The Experts below are selected from a list of 239694 Experts worldwide ranked by ideXlab platform
Dionysios Klavdianos - One of the best experts on this subject based on the ideXlab platform.
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Gillette Labs Heated Razor Packaging Design Analysis
internal, 2019Co-Authors: Dionysios KlavdianosAbstract:Certification Symbols The packaging does not feature any certification symbols. the Functional Description User Interaction
Panagiotis Giannopoulos - One of the best experts on this subject based on the ideXlab platform.
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Schick Hydro Skin Comfort -Stubble Eraser Packaging Design Analysis
internal, 2021Co-Authors: Panagiotis GiannopoulosAbstract:-52-35.png image2021-4-1_14-53-33.png image2021-4-1_14-54-29.png Functional Description User Interaction / Ergonomics
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DSC4 Packaging Design Analysis
internal, 2020Co-Authors: Panagiotis GiannopoulosAbstract:Description User Interaction / Ergonomics Opening / Closing Dispensing Information – Communication Storing
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DSC6 Packaging Design Analysis
internal, 2020Co-Authors: Panagiotis GiannopoulosAbstract:, dyes, parabens For sensitive skin Functional Description User Interaction / Ergonomics Opening / Closing Dispensing
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Gillette Fusion5 Proshield Packaging Design Analysis
internal, 2019Co-Authors: Panagiotis GiannopoulosAbstract:an arrow shaped formation which indicated the opening handle. image2019-4-10_16-40-2.png Functional Description User Interaction
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Gillette Skinguard Packaging Design Analysis
internal, 2019Co-Authors: Panagiotis GiannopoulosAbstract:. image2019-3-28_15-43-52.png Cereal and snack boxes Mixed paper (often found in magazines, mail) Functional Description User Interaction / Ergonomics The user interacts with the package via its unsealing process, opening and product access. The packaging does not feature any resealable
Jaewon Kim - One of the best experts on this subject based on the ideXlab platform.
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SIGIR - User Interaction in Mobile Web Search
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016Co-Authors: Jaewon KimAbstract:From previous studies, we believe that search behaviour on touch-enabled mobile devices is different from the behaviour with desktop screens. In the proposed research, we intend to explore User Interaction while searching with the aim of improving search experience on mobile devices.
Béatrice Lamche - One of the best experts on this subject based on the ideXlab platform.
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UMAP - Improving Mobile Recommendations through Context-Aware User Interaction
User Modeling Adaptation and Personalization, 2014Co-Authors: Béatrice LamcheAbstract:Mobile recommender systems provide personalized recommendations to help deal with today’s information overload. However, due to spatial limitations in mobile interfaces and uncertainty of the User’s preferences in the beginning, the improvement of the User experience remains one of the main challenges when designing these systems and has not been investigated thoroughly. This paper describes the aim and progress of the author’s PhD studies on the User Interaction, usability and accuracy of mobile recommender systems. The approach aims to combine different User Interaction methods with context-awareness to allow User-friendly personalized mobile recommendations.
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Decisions@RecSys - Selecting Gestural User Interaction Patterns for Recommender Applications on Smartphones
2013Co-Authors: Wolfgang Wörndl, Jan Weicker, Béatrice LamcheAbstract:Modern smartphones allow for gestural touchscreen and free-form User Interaction such as swiping across the touchscreen or shaking the device. However, User acceptance of motion gestures in recommender systems have not been studied much. In this work, we investigated the usage of gestural Interaction patterns for mobile recommender systems. We designed a prototype that implemented at least two input methods for each available function: standard on-screen buttons or menu options, and also a gestural Interaction pattern. In a User study, we then compared what input method Users would choose for a given function. Results showed that gesture usage depended on the specific task. In general, Users preferred simpler gestures and rarely switched their input method for a function during the test.
Madian Khabsa - One of the best experts on this subject based on the ideXlab platform.
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SIGIR - User Interaction Sequences for Search Satisfaction Prediction
Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2017Co-Authors: Rishabh Mehrotra, Imed Zitouni, Ahmed Hassan Awadallah, Ahmed El Kholy, Madian KhabsaAbstract:Detecting and understanding implicit measures of User satisfaction are essential for meaningful experimentation aimed at enhancing web search quality. While most existing studies on satisfaction prediction rely on Users' click activity and query reformulation behavior, often such signals are not available for all search sessions and as a result, not useful in predicting satisfaction. On the other hand, User Interaction data (such as mouse cursor movement) is far richer than just click data and can provide useful signals for predicting User satisfaction. In this work, we focus on considering holistic view of User Interaction with the search engine result page (SERP) and construct detailed universal Interaction sequences of their activity. We propose novel ways of leveraging the universal Interaction sequences to automatically extract informative, interpretable subsequences. In addition to extracting frequent, discriminatory and interleaved subsequences, we propose a Hawkes process model to incorporate temporal aspects of User Interaction. Through extensive experimentation we show that encoding the extracted subsequences as features enables us to achieve significant improvements in predicting User satisfaction. We additionally present an analysis of the correlation between various subsequences and User satisfaction. Finally, we demonstrate the usefulness of the proposed approach in covering abandonment cases. Our findings provide a valuable tool for fine-grained analysis of User Interaction behavior for metric development.
