Marko Tkalčič
Publications
Link to my Google
Scholar Profile. If you are further interested in my work, please
download my CV.
Journal Papers
- J16
-
Motamedi, E., Barile, F., & Tkalčič, M. (2022).
Prediction of Eudaimonic and Hedonic Orientation of Movie Watchers.
Applied Sciences, 12(19), 9500. https://doi.org/10.3390/app12199500
- J15
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Elahi, M., Kholgh, D. K., Kiarostami, M. S., Saghari, S., Rad, S. P.,
& Tkalčič, M. (2021). Investigating the impact of
recommender systems on user-based and item-based popularity bias.
Information Processing & Management, 58(5), 102655.
https://doi.org/10.1016/j.ipm.2021.102655
- J14
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Pesek, M., Medvešek, Š., Podlesek, A., Tkalčič, M.,
& Marolt, M. (2020). A Comparison of Human and Computational Melody
Prediction Through Familiarity and Expertise. Frontiers in Psychology,
11(December), 1–18. https://doi.org/10.3389/fpsyg.2020.557398
- J13
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Ferwerda, B., Yang, E., Schedl, M., and Tkalčič, M.,
(2019). Personality and taxonomy preferences, and the influence of
category choice on the user experience for music streaming services.
Multimedia Tools and Applications.
https://doi.org/10.1007/s11042-019-7336-7
- J12
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Schedl, M., Gomez, E., Trent, E., Tkalčič, M.,
Eghbal-Zadeh, H., & Martorell, A. (2017). On the Interrelation
between Listener Characteristics and the Perception of Emotions in
Classical Orchestra Music. IEEE Transactions on Affective Computing,
1–1. https://doi.org/10.1109/TAFFC.2017.2663421
- J11
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Vodlan, T., Tkalčič, M., & Košir, A. (2015). The
impact of hesitation, a social signal, on a user’s quality of experience
in multimedia content retrieval. Multimedia Tools and Applications,
74(17), 6871–6896. https://doi.org/10.1007/s11042-014-1933-2
- J10
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Tkalčič, M., Odić, A., Košir, A., & Tasič, J.
(2013). Affective labeling in a content-based recommender system for
images. IEEE Transactions on Multimedia, 15(2), 391–400.
https://doi.org/10.1109/TMM.2012.2229970
- J9
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Odić, A., Tkalčič, M., Tasič, J. F., & Košir, A.
(2013). Predicting and Detecting the Relevant Contextual Information in
a Movie-Recommender System. Interacting with Computers, 25(1), 74–90.
https://doi.org/10.1093/iwc/iws003
- J8
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Tkalčič, M., Košir, A., & Tasič, J. (2013). The
LDOS-PerAff-1 corpus of facial-expression video clips with affective,
personality and user-interaction metadata. Journal on Multimodal User
Interfaces, 7(1–2), 143–155. https://doi.org/10.1007/s12193-012-0107-7
- J7
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Odić, A., Tkalčič, M., Tasič, J. F., & Košir, A.
(2013). Impact of the Context Relevancy on Ratings Prediction in a
Movie-Recommender System. Automatika ‒ Journal for Control, Measurement,
Electronics, Computing and Communications, 54(2), 252–262.
https://doi.org/10.7305/automatika.54-2.258
- J6
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Tkalčič, M., Odić, A., & Košir, A. (2013). The
impact of weak ground truth and facial expressiveness on affect
detection accuracy from time-continuous videos of facial expressions.
Information Sciences, 249, 13–23.
https://doi.org/10.1016/j.ins.2013.06.006
- J5
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Tkalčič, M., Košir, A., Dobravec, Š., & Tasič, J.
(2011). Emotional properties of latent factors in an image recommender
system. Elektrotehniški Vestnik, 78(4), 177–180. Retrieved from
http://ev.fe.uni-lj.si/4-2011/Tkalčič.pdf
- J4
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Košir, A., Odić, A., Kunaver, M., Tkalčič, M., &
Tasič, J. F. (2011). Database for contextual personalization.
Elektrotehniški Vestnik, 78(5), 270–274. Retrieved from
http://ev.fe.uni-lj.si/5-2011/Kosir.pdf
- J3
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Tkalčič, M., Kosir, A., & Tasic, J. (2011). Usage
of affective computing in recommender systems. Elektrotehniski
Vestnik/Electrotechnical Review, 78(1–2), 12–17. Retrieved from
http://ev.fe.uni-lj.si/1-2-2011/Tkalčič.pdf
- J2
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Tkalčič, M., Burnik, U., & Košir, A. (2010). Using
affective parameters in a content-based recommender system for images.
