Frank Hopfgartner

Koblenz University of Applied Sciences

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Joemon M. Jose

University of Glasgow

Cathal Gurrin

Dublin City University

Till Plumbaum

Technische Universität Berlin

Benjamin Kille

Norwegian University of Science and Technology

Amon Rapp

University of Turin

Torben Brodt

Michael Meder

Robotics Research (United States)

Hideo Joho

University of Tsukuba

Udo Kruschwitz

University of Regensburg

ŞA

Şahin Albayrak

Technische Universität Berlin

Cooperative Institutions

University of Sheffield

Dublin City University

Technische Universität Berlin

University of Glasgow

Clarity Centre for Sensor Web Technologies

Trinity College Dublin

Delft University of Technology

Association for Computing Machinery

Radboud University Nijmegen

Centrum Wiskunde & Informatica

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Use of implicit graph for recommending relevant videos: a simulated evaluation

European Conference on Information Retrieval (2008)

David Vallet Frank Hopfgartner Joemon M. Jose

10.5555/1793274.1793301

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Citations (16)

Video browsing interfaces and applications: a review

Journal of Photonics for Energy (2010)

Klaus Schoeffmann Frank Hopfgartner Oge Marques Laszlo Boeszoermenyi Joemon M. Jose

We present a comprehensive review of the state of the art in video browsing and retrieval systems, with special emphasis on interfaces and applications. There has been a significant increase in activity (e.g., storage, retrieval, and sharing) employing video data in the past decade, both for personal and professional use. The ever-growing amount of video content available for human consumption and the inherent characteristics of video data-which, if presented in its raw format, is rather unwieldy and costly-have become driving forces for the development of more effective solutions to present video contents and allow rich user interaction. As a result, there are many contemporary research efforts toward developing better video browsing solutions, which we summarize. We review more than 40 different video browsing and retrieval interfaces and classify them into three groups: applications that use video-player-like interaction, video retrieval applications, and browsing solutions based on video surrogates. For each category, we present a summary of existing work, highlight the technical aspects of each solution, and compare them against each other.

Video retrieval

Interactive video

Video browsing

10.1117/6.0000005

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Citations (73)

Proceedings of the First International Workshop on Gamification for Information Retrieval

Frank Hopfgartner Gabriella Kazai Udo Kruschwitz Michael Meder

We are delighted to welcome you to the First International Workshop on Gamification for Information Retrieval, held on April 13, 2014 in conjunction with ECIR'14 in Amsterdam. This workshop focuses on the challenges and opportunities that gamification can present for the information retrieval (IR) community. Gamification is the application of game mechanics, such as leader boards, badges or achievement points, in non-gaming environments with the aim to increase user engagement, data quality or cost effectiveness. A core aspect of gamification solutions is to infuse intrinsic motivations to participate by leveraging people's natural desires for achievement and competition. While gamification, on the one hand, is emerging as the next big thing in industry, e.g., an effective way to generate business, on the other hand, it is also becoming a major research area. However, its adoption in Information Retrieval is still in its infancy, despite the wide ranging IR tasks that may benefit from gamification techniques. These include the manual annotation of documents for IR evaluation, the participation in user studies to study interactive IR challenges, or the shift from single-user search to social search, just to mention a few.

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Prognostic accuracy of triage tools for adults with suspected COVID-19 in a pre-hospital setting: an observational cohort study

medRxiv (Cold Spring Harbor Laboratory) (2021)

Carl Marincowitz Laura Sutton Tony Stone Richard Pilbery Richard Campbell

Abstract Study Objective Tools proposed to triage patient acuity in COVID-19 infection have only been validated in hospital populations. We estimated the accuracy of five risk-stratification tools recommended to predict severe illness and compare accuracy to existing clinical decision-making in a pre-hospital setting. Methods An observational cohort study using linked ambulance service data for patients attended by EMS crews in the Yorkshire and Humber region of England between 18th March 2020 and 29th June 2020 was conducted to assess performance of the PRIEST tool, NEWS2, the WHO algorithm, CRB-65 and PMEWS in patients with suspected COVID-19 infection. The primary outcome was death or need for organ support. Results Of 7549 patients in our cohort, 17.6% (95% CI:16.8% to 18.5%) experienced the primary outcome. The NEWS2, PMEWS, PRIEST tool and WHO algorithm identified patients at risk of adverse outcomes with a high sensitivity (>0.95) and specificity ranging from 0.3 (NEWS2) to 0.41 (PRIEST tool). The high sensitivity of NEWS2 and PMEWS was achieved by using lower thresholds than previously recommended. On index assessment, 65% of patients were transported to hospital and EMS decision to transfer patients achieved a sensitivity of 0.84 (95% CI 0.83 to 0.85) and specificity of 0.39 (95% CI 0.39 to 0.40). Conclusion Use of NEWS2, PMEWS, PRIEST tool and WHO algorithm could improve sensitivity of EMS triage of patients with suspected COVID-19 infection. Use of the PRIEST tool would improve sensitivity of triage without increasing the number of patients conveyed to hospital.

Triage

10.1101/2021.07.27.21261031

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MultiMedia modeling : 20th Anniversary International Conference, MMM 2014, Dublin, Ireland, January 6-10, 2014 : proceedings

Springer eBooks (2014)

Cathal Gurrin Frank Hopfgartner Wolfgang Huerst Håvard D. Johansen Hyowon Lee

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An Introduction to Retrieval and Reminiscence from Lifelog Archives at NTCIR

Frank Hopfgartner

In recent years, various software and hardware tools have entered the consumer market which enable users to log data about their lives on a continuous basis. Popular examples include self-tracking devices or apps such as Fitbit or Garmin that allow users to keep track of their physical activities or to monitor their biometrics. The process of gathering such multi-modal data from multiple sources is also referred to as lifelogging.

Lifelog

Reminiscence

10.1145/3512729.3533004

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Semantic User Modelling for Personal News Video Retrieval

Lecture notes in computer science (2009)

Frank Hopfgartner Joemon M. Jose

Video retrieval

Interface (matter)

10.1007/978-3-642-11301-7_35

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Citations (19)

Benchmarking News Recommendations

ACM SIGIR Forum (2016)

Frank Hopfgartner Torben Brodt Jonas Seiler Benjamin Kille Andreas Lommatzsch

The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to evaluate and optimize news recommender algorithms. The goal is to create an algorithm that is able to generate news items that users would click, respecting a strict time constraint. The lab challenges participants to compete in either a "living lab" (Task 1) or perform an evaluation that replays recorded streams (Task 2). In this report, we discuss the objectives and challenges of the NewsREEL lab, summarize last year's campaign and outline the main research challenges that can be addressed by participating in NewsREEL 2016.

Clef

Benchmarking

10.1145/2888422.2888443

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Citations (41)

Proceedings of the 20th Anniversary International Conference on MultiMedia Modeling - Volume 8325

Conference on Multimedia Modeling (2014)

Cathal Gurrin Frank Hopfgartner Wolfgang Hürst Håvard D. Johansen Hyowon Lee

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Adaptive interactive news video recommendation: an example system

Frank Hopfgartner

This position paper introduces a recommender system which has been developed to study research questions in the field of news video recommendation and personalization. The system is based on semantically enriched video data and can be seen as an example system that allows research on semantic models for adaptive interactive systems.

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Citations (3)