Unified Implicit and Explicit Feedback for Multi-Application User Interest Modeling

A user often interacts with multiple applications while working on a task. User models can be developed individually at each of the individual applications, but there is no easy way to come up with a more complete user model based on the distributed activity of the user. To address this issue, this research studies the importance of combining various implicit and explicit relevance feedback indicators in a multi-application environment. It allows different applications used for different purposes by the user to contribute user activity and its context to mutually support users with unified relevance feedback. Using the data collected by the web browser, Microsoft Word and Microsoft PowerPoint, Adobe Acrobat Writer and VKB, combinations of implicit relevance feedback with semi-explicit relevance feedback were analyzed and compared with explicit user ratings. Our past research show that multi-application interest models based on implicit feedback theoretically out performed single application interest models based on implicit feedback. Also in practice, a multi-application interest model based on semi-explicit feedback increased user attention to high-value documents. In the current dissertation study, we have incorporated topic modeling to represent interest in user models for textual content and compared similarity measures for improved recall and precision based on the text content. We also learned the relative value of features from content consumption applications and content production applications. Our experimental results show that incorporating implicit feedback in page-level user interest estimation resulted in significant improvements over the baseline models. Furthermore, incorporating semi-explicit content (e.g. annotated text) with the authored text is effective in identifying segment-level relevant content. We have evaluated the effectiveness of the recommendation support from both semi-explicit model (authored/annotated text) and unified model (implicit + semi-explicit) and have found that they are successful in allowing users to locate the content easily because the relevant details are selectively highlighted and recommended documents and passages within documents based on the user’s indicated interest. Our recommendations based on the semi-explicit feedback were viewed the same as those from unified feedback and recommendations based on semi-explicit feedback outperformed those from unified feedback in terms of matching post-task document assessments

LookBook: pioneering Inclusive beauty with artificial intelligence and machine learning algorithms

Technology's imperfections and biases inherited from historical norms are crucial to acknowledge. Rapid perpetuation and amplification of these biases necessitate transparency and proactive measures to mitigate their impact. The online visual culture reinforces Eurocentric beauty ideals through prioritized algorithms and augmented reality filters, distorting reality and perpetuating unrealistic standards of beauty. Narrow beauty standards in technology pose a significant challenge to overcome. Algorithms personalize content, creating "filter bubbles" that reinforce these ideals and limit exposure to diverse representations of beauty. This cycle compels individuals to conform, hindering the embrace of their unique features and alternative definitions of beauty. LookBook counters prevalent narrow beauty standards in technology. It promotes inclusivity and representation through self-expression, community engagement, and diverse visibility. LookBook comprises three core sections: Dash, Books, and Community. In Dash, users curate their experience through personalization algorithms. Books allow users to collect curated content for inspiration and creativity, while Community fosters connections with like-minded individuals. Through LookBook, users create a reality aligned with their unique vision. They control consumed content, nurturing individualism through preferences and creativity. This personalization empowers individuals to break free from narrow beauty standards and embrace their distinctiveness. LookBook stands out with its algorithmic training and data representation. It offers transparency on how personalization algorithms operate and ensures a balanced and diverse representation of physicalities and ethnicities. By addressing biases and embracing a wide range of identities, LookBook sparks a conversation for a technology landscape that amplifies all voices, fostering an environment celebrating diversity and prioritizing inclusivity