User Modelling and User-Adapted Interaction, 20(4), 279–311.
https://doi.org/10.1007/s11257-010-9079-z
- J1
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Grbec, S., Tkalčič, M., & Diaci, J. (2008). The
influence of inertial loading on color gamut properties of a TFT LCD
display. Displays, 29(1), 18–24.
https://doi.org/10.1016/j.displa.2007.06.008
Conference Papers
- C36
-
Motamedi, E., Tkalcic, M., & Szlávik, Z. (2023). Eudaimonic and
Hedonic Qualities as Predictors of Music Videos’ Relevance to Users: A
Human-Centric Study. Adjunct Proceedings of the 31st ACM Conference on
User Modeling, Adaptation and Personalization, 44–49.
https://doi.org/10.1145/3563359.3597415
- C35
-
Ferwerda, B., Kiunsi, D. R., & Tkalčič, M. (2022). Too Much of a
Good Thing: When In-Car Driver Assistance Notifications Become Too Much.
14th International Conference on Automotive User Interfaces and
Interactive Vehicular Applications, 79–82.
https://doi.org/10.1145/3544999.3552536
- C34
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Tkalčič, M., Motamedi, E., Barile, F., Puc, E., & Mars Bitenc, U.
(2022). Prediction of Hedonic and Eudaimonic Characteristics from User
Interactions. Adjunct Proceedings of the 30th ACM Conference on User
Modeling, Adaptation and Personalization, 366–370.
https://doi.org/10.1145/3511047.3537656
- C33
-
Reiter-Haas, M., Parada-Cabaleiro, E., Schedl, M., Motamedi, E.,
Tkalcic, M., & Lex, E. (2021). Predicting Music
Relistening Behavior Using the ACT-R Framework. Fifteenth ACM Conference
on Recommender Systems, 702–707. https://doi.org/10.1145/3460231.3478846
- C32
-
Najafian, S., Delic, A., Tkalcic, M., & Tintarev,
N. (2021). Factors Influencing Privacy Concern for Explanations of Group
Recommendation. Proceedings of the 29th ACM Conference on User Modeling,
Adaptation and Personalization, 14–23.
https://doi.org/10.1145/3450613.3456845
- C31
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Elahi, M., Bakhshandegan Moghaddam, F., Hosseini, R., Rimaz, M. H., El
Ioini, N., Tkalcic, M., Trattner, C., & Tillo, T.
(2021). Recommending Videos in Cold Start With Automatic Visual Tags.
Adjunct Proceedings of the 29th ACM Conference on User Modeling,
Adaptation and Personalization, 54–60.
https://doi.org/10.1145/3450614.3461687
- C30
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Najafian, S., Draws, T., Barile, F., Tkalcic, M., Yang,
J., & Tintarev, N. (2021). Exploring User Concerns about Disclosing
Location and Emotion Information in Group Recommendations. Proceedings
of the 32st ACM Conference on Hypertext and Social Media, 155–164.
https://doi.org/10.1145/3465336.3475104
- C29
-
Ferwerda, B., & Tkalčič, M. (2020). Exploring the
Prediction of Personality Traits from Drug Consumption Profiles. Adjunct
Publication of the 28th ACM Conference on User Modeling, Adaptation and
Personalization, 2–5. https://doi.org/10.1145/3386392.3397589
- C28
-
Barile, F., Ricci, F., Tkalcic, M., Magnini, B.,
Zanoli, R., Lavelli, A., & Speranza, M. (2019). A News Recommender
System for Media Monitoring. Web Intelligence 2019.
https://doi.org/10.1145/3350546.3352510
- C27
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Rimaz, M. H., Elahi, M., Moghadam, F., Trattner, C., Hosseini, R., &
Tkalčič, M. (2019). Exploring the Power of Visual
Features for Recommendation of Movies. UMAP 2019.
