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2022
Hakim Hacid; Monther Aldwairi; Mohamed Reda Bouadjenek; Marinella Petrocchi; Noura Faci; Fatma Outay; Amin Beheshti; Lauritz Thamsen; Hai Dong
Service-Oriented Computing - ICSOC 2021 Workshops - AIOps, STRAPS, AI-PA, and Satellite Events, Dubai, United Arab Emirates, November 22-25, 2021, Proceedings. Lecture Notes in Computer Science. Proceedings
2022.
BibTeX | Tags: Cristin | Links:
@proceedings{cristin1957036,
title = {Service-Oriented Computing - ICSOC 2021 Workshops - AIOps, STRAPS, AI-PA, and Satellite Events, Dubai, United Arab Emirates, November 22-25, 2021, Proceedings. Lecture Notes in Computer Science.},
author = {Hakim Hacid and Monther Aldwairi and Mohamed Reda Bouadjenek and Marinella Petrocchi and Noura Faci and Fatma Outay and Amin Beheshti and Lauritz Thamsen and Hai Dong},
url = {https://app.cristin.no/results/show.jsf?id=1957036, Cristin
https://link.springer.com/conference/icsoc},
year = {2022},
date = {2022-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {proceedings}
}
Bjørnar Tessem
The Future Technologies in Journalism Presentation
EBU Metadata Network 2022 Online Conference, 01.01.2022.
BibTeX | Tags: Cristin | Links:
@misc{cristin2028464,
title = {The Future Technologies in Journalism},
author = {Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=2028464, Cristin},
year = {2022},
date = {2022-01-01},
howpublished = {EBU Metadata Network 2022 Online Conference},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
Tord Kvifte; Mehdi Elahi; Christoph Trattner
Hybrid Recommendation of Movies based on Deep Content Features Proceedings Article
In: Springer Nature, 2022.
Abstract | BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1957037,
title = {Hybrid Recommendation of Movies based on Deep Content Features},
author = {Tord Kvifte and Mehdi Elahi and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1957037, Cristin
https://aip-research-center.github.io/AIPA_workshop/2021/},
year = {2022},
date = {2022-01-01},
booktitle = {Springer Nature},
abstract = {When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list. This paper investigates hybrid recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. We have evaluated our proposed technique using a large dataset of movies and shown that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Bjørnar Tessem; Lars Nyre; Michel dos Santos Mesquita; Paul Mulholland
Deep Learning to Encourage Citizen Involvement in Local Journalism Proceedings Article
In: Palgrave Macmillan, 2022.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin2023207,
title = {Deep Learning to Encourage Citizen Involvement in Local Journalism},
author = {Bjørnar Tessem and Lars Nyre and Michel dos Santos Mesquita and Paul Mulholland},
url = {https://app.cristin.no/results/show.jsf?id=2023207, Cristin},
doi = {https://doi.org/10.1007/978-3-030-95073-6_14},
year = {2022},
date = {2022-01-01},
booktitle = {Palgrave Macmillan},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
2021
Christoph Trattner; Dietmar Jannach; Enrico Motta; Irene Costera Meijer; Nicholas Diakopoulos; Mehdi Elahi; Andreas L. Opdahl; Bjørnar Tessem; Njål Borch; Morten Fjeld; Lilja Øvrelid; Koenraad De Smedt; Hallvard Moe
Responsible media technology and AI: challenges and research directions Journal Article
In: AI and Ethics, 2021.
BibTeX | Tags: Cristin | Links:
@article{cristin2000622,
title = {Responsible media technology and AI: challenges and research directions},
author = {Christoph Trattner and Dietmar Jannach and Enrico Motta and Irene Costera Meijer and Nicholas Diakopoulos and Mehdi Elahi and Andreas L. Opdahl and Bjørnar Tessem and Njål Borch and Morten Fjeld and Lilja Øvrelid and Koenraad De Smedt and Hallvard Moe},
url = {https://app.cristin.no/results/show.jsf?id=2000622, Cristin
https://link.springer.com/content/pdf/10.1007/s43681-021-00126-4.pdf},
doi = {https://doi.org/10.1007/s43681-021-00126-4},
year = {2021},
date = {2021-12-20},
urldate = {2021-12-20},
journal = {AI and Ethics},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Mehdi Elahi; Dietmar Jannach; Lars Skjærven; Erik Knudsen; Helle Sjøvaag; Kristian Tolonen; Øyvind Holmstad; Igor Pipkin; Eivind Throndsen; Agnes Stenbom; Eivind Fiskerud; Adrian Oesch; Loek Vredenberg; Christoph Trattner
Towards Responsible Media Recommendation Journal Article
In: AI and Ethics, 2021.
