We are proud to present the following three keynote speakers, who will share their expertise with the participants of ACM UMAP 2021, the 29th Conference on User Modeling, Adaptation and Personalization. In this article, you find the speakers’ biographies and the titles of their keynote talks.

Contextual features have been leveraged by recommender systems in many different domains. Traditional contextual features -- such as location and time -- have successfully been combined with collaborative filtering or content-based features. However, it is likely that there are other -- domain-specific -- features that may have even more impact. In this paper, we focus on the influence of city size on food preferences. Apart from location and time, our results show that city size can significantly boost the performance of food recommendation.

Historically, there have always been differences in how men and women cook or eat. The reasons for this gender divide have mostly gone in Western culture, but still there is qualitative and anecdotal evidence that men prefer heftier food, that women take care of everyday cooking, and that men cook to impress. In this paper, we show that these differences can also quantitatively be observed in a large dataset of almost 200 thousand members of an online recipe community. Further, we show that, using a set of 88 features, the gender of the cooks can be predicted with fairly good accuracy of 75%, with preference for particular dishes, the use of spices and the use of kitchen utensils being the strongest predictors. Finally, we show the positive impact of our results on online food recipe recommender systems that take gender information into account.

Giang Tran, Eelco Herder, Katja Markert. Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2015.

The LAK Data Challenge 2015 continues the research efforts of the previous data competitions in 2013 and 2014 by stimulating research on the evolving fields Learning Analytics (LA) and Educational Data Mining (EDM). Building on a series of activities of the LinkedUp project, the challenge aims to generate new insights and analysis on the LA & EDM disciplines and is supported through the LAK Dataset - a unique corpus of LA & EDM literature, exposed in structured and machine-readable formats.

The LAK Data Challenge 2014 continues the research efforts of the second edition by stimulating research on the evolving fields Learning Analytics (LA) and Educational Data Mining (EDM). Building on a series of activities of the LinkedUp project, the challenge aims to generate new insights and analysis on the LA & EDM disciplines and is supported through the LAK Dataset - a unique corpus of LA & EDM literature, exposed in structured and machine-readable formats.

Abstract: Learning material usually has a logical structure, with a beginning and an end, and lectures or sections that build upon one another. However, in informal Web-based learning this may not be the case. In this paper, we present a method for automatically calculating a tentative order in which objects should be learned based on the estimated complexity of their contents. Thus, the proposed method is based on a process that enriches textual objects with links to Wikipedia articles, which are used to calculate a complexity score for each object. We evaluated our method with two different datasets: Wikipedia articles and online learning courses. For Wikipedia data we achieved correlations between the ground truth and the predicted order of up to 0.57 while for subtopics inside the online learning courses we achieved correlations of 0.793. 1

In the past decade, the World Wide Web has been subject to dramatic changes. Web sites have evolved from static information resources to dynamic and interactive applications that are used for a broad scope of activities on a daily basis. To examine the consequences of these changes on user behavior, we conducted a long-term client-side Web usage study with twenty-five participants. This report presents results of this study and compares the user behavior with previous long-term browser usage studies, which range in age from seven to thirteen years. Based on the empirical data and the interview results, various implications for the interface design of browsers and Web sites are discussed. A major finding is the decreasing prominence of backtracking in Web navigation. This can largely be attributed to the increasing importance of dynamic, service-oriented Web sites. Users do not navigate on these sites searching for information, but rather interact with an online application to complete certain tasks. Furthermore, the usage of multiple windows and tabs has partly replaced back button usage, posing new challenges for user orientation and backtracking. We found that Web browsing is a rapid activity even for pages with substantial content, which calls for page designs that allow for cursory reading. Click maps provide additional information on how users interact with the Web on page level. Finally, substantial differences were observed between users, and characteristic usage patterns for different types of Web sites emphasize the need for more adaptive and customizable Web browsers.

This paper presents results of an extensive long-term click-stream study of Web browser usage. Focusing on character and challenges of page revisitation, previous findings from seven to thirteen years ago are updated. The term page re-visit had to be differentiated, since the recurrence rate--the key measure for the share of page revisits--turns out to strongly depend on interpretation. We identify different types of revisitation that allow assessing the quality of current user support and developing concepts for new tools.

This paper presents results of a long-term client-side Web usage study, updating previous studies that range in age from five to ten years. We focus on three aspects of Web navigation: changes in the distribution of navigation actions, speed of navigation and within-page navigation. “Navigation actions��? corresponding to users’ individual page requests are discussed by type. We reconfirm links to be the most important navigation element, while backtracking has lost more than half of its previously reported share and form submission has become far more common. Changes of the Web and the browser interfaces are candidates for causing these changes. Analyzing the time users stayed on pages, we confirm Web navigation to be a rapidly interactive activity. A breakdown of page characteristics shows that users often do not take the time to read the available text or consider all links. The performance of the Web is analyzed and reassessed against the resulting requirements. Finally, habits of within-page navigation are presented. Although most selected hyperlinks are located in the top left corner of the screen, in nearly a quarter of all cases people choose links that require scrolling. We analyzed the available browser real estate to gain insights for the design of non-scrolling Web pages.