https://doi.org/10.1145/3320435.3320470
- C26
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Ferwerda, B., & Tkalčič, M. (2019). Exploring
Online Music Listening Behaviors of Musically Sophisticated Users. UMAP
2019, 1–5. https://doi.org/10.1145/3314183.3324974
- C25
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Tkalčič, M., Maleki, N., Pesek, M., Elahi, M., Ricci,
F., & Marolt, M. (2019). Prediction of music pairwise preferences
from facial expressions. In Proceedings of the 24th International
Conference on Intelligent User Interfaces - IUI ’19 (pp. 150–159). New
York, New York, USA: ACM Press. https://doi.org/10.1145/3301275.3302266
- C24
-
Ferwerda, B., Tkalčič, M., Predicting Users’
Personality from Instagram Pictures: Using Visual and/or Content
Features?, In UMAP ’18: 26th Conference on User Modeling, Adaptation and
Personalization, July 8–11, 2018, Singapore, Singapore. ACM.
- C23
-
Tkalčič, M., & Ferwerda, B. (2018). Eudaimonic
Modeling of Moviegoers. In UMAP ’18: 26th Conference on User Modeling,
Adaptation and Personalization, July 8–11, 2018, Singapore, Singapore.
ACM. https://doi.org/10.1145/3209219.3209249
- C22
-
Ferwerda, B., Tkalčič, M., & Schedl, M. (2017).
Personality Traits and Music Genres. In Proceedings of the 25th
Conference on User Modeling, Adaptation and Personalization - UMAP ’17
(pp. 285–288). New York, New York, USA: ACM Press.
https://doi.org/10.1145/3079628.3079693
- C21
-
Ferwerda, B., Graus, M. P., Vall, A., Tkalčič, M.,
& Schedl, M. (2017). How item discovery enabled by diversity leads
to increased recommendation list attractiveness. In Proceedings of the
Symposium on Applied Computing - SAC ’17 (pp. 1693–1696). New York, New
York, USA: ACM Press. https://doi.org/10.1145/3019612.3019899
- C20
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Ferwerda, B., Schedl, M., & Tkalčič, M. (2016).
Personality Traits and the Relationship with ( Non- ) Disclosure
Behavior on Facebook. WWW’16 Companion.
https://doi.org/10.1145/2872518.2890085
- C19
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Ferwerda, B., Schedl, M., & Tkalčič, M. (2016).
Using Instagram Picture Features to Predict Users’ Personality. In Q.
Tian, N. Sebe, G.-J. Qi, B. Huet, R. Hong, & X. Liu (Eds.),
Multimedia Modeling (22nd International Conference, MMM 2016, Miami, FL,
USA, January 4-6, 2016, Proceedings, Part I) (Vol. 9516, pp. 850–861).
Cham: Springer International Publishing.
https://doi.org/10.1007/978-3-319-27671-7_71
- C18
-
Schedl, M., Hauger, D., Tkalčič, M., Melenhorst, M.,
& Liem, C. C. S. (2016). A dataset of multimedia material about
classical music: PHENICX-SMM. In 2016 14th International Workshop on
Content-Based Multimedia Indexing (CBMI) (pp. 1–4). IEEE.
https://doi.org/10.1109/CBMI.2016.7500240
- C17
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Kalloori, S., Ricci, F., & Tkalčič, M., (2016).
Pairwise Preferences Based Matrix Factorization and Nearest Neighbor
Recommendation Techniques. Proceedings of the 10th ACM Conference on
Recommender Systems - RecSys ’16, 143–146.
https://doi.org/10.1145/2959100.2959142
- C16
-
Schedl, M., Eghbal-zadeh, H., Gomez, E., & Tkalčič,
M. (2016). An Analysis of Agreement in Classical Music
Perception and its Relationship to Listener Characteristics. In
Proceedings of the 17th ISMIR Conference, New York City, USA, August
7-11, 2016 (pp. 578–583).
- C15
-
Ferwerda, B., Vall, A., Tkalčič, M., & Schedl, M.
(2016). Exploring Music Diversity Needs Across Countries. In Proceedings
of the 2016 Conference on User Modeling Adaptation and Personalization -
UMAP ’16 (pp. 287–288). New York, New York, USA: ACM Press.
https://doi.org/10.1145/2930238.2930262
- C14
-
Skowron, M., Ferwerda, B., Tkalčič, M., & Schedl,
M. (2016). Fusing Social Media Cues : Personality Prediction from
Twitter and Instagram. WWW’16 Companion, 2–3.
https://doi.org/10.1145/2872518.2889368
- C13
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Motajcsek, T., Dobrajs, K., Garzotto, F., Göker, A., Hopfgartner, F.,
Malagoli, D., Tkalčič, M., … Demetriou, A. (2016).
