Publications

@inproceedings{	20.500.12708_58724,

title = {Semantische Netzwerke als Hilfsmittel für die Untersuchung des Begriffskomplexes Arbeit-Lohn-Vermögen im öffentlichen Diskurs Österreichs},

author = {Klaus Hofmann and Andreas Baumann and Anna Marakasova and Julia Neidhardt and Tanja Wissik},

year  = {2021},

date = {2021-01-01},

booktitle = {Momentum 2021 Kongress},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_55667,

title = {Exploring Causal Relationships Among Emotional and Topical Trajectories in Political Text Data},

author = {Andreas Baumann and Klaus Hofmann and Bettina Kern and Anna Marakasova and Julia Neidhardt and Tanja Wissik},

doi = {10.4230/OASIcs.LDK.2021.38},

isbn = {978-3-95977-199-3},

year  = {2021},

date = {2021-01-01},

booktitle = {3rd Conference on Language, Data and Knowledge (LDK 2021)},

pages = {1–8},

publisher = {OASICS},

address = {93},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_55666,

title = {A review and cluster analysis of German polarity resources for sentiment analysis},

author = {Bettina Kern and Andreas Baumann and Thomas Kolb and Katharina Sekanina and Klaus Hofmann and Tanja Wissik and Julia Neidhardt},

doi = {10.4230/OASIcs.LDK.2021.37},

isbn = {978-3-95977-199-3},

year  = {2021},

date = {2021-01-01},

booktitle = {3rd Conference on Language, Data and Knowledge (LDK 2021)},

pages = {1–17},

publisher = {OASICS},

address = {93},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_58755,

title = {Modeling Users and Items for Recommenders:There Is More than Semantics},

author = {Mete Sertkan},

doi = {10.1145/3460231.3473898},

year  = {2021},

date = {2021-01-01},

booktitle = {Fifteenth ACM Conference on Recommender Systems},

publisher = {ACM},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zia2021step,

title = {A step towards improving knowledge tracing},

author = {Aayesha Zia and Jalal Nouri and Muhammad Afzaal and Yongchao Wu and Xiu Li and Rebecka Weegar},

year  = {2021},

date = {2021-01-01},

booktitle = {2021 International Conference on Advanced Learning Technologies (ICALT)},

pages = {38–39},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{zia2021ensemble,

title = {An ensemble approach for question-level knowledge tracing},

author = {Aayesha Zia and Jalal Nouri and Muhammad Afzaal and Yongchao Wu and Xiu Li and Rebecka Weegar},

year  = {2021},

date = {2021-01-01},

booktitle = {International Conference on Artificial Intelligence in Education},

pages = {433–437},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{afzaal2021generation,

title = {Generation of automatic data-driven feedback to students using Explainable Machine Learning},

author = {Muhammad Afzaal and Jalal Nouri and Aayesha Zia and Panagiotis Papapetrou and Uno Fors and Yongchao Wu and Xiu Li and Rebecka Weegar},

year  = {2021},

date = {2021-01-01},

booktitle = {International Conference on Artificial Intelligence in Education},

pages = {37–42},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{afzaal2021automatic,

title = {Automatic and intelligent recommendations to support students’ self-regulation},

author = {Muhammad Afzaal and Jalal Nouri and Aayesha Zia and Panagiotis Papapetrou and Uno Fors and Yongchao Wu and Xiu Li and Rebecka Weegar},

year  = {2021},

date = {2021-01-01},

booktitle = {2021 International Conference on Advanced Learning Technologies (ICALT)},

pages = {336–338},

organization = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{wu2021word,

title = {A word embeddings based clustering approach for collaborative learning group formation},

author = {Yongchao Wu and Jalal Nouri and Xiu Li and Rebecka Weegar and Muhammad Afzaal and Aayesha Zia},

year  = {2021},

date = {2021-01-01},

booktitle = {International Conference on Artificial Intelligence in Education},

pages = {395–400},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{wu2021catching,

title = {Catching Group Criteria Semantic Information When Forming Collaborative Learning Groups},

author = {Yongchao Wu and Jalal Nouri and Xiu Li and Rebecka Weegar and Muhammad Afzaal and Aayesha Zia},

year  = {2021},

date = {2021-01-01},

booktitle = {Technology-Enhanced Learning for a Free, Safe, and Sustainable World: 16th European Conference on Technology Enhanced Learning, EC-TEL 2021, Bolzano, Italy, September 20-24, 2021, Proceedings 16},

pages = {16–27},

organization = {Springer},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_58393,

title = {Comparing Lexical Usage in Political Discourse across Diachronic Corpora.},

