"More of an art than a science": Supporting the creation of playlists and mixes

This paper presents an analysis of how people construct playlists and mixes. Interviews with practitioners and postings made to a web site are analyzed using a grounded theory approach to extract themes and categorizations. The information sought is often encapsulated as music information retrieval tasks, albeit not as the traditional "known item search" paradigm. The collated data is analyzed and trends identified and discussed in relation to music information retrieval algorithms that could help support such activity

Causal Theories of Reference for Proper Names

Presentation and comparison of the main causal theories of reference for proper names, and a proposal of a new approach based on the analogy of the causal chain of reference with the block chain from blockchain technology and Paul Ricœur's narrative theory. After a brief Introduction in which the types of sentences from the concept of possible worlds are reviewed, and an overview of the theory in the Causal Theory of Reference, I present the causal theory of the reference proposed by Saul Kripke, then two hybrid causal theories developed by Gareth Evans and Michael Devitt. In the section Blockchain and the causal tree of reference I present my idea of developing a new causal theory of reference for proper names through a causal tree of reference. In the Conclusions I talk about the further development of the ways in which the terms of reference could refer to certain objects and individuals, the main criticisms of the causal theories, and suggestions for future development. CONTENTS: Abstract Introduction 1. The causal theory of reference 2. Saul Kripke 3. Gareth Evans 4. Michael Devitt 5. Blockchain and the causal tree of reference Conclusions Bibliografie DOI: 10.13140/RG.2.2.26330.9056

Reconceptualising Personas Across Cultures: Archetypes, Stereotypes & Collective Personas in Pastoral Namibia

The paucity of projects where persona is the research foci and a lack of consensus on this artefact keep many reticent about its purpose and value. Besides crafting personas is expected to differ across cultures, which contrasts the advancements in Western theory with studies and progress in other sites. We postulate User-Created Personas reveal specific characteristics of situated contexts by allowing laypeople to design persona artefacts in their own terms. Hence analysing four persona sessions with an ethnic group in pastoral Namibia –ovaHerero– brought up a set of fundamental questions around the persona artefact regarding stereotypes, archetypes, and collective persona representations: (1) to what extent user depictions are stereotypical or archetypal? If stereotypes prime (2) to what degree are current personas a useful method to represent end-users in technology design? And, (3) how can we ultimately read accounts not conforming to mainstream individual persona descriptions but to collectives

Semantic bottleneck for computer vision tasks

This paper introduces a novel method for the representation of images that is semantic by nature, addressing the question of computation intelligibility in computer vision tasks. More specifically, our proposition is to introduce what we call a semantic bottleneck in the processing pipeline, which is a crossing point in which the representation of the image is entirely expressed with natural language , while retaining the efficiency of numerical representations. We show that our approach is able to generate semantic representations that give state-of-the-art results on semantic content-based image retrieval and also perform very well on image classification tasks. Intelligibility is evaluated through user centered experiments for failure detection

Language-Driven Region Pointer Advancement for Controllable Image Captioning

Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated natural language caption. This puts a stronger focus on producing more detailed descriptions, and opens the door for more end-user control over results. A vital component of the Controllable Image Captioning architecture is the mechanism that decides the timing of attending to each region through the advancement of a region pointer. In this paper, we propose a novel method for predicting the timing of region pointer advancement by treating the advancement step as a natural part of the language structure via a NEXT-token, motivated by a strong correlation to the sentence structure in the training data. We find that our timing agrees with the ground-truth timing in the Flickr30k Entities test data with a precision of 86.55% and a recall of 97.92%. Our model implementing this technique improves the state-of-the-art on standard captioning metrics while additionally demonstrating a considerably larger effective vocabulary size