Algorithms Aside. In Proceedings of the 10th ACM Conference on
Recommender Systems - RecSys ’16 (pp. 215–219). New York, New York, USA:
ACM Press. https://doi.org/10.1145/2959100.2959164
- C12
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Schedl, M., Melenhorst, M., Liem, C. C. S., Martorell, A., Mayor, Ó.,
Tkalčič, M., (2016). A Personality-based Adaptive
System for Visualizing Classical Music Performances. In Proceedings of
the 7th International Conference on Multimedia Systems - MMSys ’16
(pp. 1–7). New York, New York, USA: ACM Press.
https://doi.org/10.1145/2910017.2910604
- C11
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Tkalčič, M., Ferwerda, B., Hauger, D., & Schedl, M.
(2015). Personality Correlates for Digital Concert Program Notes. In
UMAP 2015, Lecture Notes On Computer Science 9146 (Vol. 9146,
pp. 364–369). https://doi.org/10.1007/978-3-319-20267-9_32
- C10
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Ferwerda, B., Yang, E., Schedl, M., & Tkalčič, M.
(2015). Personality Traits Predict Music Taxonomy Preferences. In
Proceedings of the 33rd Annual ACM Conference Extended Abstracts on
Human Factors in Computing Systems - CHI EA ’15 (pp. 2241–2246).
https://doi.org/10.1145/2702613.2732754
- C9
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Schedl, M., Hauger, D., Farrahi, K., & Tkalčič, M.
(2015). On the Influence of User Characteristics on Music Recommendation
Algorithms. In A. Hanbury, G. Kazai, A. Rauber, & N. Fuhr (Eds.),
ECIR 2016, Advances in Information Retrieval Lecture Notes in Computer
Science (Vol. 9022, pp. 339–345). Springer.
https://doi.org/10.1007/978-3-319-16354-3_37
- C8
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Ferwerda, B., Schedl, M., & Tkalčič, M. (2015).
Personality & Emotional States : Understanding Users ’ Music
Listening Needs. In A. Cristea, J. Masthoff, A. Said, & N. Tintarev
(Eds.), UMAP 2015 Extended Proceedings. Retrieved from
http://ceur-ws.org/Vol-1388/
- C7
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Farrahi, K., Schedl, M., Vall, A., Hauger, D., & Tkalčič,
M. (2014). Impact of Listening Behavior on Music
Recommendation. In ISMIR 2014. Retrieved from
http://www.cp.jku.at/people/schedl/Research/Publications/pdf/farrahi_ismir_2014.pdf
- C6
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Ferwerda, B., Schedl, M., & Tkalčič, M. (2014). To
Post or Not to Post : The Effects of Persuasive Cues and Group Targeting
Mechanisms on Posting Behavior. In 2014 ASE
BIGDATA/SOCIALCOM/CYBERSECURITY Conference, Stanford University, May
27-31, 2014. Retrieved from
http://www.cp.jku.at/research/papers/Ferwerda_etal_SocialCom_2014.pdf
- C5
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Elahi, M., Braunhofer, M., Ricci, F., & Tkalčič, M.
(2013). Personality-based active learning for collaborative filtering
recommender systems. In M. Baldoni, C. Baroglio, G. Boella, & O.
Micalizio (Eds.), AIxIA 2013: Advances in Artificial Intelligence
(pp. 360–371). https://doi.org/10.1007/978-3-319-03524-6_31
- C4
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Hauger, D., Schedl, M., Košir, A., & Tkalčič, M.
(2013). The Million Musical Tweet Dataset: What We Can Learn From
Microblogs. In ISMIR 2013. Retrieved from
http://www.cp.jku.at/people/schedl/Research/Publications/pdf/hauger_ismir_2013.pdf
- C3
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Tkalčič, M., Burnik, U., Odić, A., Košir, A., &
Tasič, J. F. (2013). Emotion-Aware Recommender Systems—A Framework and a
Case Study. In S. Markovski & M. Gusev (Eds.), ICT Innovations 2012
Advances in Intelligent Systems and Computing (Vol. 207, pp. 141–150).
