111,261 research outputs found
Validation of a recommender system for prompting omitted foods in online dietary assessment surveys
Recall assistance methods are among the key aspects that improve the accuracy
of online dietary assessment surveys. These methods still mainly rely on
experience of trained interviewers with nutritional background, but data driven
approaches could improve cost-efficiency and scalability of automated dietary
assessment. We evaluated the effectiveness of a recommender algorithm developed
for an online dietary assessment system called Intake24, that automates the
multiple-pass 24-hour recall method. The recommender builds a model of eating
behavior from recalls collected in past surveys. Based on foods they have
already selected, the model is used to remind respondents of associated foods
that they may have omitted to report. The performance of prompts generated by
the model was compared to that of prompts hand-coded by nutritionists in two
dietary studies. The results of our studies demonstrate that the recommender
system is able to capture a higher number of foods omitted by respondents of
online dietary surveys than prompts hand-coded by nutritionists. However, the
considerably lower precision of generated prompts indicates an opportunity for
further improvement of the system
The Assistive Multi-Armed Bandit
Learning preferences implicit in the choices humans make is a well studied
problem in both economics and computer science. However, most work makes the
assumption that humans are acting (noisily) optimally with respect to their
preferences. Such approaches can fail when people are themselves learning about
what they want. In this work, we introduce the assistive multi-armed bandit,
where a robot assists a human playing a bandit task to maximize cumulative
reward. In this problem, the human does not know the reward function but can
learn it through the rewards received from arm pulls; the robot only observes
which arms the human pulls but not the reward associated with each pull. We
offer sufficient and necessary conditions for successfully assisting the human
in this framework. Surprisingly, better human performance in isolation does not
necessarily lead to better performance when assisted by the robot: a human
policy can do better by effectively communicating its observed rewards to the
robot. We conduct proof-of-concept experiments that support these results. We
see this work as contributing towards a theory behind algorithms for
human-robot interaction.Comment: Accepted to HRI 201
Learning 21st century science in context with mobile technologies
The paper describes a project to support personal inquiry learning with handheld and desktop technology between formal and informal settings. It presents a trial of the technology and learning across a school classroom, sports hall, and library. The main aim of the study was to incorporate inquiry learning activities within an extended school science environment in order to investigate opportunities for technological mediations and to extract initial recommendations for the design of mobile technology to link inquiry learning across different contexts. A critical incident analysis was carried out to identify learning breakdowns and breakthroughs that led to design implications. The main findings are the opportunities that a combination of mobile and fixed technology bring to: manage the formation of groups, display live visualisations of student and teacher data on a shared screen to facilitate motivation and personal relevance, incorporate broader technical support, provide context-specific guidance on the sequence, reasons and aims of learning activities, offer opportunities to micro-sites for reflection and learning in the field, to explicitly support appropriation of data within inquiry and show the relation between specific activities and the general inquiry process
Recommended from our members
Evaluation of business steps extension (e-business)
Evaluation of the Business Steps (e-business) programme, delivered in the East Midlands between August 2007 and March 2010 to improve business take-up of ICTs ('e-adoption'). Based on 500 beneficiary survey responses to investigate Strategic Added Value (SAV) and desk research to investigate net impact in GVA
Using fuzzy logic to handle the semantic descriptions of music in a content-based retrieval system
This paper explores the potential use of fuzzy logic for semantic music recommendation. We show that a set of affective/emotive, structural and kinaesthetic descriptors can be used to formulate a query which allows the retrieval of intended music. A semantic music recommendation system was built, based on an elaborate study of potential users and an analysis of the semantic descriptors that best characterize the user’s understanding of music. Significant relationships between expressive and structural semantic descriptions of music were found. Fuzzy logic was then applied to handle the
quality ratings associated with the semantic descriptions. A working semantic music recommendation system was tested and evaluated. Real-world testing revealed high user satisfaction
Personal recommendations in requirements engineering : the OpenReq approach
[Context & motivation] Requirements Engineering (RE) is considered as one of the most critical phases in software development but still many challenges remain open. [Problem] There is a growing trend of applying recommender systems to solve open RE challenges like requirements and stakeholder discovery; however, the existent proposals focus on specific RE tasks and do not give a general coverage for the RE process. [Principal ideas/results] In this research preview, we present the OpenReq approach to the development of intelligent recommendation and decision technologies that support different phases of RE in software projects. Specifically, we present the OpenReq part for personal recommendations for stakeholders. [Contribution] OpenReq aim is to improve and speed up RE processes, especially in large and distributed systemsPeer ReviewedPostprint (author's final draft
- …