BibTeX | Tags: Cristin | Links:
@article{cristin1953352,
title = {Towards Responsible Media Recommendation},
author = {Mehdi Elahi and Dietmar Jannach and Lars Skjærven and Erik Knudsen and Helle Sjøvaag and Kristian Tolonen and Øyvind Holmstad and Igor Pipkin and Eivind Throndsen and Agnes Stenbom and Eivind Fiskerud and Adrian Oesch and Loek Vredenberg and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1953352, Cristin
https://link.springer.com/article/10.1007%2Fs43681-021-00107-7},
doi = {https://doi.org/10.1007/s43681-021-00107-7},
year = {2021},
date = {2021-11-02},
journal = {AI and Ethics},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Bjørnar Tessem
Når kunstig intelligens inntar redaksjonen Medium
2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1942282,
title = {Når kunstig intelligens inntar redaksjonen},
author = {Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1942282, Cristin},
year = {2021},
date = {2021-10-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Lars Nyre; Bjørnar Tessem
Auka røynd (AR) Medium
Dag og Tid, 2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1894361,
title = {Auka røynd (AR)},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1894361, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Lars Nyre; Bjørnar Tessem
Ting i internettet Medium
Dag og Tid, 2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1931531,
title = {Ting i internettet},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1931531, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Lars Nyre; Bjørnar Tessem
Automatiske nyhende Medium
Dag og Tid, 2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1905817,
title = {Automatiske nyhende},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1905817, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Mehdi Elahi; Farshad Bakhshandegan Moghaddam; Reza Hosseini; Mohammad Hossein Rimaz; Nabil El Ioini; Marko Tkalcic; Christoph Trattner; Tammam Tillo
Recommending Videos in Cold Start With Automatic Visual Tags Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956967,
title = {Recommending Videos in Cold Start With Automatic Visual Tags},
author = {Mehdi Elahi and Farshad Bakhshandegan Moghaddam and Reza Hosseini and Mohammad Hossein Rimaz and Nabil El Ioini and Marko Tkalcic and Christoph Trattner and Tammam Tillo},
url = {https://app.cristin.no/results/show.jsf?id=1956967, Cristin
https://dl.acm.org/doi/10.1145/3450614.3461687},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
abstract = {This paper addresses the so-called New Item problem in video Recommender Systems, as part of Cold Start. New item problem occurs when a new item is added to the system catalog, and the recommender system has no or little data describing that item. This could cause the system to fail to meaningfully recommend the new item to the users. We propose a novel technique that can generate cold start recommendation by utilizing automatic visual tags, i.e., tags that are automatically annotated by deeply analyzing the content of the videos and detecting faces, objects, and even celebrities within the videos. The automatic visual tags do not need any human involvement and have been shown to be very effective in representing the video content. In order to evaluate our proposed technique, we have performed a set of experiments using a large dataset of videos. The results have shown that the automatically extracted visual tags can be incorporated into the cold start recommendation process and achieve superior results compared to the recommendation based on human-annotated tags.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Alain D. Starke; Edis Asotic; Christoph Trattner
“Serving Each User”: Supporting Different Eating Goals Through a Multi-List Recommender Interface Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956504,
title = {“Serving Each User”: Supporting Different Eating Goals Through a Multi-List Recommender Interface},
author = {Alain D. Starke and Edis Asotic and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956504, Cristin},
doi = {https://doi.org/10.1145/3460231.3474232},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Alain D. Starke; Christoph Trattner
Promoting Healthy Food Choices Online: A Case for Multi-List Recommender Systems Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956555,
title = {Promoting Healthy Food Choices Online: A Case for Multi-List Recommender Systems},
author = {Alain D. Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956555, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Cataldo Musto; Alain D. Starke; Christoph Trattner; Amon Rapp; Giovanni Semeraro
Exploring the effects of natural language justifications on food recommender systems Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956541,
title = {Exploring the effects of natural language justifications on food recommender systems},
author = {Cataldo Musto and Alain D. Starke and Christoph Trattner and Amon Rapp and Giovanni Semeraro},
url = {https://app.cristin.no/results/show.jsf?id=1956541, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Alain D. Starke; Christoph Trattner; Hedda Bakken; Martin Skivenesvåg Johannessen; Vegard Solberg
The Cholesterol Factor: Balancing Accuracy and Health in Recipe Recommendation Through a Nutrient-Specific Metric Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956600,
title = {The Cholesterol Factor: Balancing Accuracy and Health in Recipe Recommendation Through a Nutrient-Specific Metric},
author = {Alain D. Starke and Christoph Trattner and Hedda Bakken and Martin Skivenesvåg Johannessen and Vegard Solberg},
url = {https://app.cristin.no/results/show.jsf?id=1956600, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Marc Gallofré Ocaña; Andreas L. Opdahl
Developing a Software Reference Architecture for Journalistic Knowledge Platforms Journal Article
In: CEUR Workshop Proceedings, 2021.
BibTeX | Tags: Cristin | Links:
@article{cristin1949655,
title = {Developing a Software Reference Architecture for Journalistic Knowledge Platforms},
author = {Marc Gallofré Ocaña and Andreas L. Opdahl},
url = {https://app.cristin.no/results/show.jsf?id=1949655, Cristin
http://ceur-ws.org/Vol-2978/saml-paper2.pdf},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {CEUR Workshop Proceedings},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Mehdi Elahi; Danial Khosh Kholgh; Mohammad Sina Kiarostami; Sorush Saghari; Shiva Parsa Rad; Marko Tkalcic
Investigating the impact of recommender systems on user-based and item-based popularity bias Journal Article
In: Information Processing & Management, 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@article{cristin1953363,
title = {Investigating the impact of recommender systems on user-based and item-based popularity bias},
author = {Mehdi Elahi and Danial Khosh Kholgh and Mohammad Sina Kiarostami and Sorush Saghari and Shiva Parsa Rad and Marko Tkalcic},
url = {https://app.cristin.no/results/show.jsf?id=1953363, Cristin
https://www.sciencedirect.com/science/article/pii/S0306457321001436},
doi = {https://doi.org/10.1016/j.ipm.2021.102655},
year = {2021},
date = {2021-01-01},
journal = {Information Processing & Management},
abstract = {Recommender Systems are decision support tools that adopt advanced algorithms in order to help users to find less-explored items that can be interesting for them. While recommender systems may offer a range of attractive benefits, they may also intensify undesired effects, such as the Popularity Bias, where a few popular users/items get more popular and many unpopular users/items get more unpopular.
In this paper, we study the impact of different recommender algorithms on the popularity bias in different application domains and recommendation scenarios. We have designed a comprehensive evaluation methodology by considering two different recommendation scenarios, i.e., the user-based scenario (e.g., recommending users to users to follow), and the item-based scenario (e.g., recommending items to users to consume). We have used two large datasets, Twitter and Movielens, and compared a wide range of classical and modern recommender algorithms by considering a diverse range of metrics, such as PR-AUC, RCE, Gini index, and Entropy Score.
The results have shown a substantial difference between different scenarios and different recommendation domains. According to our observations, while the recommendation of users to users may increase the popularity bias in the system, the recommendation of items to users may indeed decrease it. Moreover, while we have measured a different level of popularity bias in different languages (i.e., English, Spanish, Portuguese, and Japaneses), the above-noted phenomena has been consistently observed in all of these languages.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
In this paper, we study the impact of different recommender algorithms on the popularity bias in different application domains and recommendation scenarios. We have designed a comprehensive evaluation methodology by considering two different recommendation scenarios, i.e., the user-based scenario (e.g., recommending users to users to follow), and the item-based scenario (e.g., recommending items to users to consume). We have used two large datasets, Twitter and Movielens, and compared a wide range of classical and modern recommender algorithms by considering a diverse range of metrics, such as PR-AUC, RCE, Gini index, and Entropy Score.
