Publikationen

Food recommenders have the potential to positively inuence theeating habits of users. To achieve this, however, we need to understandhow healthy recommendations are and the factors whichinuence this. Focusing on two approaches from the literature(single item and daily meal plan recommendation) and utilizing alarge Internet sourced dataset from Allrecipes.com, we show howalgorithmic solutions relate to the healthiness of the underlyingrecipe collection. First, we analyze the healthiness of Allrecipes.comrecipes using nutritional standards from the World Health Organisationand the United Kingdom Food Standards Agency. Second,we investigate user interaction patterns and how these relate to thehealthiness of recipes. Third, we experiment with both recommendationapproaches. Our results indicate that overall the recipes inthe collection are quite unhealthy, but this varies across categorieson the website. Users in general tend to interact most often with theleast healthy recipes. Recommender algorithms tend to score popularitems highly and thus on average promote unhealthy items. Thiscan be tempered, however, with simple post-ltering approaches,which we show by experiment are better suited to some algorithmsthan others. Similarly, we show that the generation of meal planscan dramatically increase the number of healthy options open tousers. One of the main ndings is, nevertheless, that the utilityof both approaches is strongly restricted by the recipe collection.Based on our ndings we draw conclusions how researchers shouldattempt to make food recommendation systems promote healthynutrition.

One government response to increasing incidence of lifestyle related illnesses, such as obesity, has been to encourage people to cook for themselves. The healthiness of home cooking will, nevertheless, depend on what people cook and how they cook it. In this article one common source of cooking inspiration - Internet-sourced recipes - is investigated in depth. The energy and macronutrient content of 5237 main meal recipes from the food website Allrecipes.com are compared with those of 100 main meal recipes from five bestselling cookery books from popular celebrity chefs and 100 ready meals from the three leading UK supermarkets. The comparison is made using nutritional guidelines published by the World Health Organisation and the UK Food Standards Agency. The main conclusions drawn from our analyses are that Internet recipes sourced from Allrecipes.com are less healthy than TV-chef recipes and ready meals from leading UK supermarkets. Only 6 out of 5237 Internet recipes fully complied with the WHO recommendations. Internet recipes were more likely to meet the WHO guidelines for protein than both other classes of meal (10.88% v 7% (TV), p<0.01; 10.86% v 9% (ready), p<0.01). However, the Internet recipes were less likely to meet the criteria for fat (14.28% v 24% (TV) v 37% (ready); p<0.01), saturated fat (25.05% v 33% (TV) v 34% (ready); p<0.01) and fibre (compared to ready meals 16.50% v 56%; p<0.01). More Internet recipes met the criteria for sodium density than ready meals (19.63% v 4%; p<0.01), but fewer than the TV-chef meals (19.32% v 36%; p<0.01). For sugar, no differences between Internet recipes and TV-chef recipes were observed (81.1% v 81% (TV); p=0.86), although Internet recipes were less likely to meet the sugar criteria than ready meals (81.1% v 83 % (ready); p<0.01). Repeating the analyses for each year of available data shows that the results are very stable over time.

Busy lifestyles, abundant options, lack of knowledge ... there are many reasons why people make poor decisions relating to their health. Yet these poor decisions are leading to epidemics, which represent some of the greatest challenges we face as a society today. Noncommunicable Diseases (NCDs), which include cardiovascular diseases, cancer, chronic respiratory diseases and diabetes, account for ∼60% of total deaths worldwide. These diseases share the same four behavioural risk factors: tobacco use, unhealthy diet, physical inactivity and harmful consumption of alcohol and can be prevented and sometimes even reversed with simple lifestyle changes. Eating more healthily, exercising more appropriately, sleeping and relaxing more, as well as simply being more aware of one’s state of health are all things that would lead to improved health. Yet knowing exactly what to change and how, implementing changes and maintaining changes over long time periods are all things people find challenging. These are also problems, for which we believe recommender systems can provide assistance by offering specific, tailored suggestions for behavioural change. In recent years recommender systems for health has become a popular topic within the RecSys community and a selection of empirical contributions and demo systems have been published. Efforts to date, however have been sporadic and lack coordination. We lack shared infrastructure such as datasets, appropriate cross-disciplinary knowledge, even agreed upon goals. It is our aim to use this workshop as a vehicle to: