CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

How to make privacy policies both GDPR-compliant and usable

It is important for organisations to ensure that their privacy policies are General Data Protection Regulation (GDPR) compliant, and this has to be done by the May 2018 deadline. However, it is also important for these policies to be designed with the needs of the human recipient in mind. We carried out an investigation to find out how best to achieve this.We commenced by synthesising the GDPR requirements into a checklist-type format. We then derived a list of usability design guidelines for privacy notifications from the research literature. We augmented the recommendations with other findings reported in the research literature, in order to confirm the guidelines. We conclude by providing a usable and GDPR-compliant privacy policy template for the benefit of policy writers

Optimizing product recommendations for a try-before-you-buy fashion e-commerce sit

The fashion e-commerce market has experienced a significant growth and more and more customers tend to buy products online, rather than in physical stores. However, after a customer buys a product online, only a fraction of the garments stay in their wardrobe as many items are being returned to the vendor. Due to the absence of physical examination and misleading product descriptions customers struggle to find the right product suitable to their personal preferences. Especially the category of women’s lingerie suffers to a great extend from high return rates. Different sources report that between 70 up to 100% of women wear wrong sized bras. Personalized recommendations through so called recommendation systems play an essential role in e-commerce. This thesis aims to optimize the current product recommendations of a Belgium start-up called CurveCatch that sells women’s lingerie articles online and relies on a try-before-you-buy concept. To predict which products a customer is likely to buy two different personalized deep learning approaches were introduced. Data sparsity was addressed by labeling each unique product per customer and minority classes were synthetically oversampled. The findings demonstrated that recommendation systems are not only relevant for companies operating on a large scale. Rather, they also can be a valuable source of accurate recommendations for start-ups with sparse data. However, results also underlined well-known limitations of recommendation systems. Both models struggled especially when identifying products a customer is likely to buy, while it was rather easy to identify products a customer is not likely to buy.O mercado de e-commerce de moda experimentou um crescimento significativo e cada vez mais os clientes tendem a comprar produtos online, em vez de em lojas físicas. No entanto, muitos itens são devolvidos ao vendedor após a compra online, pois os clientes têm dificuldade em encontrar o produto certo adequado às suas preferências pessoais devido à falta de exame físico e às descrições de produtos enganosas. A categoria de lingerie feminina sofre muito com as altas taxas de devolução. Diferentes fontes relatam que entre 70% e 100% das mulheres usam sutiãs do tamanho errado. As recomendações personalizadas através dos chamados sistemas de recomendação desempenham um papel essencial no e-commerce. Esta tese visa otimizar as atuais recomendações de produtos de uma start-up belga chamada CurveCatch que vende artigos de lingerie feminina online e depende de um conceito de experimente antes de comprar. Para prever quais produtos um cliente é mais propenso a comprar, foram introduzidos dois diferentes abordagens de aprendizado profundo personalizadas. A escassez de dados foi abordada rotulando cada produto único por cliente e as classes minoritárias foram sobreamostradas sinteticamente. Os resultados demonstraram que os sistemas de recomendação também podem ser uma fonte valiosa de recomendação de produtos para start-ups com dados escassos. No entanto, os resultados também sublinharam as bem conhecidas limitações dos sistemas de recomendação. Ambos os modelos lutaram especialmente ao identificar os produtos que um cliente é mais propenso a comprar, enquanto era relativamente fácil identificar os produtos que um cliente não é propenso a comprar

Develop Guidelines for Pavement Preservation Treatments and for Building a Pavement Preservation Program Platform for Alaska

INE/AUTC 12.0

Include 2011 : The role of inclusive design in making social innovation happen.

Include is the biennial conference held at the RCA and hosted by the Helen Hamlyn Centre for Design. The event is directed by Jo-Anne Bichard and attracts an international delegation

Commercialisation of precision agriculture technologies in the macadamia industry

A prototype vision-based yield monitor has been developed for the macadamia industry. The system estimates yield for individual trees by detecting nuts and their harvested location. The technology was developed by the National Centre for Engineering in Agriculture, University of Southern Queensland for the purpose of reducing labour and costs in varietal assessment trials where yield for individual trees are required to be measured to indicate tree performance. The project was commissioned by Horticulture Australia Limited

AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI

Humans and AI systems are usually portrayed as separate sys- tems that we need to align in values and goals. However, there is a great deal of AI technology found in non-autonomous systems that are used as cognitive tools by humans. Under the extended mind thesis, the functional contributions of these tools become as essential to our cognition as our brains. But AI can take cognitive extension towards totally new capabil- ities, posing new philosophical, ethical and technical chal- lenges. To analyse these challenges better, we define and place AI extenders in a continuum between fully-externalized systems, loosely coupled with humans, and fully-internalized processes, with operations ultimately performed by the brain, making the tool redundant. We dissect the landscape of cog- nitive capabilities that can foreseeably be extended by AI and examine their ethical implications. We suggest that cognitive extenders using AI be treated as distinct from other cognitive enhancers by all relevant stakeholders, including developers, policy makers, and human users