The results have shown a substantial difference between different scenarios and different recommendation domains. According to our observations, while the recommendation of users to users may increase the popularity bias in the system, the recommendation of items to users may indeed decrease it. Moreover, while we have measured a different level of popularity bias in different languages (i.e., English, Spanish, Portuguese, and Japaneses), the above-noted phenomena has been consistently observed in all of these languages.
Arngeir Berge; Vegard Velle Sjøen; Alain D. Starke; Christoph Trattner
Changing Salty Food Preferences with Visual and TextualExplanations in a Search Interface Journal Article
In: CEUR Workshop Proceedings, 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@article{cristin1933059,
title = {Changing Salty Food Preferences with Visual and TextualExplanations in a Search Interface},
author = {Arngeir Berge and Vegard Velle Sjøen and Alain D. Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1933059, Cristin
http://ceur-ws.org/Vol-2903/IUI21WS-HEALTHI-2.pdf},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {CEUR Workshop Proceedings},
abstract = {Salt is consumed at too high levels in the general population, causing high blood pressure and related health problems. In this paper, we present results of ongoing research that tries to reduce salt intake via technology and in particular from an interface perspective. In detail, this paper features results of a study that examines the extent to which visual and textual explanations in a search interface can change salty food preferences. An online user study with 200 participants demonstrates that this is possible in food search results by accompanying recipes with a visual taste map that includes salt-replacer herbs and spices in the calculation of salty taste.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Koenraad De Smedt
Contagious "Corona" Compounding by Journalists in a CLARIN Newspaper Monitor Corpus Proceedings Article
In: 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1918658,
title = {Contagious "Corona" Compounding by Journalists in a CLARIN Newspaper Monitor Corpus},
author = {Koenraad De Smedt},
url = {https://app.cristin.no/results/show.jsf?id=1918658, Cristin
https://ecp.ep.liu.se/index.php/clarin/article/view/10/209},
doi = {https://doi.org/https://doi.org/10.3384/ecp18010},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Erik Knudsen; Stefan Dahlberg; Magnus Hoem Iversen; Mikael Poul Johannesson; Silje Nygaard
How the public understands news media trust: An open-ended approach Journal Article
In: Journalism - Theory, Practice & Criticism, 2021.
BibTeX | Tags: Cristin | Links:
@article{cristin1902285,
title = {How the public understands news media trust: An open-ended approach},
author = {Erik Knudsen and Stefan Dahlberg and Magnus Hoem Iversen and Mikael Poul Johannesson and Silje Nygaard},
url = {https://app.cristin.no/results/show.jsf?id=1902285, Cristin},
doi = {https://doi.org/10.1177/14648849211005892},
year = {2021},
date = {2021-01-01},
journal = {Journalism - Theory, Practice & Criticism},
keywords = {Cristin},
pubstate = {published},
tppubtype = {article}
}
Arngeir Berge; Vegard Velle Sjøen; Alain D. Starke; Christoph Trattner
Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956563,
title = {Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface},
author = {Arngeir Berge and Vegard Velle Sjøen and Alain D. Starke and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956563, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Alain D. Starke; Sebastian Øverhaug Larsen; Christoph Trattner
Predicting Feature-based Similarity in the News Domain Using Human Judgments Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956594,
title = {Predicting Feature-based Similarity in the News Domain Using Human Judgments},
author = {Alain D. Starke and Sebastian Øverhaug Larsen and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1956594, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Himan Abdollahpouri; Mehdi Elahi; Masoud Mansoury; Shaghayegh Sahebi; Zahra Nazari; Allison Chaney; Babak Loni
MORS 2021: 1st Workshop on Multi Objective Recommender Systems Proceedings Article
In: Association for Computing Machinery (ACM), 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@inproceedings{cristin1956978,
title = {MORS 2021: 1st Workshop on Multi Objective Recommender Systems},
author = {Himan Abdollahpouri and Mehdi Elahi and Masoud Mansoury and Shaghayegh Sahebi and Zahra Nazari and Allison Chaney and Babak Loni},
url = {https://app.cristin.no/results/show.jsf?id=1956978, Cristin
https://dl.acm.org/doi/10.1145/3460231.3470936},
year = {2021},
date = {2021-01-01},
booktitle = {Association for Computing Machinery (ACM)},
abstract = {Historically, the main criterion for a successful recommender system was the relevance of the recommended items to the user. In other words, the only objective for the recommendation algorithm was to learn user’s preferences for different items and generate recommendations accordingly. However, real-world recommender systems are well beyond a simple objective and often need to take into account multiple objectives simultaneously. These objectives can be either from the users’ perspective or they could come from other stakeholders such as item providers or any party that could be impacted by the recommendations. Such multi-objective and multi-stakeholder recommenders present unique challenges and these challenges were the focus of the MORS workshop.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {inproceedings}
}
Erik Knudsen; Hallvard Moe
EN ANALYSE AV SAMMENHENGEN MELLOM BRUK AV NRKS DIGITALE NYHETSTILBUD OG BETALINGSVILJE FOR DIGITALE NYHETER Technical Report
2021.