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

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

Adopted Statements in the Digital Age: Hearsay Responses to Social Media Likes

Social media users collectively register billions of likes each and every day to the endless flow of content posted on social networking websites. What an individual user actually intends by the quick click of the like button may vary widely. Perhaps she is conveying acknowledgement but not agreement. Maybe he is expressing support but not acceptance. Within the social media context, short-form clicks register the same response. Yet they may be intended to convey sorrow, joy, support, agreement, acknowledgement, humor, or a multitude of other emotions. What a user actually intends by social media likes depends entirely on the person and the post. In the evidentiary context of hearsay, however, the intent a user may be held to have manifested by liking online content has significant legal consequences. This Article addresses the nuanced question of applying social media likes to traditional rules governing the manifestation of adoptive statements in the hearsay context. It focuses on whether a like is a tacit adoption of the post itself or a far more casual and less concrete response that fails to manifest adoptive intent without more. Should a statement that would otherwise be excluded as the hearsay statement of a third party nonetheless be admitted as the statement of the individual who merely liked the comment? Does a single click manifest a belief in the truth of the online content? Or is a like merely an acknowledgement - the online equivalent of a shrug and nod - without more? How does a court discern this question when faced with the offer? This Article endeavors to answer these questions while offering courts and practitioners alike a functional analysis for determining whether social media likes may be deemed adoptive statements under traditional hearsay orthodoxy

EYE-AS-AN-INPUT FOR IMPROVING INTERACTIVE INFORMATION RETRIEVAL

In this work, Publication Access Through Tiered Interaction and Exploration (PATTIE) is presented with the eye as an additional input modality. PATTIE is built upon the scatter/gather information retrieval paradigm where users can explore a visual and interactive table-of-contents metaphor for large-scale document collections in an iterative manner. Additionally, the prototype has been integrated with eye-tracking through the web camera and experimental findings are provided to demonstrate a proof-of-concept for interest modeling at the term level and implicit relevance feedback on the gold standard inaugural 2019 Text REtrieval Conference Precision Medicine dataset (TREC PM). Low error rates for gaze tracking, and acceptable performance on binary classification of interest are reported as well as statistically significant increases in precision and recall performance for relevant information on a TREC PM task when PATTIE is used with eye-as-an-input versus a baseline PATTIE system.Doctor of Philosoph

Human-Computer Interaction

In this book the reader will find a collection of 31 papers presenting different facets of Human Computer Interaction, the result of research projects and experiments as well as new approaches to design user interfaces. The book is organized according to the following main topics in a sequential order: new interaction paradigms, multimodality, usability studies on several interaction mechanisms, human factors, universal design and development methodologies and tools

Gaze in remote collaboration: Where do people look during video conference in the context of student collaboration

This thesis presents the results of an exploratory pilot study designed to investigate where people look during remote collaboration using video conferencing. The main research question was "Where do people look at when having a remote meeting?" The experiment involved six participants recruited from Tampere University, who were divided into two groups of three. Each round of the experiment consisted of two tasks. In the first task, participants were given questions to discuss, and they were encouraged to talk freely. In the second task, participants were asked to solve puzzles on the Mural board. Gaze information was collected using myGaze software and ETU driver, with the duration of participants' gaze on areas of interest calculated using Excel formulas. The study found that the majority of the time during the video conference was spent looking at the videos of other participants. There was no significant difference in the mean duration of looking at their own video images between the two genders. The study also found that when working on platforms that indicate the cursor locations of users, looking at the videos of others was not necessarily needed, as hearing was more relied on. This study served as an exploratory pilot study, providing insights into where people look during remote collaboration using video conferencing. The findings of this study can be used to guide future research in this area and inform the design of video conferencing tools that can better support remote collaboration. Overall, this study contributes to a growing body of research on remote collaboration and provides insights into the role of gaze during video conferencing

Interpreting the Experience: The Impact of Map Literacy on Installation Usability Design

The design of highly interactive displays or installations for public spaces requires understanding of the capabilities, preferences, and experiences of broad audiences. In the case of immersive maps, levels of map literacy are particularly important. This project, The NC Audio Map, explores the ways by which geography might catalyze knowledge acquisition goals. The project seeks to identify what effects information processing through map literacy has on design of a novel installation. Map literacy and interpretation at large, as discussed in previous research are applied to the design of the NC Audio Map ubiquitous computing environment. The ultimate goal is to explore how user experience design may benefit from anticipating user information processing skills