author = {Klaus Hofmann and Anna Marakasova and Andreas Baumann and Julia Neidhardt and Tanja Wissik},

year  = {2020},

date = {2020-01-01},

booktitle = {Proceedings of the Second ParlaCLARIN Workshop. Language Resources and Evaluation Conference (LREC 2020), Marseille, 11-16 May 2020.},

pages = {58–65},

publisher = {ACL Anthology},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_58382,

title = {Eliciting Touristic Profiles: A User Study on Picture Collections},

author = {Mete Sertkan and Julia Neidhardt and Hannes Werthner},

editor = {Tsvi Kuflik and Ilaria Torre and Robin Burke and Cristina Gena},

doi = {10.1145/3340631.3394868},

year  = {2020},

date = {2020-01-01},

booktitle = {Proceedings of the 28th ACM Conference on User Modeling, Adaptation and Personalization},

publisher = {Association for Computing Machinery, New York, NY, USA},

abstract = {Eliciting the preferences and needs of tourists is challenging, since people often have difficulties to explicitly express them, especially in the initial phase of travel planning. Recommender systems employed at the early stage of planning can therefore be very beneficial to the general satisfaction of a user. Previous studies have explored pictures as a tool of communication and as a way to implicitly deduce a traveller's preferences and needs. In this paper, we conduct a user study to verify previous claims and conceptual work on the feasibility of modelling travel interests from a selection of a user's pictures. We utilize fine-tuned convolutional neural networks to compute a vector representation of a picture, where each dimension corresponds to a travel behavioural pattern from the traditional Seven-Factor model. In our study, we followed strict privacy principles and did not save uploaded pictures after computing their vector representation. We aggregate the representations of the pictures of a user into a single user representation, ie, touristic profile, using different strategies. In our user study with 81 participants, we let users adjust the predicted touristic profile and confirm the usefulness of our approach. Our results show that given a collection of pictures the touristic profile of a user can be determined.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_58381,

title = {From Pictures to Travel Characteristics: Deep Learning-Based Profiling of Tourists and Tourism Destinations},

author = {Mete Sertkan and Julia Neidhardt and Hannes Werthner},

editor = {Julia Neidhardt and Wolfgang Wörndl},

doi = {10.1007/978-3-030-36737-4_12},

isbn = {9783030367374},

year  = {2020},

date = {2020-01-01},

booktitle = {Information and Communication Technologies in Tourism 2020},

pages = {142–153},

publisher = {Springer},

abstract = {Tourism products are complex and strongly tied to emotions. Thus, it is not easy for consumers to explicitly communicate their travel preferences, needs, and interest, especially in the early phase of travel decision making. In the spirit of the idiom "A picture is worth a thousand words" we utilize pictures to characterize tourists as well as tourism destinations in order to build the foundations of a recommender system (RS). In this work all entities (i.e., users and items) are characterized using the Seven-Factor Model. Pre-labelled pictures are used in order to train convolutional neural networks (CNN) in a transfer learning manner with the goal to extract the Seven-Factors of a given picture. We demonstrate that touristic characteristics can be extracted out of pictures. Furthermore, we show that those characteristics can be aggregated for a collection of pictures, such that a representation of a user or a destination can be determined respectively.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_58385,

title = {PicTouRe - A Picture-Based Tourism Recommender},

author = {Mete Sertkan and Julia Neidhardt and Hannes Werthner},

doi = {10.1145/3383313.3411526},

year  = {2020},

date = {2020-01-01},

booktitle = {Fourteenth ACM Conference on Recommender Systems},

publisher = {Association for Computing Machinery, New York, United States},

abstract = {We present PicTouRe-a picture-based tourism recommender. PicTouRe aims to mitigate people´s difficulties in explicitly expressing their touristic preferences, which is even more challenging in the initial phase of travel decision making. Addressing this issue, with PicTouRe we follow the idiom "a picture is worth a thousand words" and use pictures as a tool to implicitly elicit peoples´ touristic preferences. We describe the core concept of PicTouRe-the Generic Profiler, which in essence determines an explainable vector representation, ie, touristic profile, given any picture collection as input. We showcase a user´s journey through PicTouRe and describe the steps behind. Finally, we present results of a first user study supporting our approach. PicTouRe is available under https://pictoprof. ec. tuwien. ac. at and a demo video under https://youtu. be/xZnXLPcenEs.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{	20.500.12708_55595,

title = {Short-term Semantic Shifts and their Relation to Frequency Change},

author = {Anna Marakasova and Julia Neidhardt},

year  = {2020},

date = {2020-01-01},

booktitle = {Proceedings of the Probability and Meaning Conference (PaM 2020)},

pages = {146–153},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}