BibTeX | Tags: Cristin | Links:
@techreport{cristin1958452,
title = {EN ANALYSE AV SAMMENHENGEN MELLOM BRUK AV NRKS DIGITALE NYHETSTILBUD OG BETALINGSVILJE FOR DIGITALE NYHETER},
author = {Erik Knudsen and Hallvard Moe},
url = {https://app.cristin.no/results/show.jsf?id=1958452, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {techreport}
}
Samia Touileb; Lilja Øvrelid; Erik Velldal
Using Gender- and Polarity-informed Models to Investigate Bias Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1958571,
title = {Using Gender- and Polarity-informed Models to Investigate Bias},
author = {Samia Touileb and Lilja Øvrelid and Erik Velldal},
url = {https://app.cristin.no/results/show.jsf?id=1958571, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Mehdi Elahi; Øyvind Johannessen
Novel Methods Using Human Emotion and Visual Features for Recommending Movies Masters Thesis
Universitetet i Bergen, 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@mastersthesis{cristin1957008,
title = {Novel Methods Using Human Emotion and Visual Features for Recommending Movies},
author = {Mehdi Elahi and Øyvind Johannessen},
url = {https://app.cristin.no/results/show.jsf?id=1957008, Cristin},
year = {2021},
date = {2021-01-01},
school = {Universitetet i Bergen},
abstract = {This master thesis investigates novel methods using human emotion as contextual information to estimate and elicit ratings when watching movie trailers. The aim is to acquire user preferences without the intrusive and time-consuming behavior of Explicit Feedback strategies, and generate quality recommendations. The proposed preference-elicitation technique is implemented as an Emotion-based Filtering technique (EF) to generate recommendations, and is evaluated against two other recommendation techniques. One Visual-based Filtering technique, using low-level visual features of movies, and one Collaborative Filtering (CF) using explicit ratings. In terms of Accuracy, we found the Emotion-based Filtering technique (EF) to perform better than the two other filtering techniques. In terms of Diversity, the Visual-based Filtering (VF) performed best. We further analyse the obtained data to see if movie genres tend to induce specific emotions, and the potential correlation between emotional responses of users and visual features of movie trailers. When investigating emotional responses, we found that joy and disgust tend to be more prominent in movie genres than other emotions. Our findings also suggest potential correlations on a per movie level. The proposed Emotion-based Filtering technique can be adopted as an Implicit Feedback strategy to obtain user preferences. For future work, we will extend the experiment with more participants and build stronger affective profiles to be studied when recommending movies.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {mastersthesis}
}
Ingar M Arntzen; Njål Borch; Anders Andersen
Unify Media and UX with timed variables Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1959749,
title = {Unify Media and UX with timed variables},
author = {Ingar M Arntzen and Njål Borch and Anders Andersen},
url = {https://app.cristin.no/results/show.jsf?id=1959749, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Mehdi Elahi; Tord Kvifte
Video Recommendations Based on Visual Features Extracted with Deep Learning Masters Thesis
Universitetet i Bergen, 2021.
