A summary of the third workshop on theory-informed user modeling for tailoring and personalizing interfaces

The third workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE) 1 took place in conjunction with the 24th annual meeting of the intelligent user interfaces (IUI) 2 community in Los Angeles, CA, USA on March 20, 2019. The goal of the workshop was to attract researchers from different fields by accepting contributions on the intersection of practical data mining methods and theoretical knowledge for personalization. A total of six papers were accepted for this edition of the workshop.

Using latent features diversification to reduce choice difficulty in recommendation lists

Ail important side effect of using recoinmender systems is a phenomenon called "choice overload"; the negative feeling incurred by the increased difficulty to choose from large sets of high quality recommendations. Choice overload has traditionally been related to the size of the item set, but recent work suggests that the diversity of the item set is an important moderator. Using the latent feanires of a matrix factorization algorithm, we were able to manipulate the diversity of the items, while controlling the overall attractiveness of the list of recommendations. In a user study, participants evaluated personalized item lists (varying in level of diversity) on perceived diversity and attractiveness, and their experienced choice difficulty and tradeoff difficulty. The results suggest that diversifying the recommendations might be an effective way to reduce choice overload, as perceived diversity and attractiveness increase with item set diversity, subsequently resulting in participants experiencing less tradeoff difficulty and choice difficulty.</p

Contactin-associated protein-2 antibodies in non-paraneoplastic cerebellar ataxia

Background Relatively few studies have searched for potentially pathogenic antibodies in non-paraneoplastic patients with cerebellar ataxia. Methods and Results We first screened sera from 52 idiopathic ataxia patients for binding of serum IgG antibodies to cerebellar neurons. One strong-binding serum was selected for immunoprecipitation and mass spectrometry, which resulted in the identification of contactin-associated protein 2 (CASPR2) as a major antigen. CASPR2 antibodies were then found by a cell-based assay in 9/88 (10%) ataxia patients, compared to 3/144 (2%) multiple sclerosis or dementia controls (p=0.011). CASPR2 is strongly expressed in the cerebellum, only partly in association with voltage-gated potassium channels. Conclusions Prospective studies are now needed to see whether identification of CASPR2 antibodies has relevance for the diagnosis and treatment of idiopathic cerebellar ataxia

Main assumptions for energy pathways

© The Author(s) 2019. The aim of this chapter is to make the scenario calculations fully transparent and comprehensible to the scientific community. It provides the scenario narratives for the reference case (5.0 °C) as well as for the 2.0 °C and 1.5 °C on a global and regional basis. Cost projections for all fossil fuels and renewable energy technologies until 2050 are provided. Explanations are given for all relevant base year data for the modelling and the main input parameters such as GDP, population, renewable energy potentials and technology parameters

β1 Integrin Maintains Integrity of the Embryonic Neocortical Stem Cell Niche

IInteractions between laminins and integrin receptors hold neural stem cells in place at the ventricular surface of embryonic brain. Transient disruption leads to abnormal stem cell divisions and permanent cortical malformation

Fourth HUMANIZE workshop on transparency and explainability in adaptive systems through user modeling grounded in psychological theory

The fourth HUMANIZE workshop1 on Transparency and Explainability in Adaptive Systems through User Modeling Grounded in Psychological Theory took place in conjunction with the 25th annual meeting of the Intelligent User Interfaces (IUI)2 community in Cagliari, Italy on March 17, 2020. The workshop provided a venue for researchers from different fields to interact by accepting contributions on the intersection of practical data mining methods and theoretical knowledge for personalization. A total of four papers was accepted for this edition of the workshop

Fourth HUMANIZE workshop on Transparency and Explainability in Adaptive Systems through User Modeling Grounded in Psychological Theory: Summary

The fourth HUMANIZE workshop1 on Transparency and Explainability in Adaptive Systems through User Modeling Grounded in Psychological Theory took place in conjunction with the 25th annual meeting of the Intelligent User Interfaces (IUI)2 community in Cagliari, Italy on March 17, 2020. The workshop provided a venue for researchers from different fields to interact by accepting contributions on the intersection of practical data mining methods and theoretical knowledge for personalization. A total of four papers was accepted for this edition of the workshop

Personalizing a parenting app:parenting-style surveys beat behavioral reading-based models

The present study set out to personalize a digital library aimed at new parents by reordering articles to match users' inferred interests. The interests were inferred from reading behavior as well as parenting styles measured through surveys. As prior research has shown that parenting styles are related to how parents take care of their children, these styles are likely to be related to what content a parent is interested in. The present study compared personalization based on parenting styles against other types of personalization. We conducted a user study with 106 participants, in which we compared the effects of four different approaches of personalization to our users' reading behavior and user experience: a non-personalized baseline, personalization based on reading behavior, personalization based on parenting styles measured through surveys, and a hybrid personalization based on both reading behavior and parenting styles. We found that while the reading behavior was not significantly influenced by different types of personalization, participants had a better user experience with our survey-based approach. They indicated they perceived a higher level of personalization and satisfaction with the system, even though in terms of objective metrics this approach performed worse.Part of Workshop 4: Theory-Informed User Modeling for Tailoring and Personalizing Interfaces - HUMANIZE</p

How item discovery enabled by diversity leads to increased recommendation list attractiveness

Applying diversity to a recommendation list has been shown to positively inuence the user experience. A higher perceived diversity is argued to have a positive effect on the attractiveness of the recommendation list and a negative effect on the difficulty to make a choice. In a user study we presented 100 participants with several personalized lists of recommended music artists varying in levels of diversity. Participants were asked to assess these lists on perceived diversity and attractiveness, the experienced choice difficulty and discovery (i.e., the extent the list enriches their taste). We found that recommendation list attractiveness is inuenced by two effects: 1) by diversity mediated through discovery; diverse recommendation lists are perceived to be more attractive if they enrich the user's taste or 2) by the list familiarity; a higher list familiarity contributes to a higher list attractiveness. We additionally revealed how individual differences (i.e., familiarity) moderate the effects found. Our results have implications on the composition of diversiffed recommendation lists. Specifically recommended items should contribute in extending and/or deepening the user's taste for the diversification to be effective