Berlin, Heidelberg: Springer Berlin Heidelberg.
https://doi.org/10.1007/978-3-642-37169-1_14
- C2
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Tkalčič, M., Odić, A., Košir, A., & Tasič, J.
(2012). Exploiting implicit affective labeling for image
recommendations. In J. Wang, J. del R. Millán, & S. Cho (Eds.),
Conference Proceedings - IEEE International Conference on Systems, Man
and Cybernetics (pp. 3321–3326).
https://doi.org/10.1109/ICSMC.2012.6378304
- C1
-
Tkalčič, M., & Tasic, J. F. (2003). Colour spaces:
perceptual, historical and applicational background. In B. Zajc & M.
Tkalčič (Eds.), The IEEE Region 8 EUROCON 2003. Computer as a Tool.
(Vol. 1, pp. 304–308). Proceedings of the IEEE Region 8 EUROCON 2003.
Computer as a Tool. https://doi.org/10.1109/EURCON.2003.1248032
Demos
- D2
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Tkalčič, M., Maleki, N., Pesek, M., Elahi, M., Ricci,
F., & Pesek, M. (n.d.). A Research Tool for User Preferences
Elicitation with Facial Expressions. In ACM RecSys 2017 Demo (pp. 1–2).
https://doi.org/10.1145/3109859.3109978
- D1
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Tkalčič, M., Schedl, M., Liem, C. C. S. S., &
Melenhorst, M. S. (2016). Personalized Retrieval and Browsing of
Classical Music and Supporting Multimedia Material. In Proceedings of
the 2016 ACM on International Conference on Multimedia Retrieval - ICMR
’16 (pp. 393–396). New York, New York, USA: ACM Press.
https://doi.org/10.1145/2911996.2912023
Workshop Papers
- W23
-
Barile, F., Ricci, F., Tkalcic, M., Magnini, B.,
Zanoli, R., Lavelli, A., & Speranza, M. (2019). Media Monitoring
using News Recommenders. IIR 2019, September 16–18, 2019, Padova, Italy.
- W22
-
Moghaddam, F. B., Elahi, M., Hosseini, R., Trattner, C., &
Tkalcic, M. (2019). Predicting Movie Popularity and
Ratings with Visual Features. 2019 14th International Workshop on
Semantic and Social Media Adaptation and Personalization (SMAP), 1–6.
https://doi.org/10.1109/SMAP.2019.8864912
- W21
-
Tkalcic, M., & Ferwerda, B. (2018). Theory-driven
Recommendations : Modeling Hedonic and Eudaimonic Movie Preferences. In
N. Tonellotto, L. Becchetti, & M. Tkalcic (Eds.), Proceedings of the
9th Italian Information Retrieval Workshop (pp. 1–5).
- W20
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Ferwerda, B., & Tkalčič, M. (2018). You Are What
You Post : What the Content of Instagram Pictures Tells About Users ’
Personality. In Joint Proceedings of the ACM IUI 2018 Workshops.
- W19
-
Ferwerda, B., Tkalčič, M., & Schedl, M. (2017).
Personality Traits and Music Genre Preferences: How Music Taste Vary
Over Age Groups. In RecTemp Workshop in conjunction with Recsys 2017,
Como, Italy
- W18
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Ferwerda, B., Graus, M., & Schedl, M. & Tkalčič,
M. (2016). The Influence of Users ’ Personality Traits on
Satisfaction and Attractiveness of Diversified Recommendation Lists. In
M. Tkalčič, B. De Carolis, M. de Gemmis, & A. Košir (Eds.),
Proceedings of the 4th Workshop on Emotions and Personality in
Personalized Systems co-located with ACM Conference on Recommender
Systems (RecSys 2016). Boston, MA. Retrieved from
http://ceur-ws.org/Vol-1680/
- W17
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Knees, P., Andersen, K., & Tkalčič, M. (2015). “I’d
like it to do the opposite”: Music-Making Between Recommendation and
Obstruction. In M. Ge & F. Ricci (Eds.), Proceedings of the 2nd
International Workshop on Decision Making and Recommender Systems
(pp. 1–7).
- W16
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Ferwerda, B., Schedl, M., & Tkalčič, M. (2015).
Predicting Personality Traits with Instagram Pictures. In M. Tkalčič, B.