Abstract | BibTeX | Tags: Cristin | Links:
@mastersthesis{cristin1956990,
title = {Video Recommendations Based on Visual Features Extracted with Deep Learning},
author = {Mehdi Elahi and Tord Kvifte},
url = {https://app.cristin.no/results/show.jsf?id=1956990, Cristin
https://hdl.handle.net/11250/2760300},
year = {2021},
date = {2021-01-01},
school = {Universitetet i Bergen},
abstract = {When a movie is uploaded to a movie Recommender System (e.g., YouTube), the system can exploit various forms of descriptive features (e.g., tags and genre) in order to generate personalized recommendation for users. However, there are situations where the descriptive features are missing or very limited and the system may fail to include such a movie in the recommendation list, known as Cold-start problem. This thesis investigates recommendation based on a novel form of content features, extracted from movies, in order to generate recommendation for users. Such features represent the visual aspects of movies, based on Deep Learning models, and hence, do not require any human annotation when extracted. The proposed technique has been evaluated in both offline and online evaluations using a large dataset of movies. The online evaluation has been carried out in a evaluation framework developed for this thesis. Results from the offline and online evaluation (N=150) show that automatically extracted visual features can mitigate the cold-start problem by generating recommendation with a superior quality compared to different baselines, including recommendation based on human-annotated features. The results also point to subtitles as a high-quality future source of automatically extracted features. The visual feature dataset, named DeepCineProp13K and the subtitle dataset, CineSub3K, as well as the proposed evaluation framework are all made openly available online in a designated Github repository.},
keywords = {Cristin},
pubstate = {published},
tppubtype = {mastersthesis}
}
Mehdi Elahi; Himan Abdollahpouri; Masoud Mansoury; Helma Torkamaan
Beyond Algorithmic Fairness in Recommender System Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957035,
title = {Beyond Algorithmic Fairness in Recommender System},
author = {Mehdi Elahi and Himan Abdollahpouri and Masoud Mansoury and Helma Torkamaan},
url = {https://app.cristin.no/results/show.jsf?id=1957035, Cristin
https://dl.acm.org/doi/abs/10.1145/3450614.3461685},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Mehdi Elahi; Farshad Bakhshandegan Moghaddam; Reza Hosseini; Mohammad Hossein Rimaz; Christoph Trattner
Enhanced Movie Recommendation Incorporating Visual Features Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957034,
title = {Enhanced Movie Recommendation Incorporating Visual Features},
author = {Mehdi Elahi and Farshad Bakhshandegan Moghaddam and Reza Hosseini and Mohammad Hossein Rimaz and Christoph Trattner},
url = {https://app.cristin.no/results/show.jsf?id=1957034, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Erik Knudsen
Medieundersøkelsen 2021: Har koronadekningen svekket tilliten til mediene? Presentation
Nordiske Mediedager 2021, 01.01.2021.
BibTeX | Tags: Cristin | Links:
@misc{cristin1957213,
title = {Medieundersøkelsen 2021: Har koronadekningen svekket tilliten til mediene?},
author = {Erik Knudsen},
url = {https://app.cristin.no/results/show.jsf?id=1957213, Cristin
https://www.nordiskemediedager.no/medieundersoekelsen/medieundersoekelsen/},
year = {2021},
date = {2021-01-01},
howpublished = {Nordiske Mediedager 2021},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
Erik Knudsen
The Promise and Perils of Algorithmic News Recommenders' Influence on Democracy Presentation
TEDxBergen2021, 01.01.2021.
BibTeX | Tags: Cristin | Links:
@misc{cristin1957207,
title = {The Promise and Perils of Algorithmic News Recommenders' Influence on Democracy},
author = {Erik Knudsen},
url = {https://app.cristin.no/results/show.jsf?id=1957207, Cristin
https://youtu.be/B3qHJC5LwJQ},
year = {2021},
date = {2021-01-01},
howpublished = {TEDxBergen2021},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
Erik Knudsen
How can news sites personalize audiences's news experiences without making audiences more polarized and fragmented? Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957727,
title = {How can news sites personalize audiences's news experiences without making audiences more polarized and fragmented? },
author = {Erik Knudsen},
url = {https://app.cristin.no/results/show.jsf?id=1957727, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
John Magnus Ragnhildson Dahl
What can TV companies do for teenagers who are on their phone all the time? Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957717,
title = {What can TV companies do for teenagers who are on their phone all the time?},
author = {John Magnus Ragnhildson Dahl},
url = {https://app.cristin.no/results/show.jsf?id=1957717, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Ana Milojevic
Datafication, Media and Democracy: Transformation of news work in datafied society Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957739,
title = {Datafication, Media and Democracy: Transformation of news work in datafied society},
author = {Ana Milojevic},
url = {https://app.cristin.no/results/show.jsf?id=1957739, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Marianne Borchgrevink-Brækhus
Why won't young people pay for news? Working paper
2021.
