducted to further investigate earcons modulated by different sonic parameters to present primary driving sounds. We discovered that earcons containing naturally mapped sonic parameters such as pitch and timbre were as effective as existing sounds in a simulated automated vehicle

Video test collection with graded relevance assessments

Relevance is a complex, but core, concept within the field of Information Retrieval. In order to allow system comparisons the many factors that influence relevance are often discarded to allow abstraction to a single score relating to relevance. This means that a great wealth of information is often discarded. In this paper we outline the creation of a video test collection with graded relevance assessments, to the best of our knowledge the first example of such a test collection for video retrieval. To directly address the shortcoming above we also gathered behavioural and perceptual data from assessors during the assessment process. All of this information along with judgements are available for download. Our intention is to allow other researchers to supplement the judgements to help create an adaptive test collection which contains supplementary information rather than a completely static collection with binary judgements

Exploring how drivers perceive spatial earcons in automated vehicles

Automated vehicles seek to relieve the human driver from primary driving tasks, but this substantially diminishes the connection between driver and vehicle compared to manual operation. At present, automated vehicles lack any form of continual, appropriate feedback to re-establish this connection and offer a feeling of control. We suggest that auditory feedback can be used to support the driver in this context. A preliminary field study that explored how drivers respond to existing auditory feedback in manual vehicles was first undertaken. We then designed a set of abstract, synthesised sounds presented spatially around the driver, known as Spatial Earcons, that represented different primary driving sounds e.g. acceleration. To evaluate their effectiveness, we undertook a driving simulator study in an outdoor setting using a real vehicle. Spatial Earcons performed as well as Existing Vehicle Sounds during automated and manual driving scenarios. Subjective responses suggested Spatial Earcons produced an engaging driving experience. This paper argues that entirely new synthesised primary driving sounds, such as Spatial Earcons, can be designed for automated vehicles to replace Existing Vehicle Sounds. This creates new possibilities for presenting primary driving information in automated vehicles using auditory feedback, in order to re-establish a connection between driver and vehicle

Using thermal stimuli to influence affect in different picture display sizes

The ability of images to evoke emotions in people has been well documented in previous research, as well as the differences in the emotional perception of images when viewed on different-sized screens and device types. The ability of thermal stimuli to evoke emotions in people when used for media augmentation has also been examined. However little is known about how thermal stimuli can be used to enhance or reduce affect in images with varying emotional properties displayed in different sizes or on different devices. To the best of our knowledge no work has been conducted to investigate if there is any difference in the effect thermal augmentation has on images displayed in different sizes on different device types. This paper presents two user studies to address this research gap. Study 1 explored the effect thermal stimulation has on images displayed in different sizes. Images were displayed in sizes corresponding to the full screen display of a laptop, tablet and mobile phone. In study 2 we examined whether the actual presentation device (tablet and mobile) plays a role in the emotional perception of images displayed on mobile devices. Results showed that thermal augmentation was most effective in modulating emotions in small-sized pictures (427x240 pixels display size) and pictures displayed on a mobile phone. Thermal stimuli also reduced emotions in medium display sizes (corresponding to the full screen display of a tablet)

Using thermal stimuli to enhance photo-sharing in social media

Limited work has been undertaken to show how the emotive ability of thermal stimuli can be used for interaction purposes. One potential application area is using thermal stimuli to influence emotions in images shared online such as social media platforms. This paper presents a two-part study, which examines how the documented emotive property of thermal stimuli can be applied to enhance social media images. Participants in part-one supplied images from their personal collection or social media profiles, and were asked to augment each image with thermal stimuli based on the emotions they wanted to enhance or reduce. Part-one participants were interviewed to understand the effects they wanted augmented images to have. In part-two, these augmented images were perceived by a different set of participants in a simulated social media interface. Results showed strong agreement between the emotions augmented images were designed to evoke and the emotions they actually evoked as perceived by part-two participants. Participants in part-one selected thermal stimuli augmentation intended to modulate valence and arousal in images as a way of enhancing the realism of the images augmented. Part-two results indicate this was achieved as participants perceived thermal stimuli augmentation reduced valence in negative images and modulated valence and arousal in positive images

Towards quantifying the impact of non-uniform information access in collaborative information retrieval

The majority of research into Collaborative Information Retrieval (CIR) has assumed a uniformity of information access and visibility between collaborators. However in a number of real world scenarios, information access is not uniform between all collaborators in a team e.g. security, health etc. This can be referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, there has not yet been any systematic investigation of the effect of MLCIR on search outcomes. To address this shortcoming, in this paper, we present the results of a simulated evaluation conducted over 4 different non-uniform information access scenarios and 3 different collaborative search strategies. Results indicate that there is some tolerance to removing access to the collection and that there may not always be a negative impact on performance. We also highlight how different access scenarios and search strategies impact on search outcomes

Beyond Traditional Collaborative Search: Understanding the Effect of Awareness on Multi-Level Collaborative Information Retrieval

Although there has been a great deal of research into Collaborative Information Retrieval (CIR) and Collaborative Information Seeking (CIS), the majority has assumed that team members have the same level of unrestricted access to underlying information. However, observations from different domains (e.g. healthcare, business, etc.) have suggested that collaboration sometimes involves people with differing levels of access to underlying information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, no studies have been conducted to investigate the effect of awareness, an existing CIR/CIS concept, on MLCIR. To address this gap in current knowledge, we conducted two separate user studies using a total of 5 different collaborative search interfaces and 3 information access scenarios. A number of Information Retrieval (IR), CIS and CIR evaluation metrics, as well as questionnaires were used to compare the interfaces. Design interviews were also conducted after evaluations to obtain qualitative feedback from participants. Results suggested that query properties such as time spent on query, query popularity and query effectiveness could allow users to obtain information about team’s search performance and implicitly suggest better queries without disclosing sensitive data. Besides, having access to a history of intersecting viewed, relevant and bookmarked documents could provide similar positive effect as query properties. Also, it was found that being able to easily identify different team members and their actions is important for users in MLCIR. Based on our findings, we provide important design recommendations to help develop new CIR and MLCIR interfaces