BibTeX | Tags: Cristin | Links:
@workingpaper{cristin1957735,
title = {Why won't young people pay for news?},
author = {Marianne Borchgrevink-Brækhus},
url = {https://app.cristin.no/results/show.jsf?id=1957735, Cristin},
year = {2021},
date = {2021-01-01},
keywords = {Cristin},
pubstate = {published},
tppubtype = {workingpaper}
}
Lars Nyre; Bjørnar Tessem
Kva datamaskiner kan gjere Medium
Dag og Tid, 2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1957728,
title = {Kva datamaskiner kan gjere},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1957728, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Hallvard Moe
Fake news og mediebruk Presentation
Vestlandsseminaret, 01.01.2021.
BibTeX | Tags: Cristin | Links:
@misc{cristin1957718,
title = {Fake news og mediebruk},
author = {Hallvard Moe},
url = {https://app.cristin.no/results/show.jsf?id=1957718, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Vestlandsseminaret},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
Sarah Ljungblad; Yemao Man; Mehmet Aydın Baytaş; Mafalda Gamboa; Morten Fjeld; Mohammad Obaid
What Matters in Professional Drone Pilots’ Practice? An Interview Study to Understand the Complexity of Their Work and Inform Human-Drone Interaction Research Proceedings
ACM CHI on human factors in computing systems conference proceeding, 2021.
BibTeX | Tags: Cristin | Links:
@proceedings{cristin2003885,
title = {What Matters in Professional Drone Pilots’ Practice? An Interview Study to Understand the Complexity of Their Work and Inform Human-Drone Interaction Research},
author = {Sarah Ljungblad and Yemao Man and Mehmet Aydın Baytaş and Mafalda Gamboa and Morten Fjeld and Mohammad Obaid},
url = {https://app.cristin.no/results/show.jsf?id=2003885, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {ACM CHI on human factors in computing systems conference proceeding},
keywords = {Cristin},
pubstate = {published},
tppubtype = {proceedings}
}
Lars Nyre; Bjørnar Tessem
Kvifor Google-briller vart ein fiasko Medium
Dag og Tid, 2021.
BibTeX | Tags: Cristin | Links:
@media{cristin1942262,
title = {Kvifor Google-briller vart ein fiasko},
author = {Lars Nyre and Bjørnar Tessem},
url = {https://app.cristin.no/results/show.jsf?id=1942262, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {Dag og Tid},
keywords = {Cristin},
pubstate = {published},
tppubtype = {media}
}
Bjørnar Tessem; Andreas L. Opdahl
Content Analysis and Production Presentation
MediaFutures Annual Meeting 2021, 01.01.2021.
BibTeX | Tags: Cristin | Links:
@misc{cristin1942264,
title = {Content Analysis and Production},
author = {Bjørnar Tessem and Andreas L. Opdahl},
url = {https://app.cristin.no/results/show.jsf?id=1942264, Cristin},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
howpublished = {MediaFutures Annual Meeting 2021},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}
Erik Knudsen; Åsta Dyrnes Nordø; Magnus Hoem Iversen
The Effect of the COVID-19 Pandemic Crisis on Trust in the News Media: Evidence From Three Panel Waves With a Pre-Crisis Baseline Erik Knudsen Presentation
71st Annual ICA Conference, 01.01.2021.
BibTeX | Tags: Cristin | Links:
@misc{cristin1957204,
title = {The Effect of the COVID-19 Pandemic Crisis on Trust in the News Media: Evidence From Three Panel Waves With a Pre-Crisis Baseline Erik Knudsen},
author = {Erik Knudsen and Åsta Dyrnes Nordø and Magnus Hoem Iversen},
url = {https://app.cristin.no/results/show.jsf?id=1957204, Cristin},
year = {2021},
date = {2021-01-01},
howpublished = {71st Annual ICA Conference},
keywords = {Cristin},
pubstate = {published},
tppubtype = {presentation}
}