De Carolis, M. de Gemmis, A. Odić, & A. Košir (Eds.), Proceedings of
the 3rd Workshop on Emotions and Personality in Personalized Systems
2015 - EMPIRE ’15 (pp. 7–10). New York, New York, USA: ACM Press.
https://doi.org/10.1145/2809643.2809644
- W15
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Schedl, M., & Tkalčič, M. (2014). Genre-based
Analysis of Social Media Data on Music Listening Behavior. In R.
Zimmerman & Y. Yu (Eds.), Proceedings of the First International
Workshop on Internet-Scale Multimedia Management - WISMM ’14 (pp. 9–13).
New York, New York, USA: ACM Press.
https://doi.org/10.1145/2661714.2661717
- W14
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Tkalčič, M., de Gemmis, M., & Semeraro, G. (2014).
Personality and Emotions in Decision Making and Recommender Systems. In
M. Ge & F. Ricci (Eds.), Proceedings of the First International
Workshop on Decision Making and Recommender Systems (DMRS2014) Bolzano,
Italy, September 18-19, 2014. Retrieved from
http://ceur-ws.org/Vol-1278/paper3.pdf
- W13
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Košir, A., Odić, A., Tkalčič, M., & Svetina, M.
(2014). Human decisions in user modeling : motivation , procedure and
example application. In I. Cantador, M. Chi, R. Farzan, & R. Jäschke
(Eds.), UMAP 2014 Extended Proceedings. Retrieved from
http://ceur-ws.org/Vol-1181/empire2014_paper_03.pdf
- W12
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Tkalčič, M., Ferwerda, B., Schedl, M., Liem, C.,
Melenhorst, M., Odić, A., & Košir, A. (2014). Using social media
mining for estimating theory of planned behaviour parameters. In I.
Cantador, M. Chi, R. Farzan, & R. Jäschke (Eds.), UMAP 2014 Extended
Proceedings (Vol. 1181). Retrieved from
http://ceur-ws.org/Vol-1181/empire2014_paper_06.pdf
- W11
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Vodlan, T., Tkalčič, M., & Kosir, A. (2013). The
Role of Social Signals in Telecommunication : Experimental Design. In S.
Berkovsky, E. Herder, P. Lops, & O. C. Santos (Eds.), UMAP 2013
Extended Proceedings. Retrieved from
http://ceur-ws.org/Vol-997/empire2013_paper_6.pdf
- W10
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Košir, A., Odić, A., & Tkalčič, M. (2013). How to
improve the statistical power of the 10-fold cross validation scheme in
recommender systems. In A. Bellogín, P. Castells, A. Said, & D. Tikk
(Eds.), Proceedings of the International Workshop on Reproducibility and
Replication in Recommender Systems Evaluation - RepSys ’13 (pp. 3–6).
New York, New York, USA: ACM Press.
https://doi.org/10.1145/2532508.2532510
- W9
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Odić, A., Tkalčič, M., & Košir, A. (2013). Managing
Irrelevant Contextual Categories in a Movie Recommender System. In L.
Chen, M. de Gemmis, A. Felfernig, P. Lops, F. Ricci, G. Semeraro, &
M. Willemsen (Eds.), RecSys’13 Workshop on Human Decision Making in
Recommender Systems, 2013, Hong Kong. Retrieved from
http://ceur-ws.org/Vol-1050/paper5.pdf
- W8
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Odić, A., Tkalčič, M., Tasič, J. F., & Košir, A.
(2013). Personality and Social Context : Impact on Emotion Induction
from Movies. In S. Berkovsky, E. Herder, P. Lops, & O. C. Santos
(Eds.), UMAP 2013 Extended Proceedings. Retrieved from
http://ceur-ws.org/Vol-997/empire2013_paper_5.pdf
- W7
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Odić, A., Tkalčič, M., Tasič, J. F., & Košir, A.
(2012). Relevant Context in a Movie Recommender System : Users ’ Opinion
vs . Statistical Detection. In G. Adomavicius, L. Baltrunas, E. W. de
Luca, T. Hussein, & A. Tuzhilin (Eds.), Proceedings of the 4th
Workshop on Context-Aware Recommender Systems in conjunction with the
6th ACM Conference on Recommender Systems (RecSys 2012). Retrieved from
http://ceur-ws.org/Vol-889/paper2.pdf
- W6
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Tkalčič, M., Kunaver, M., Košir, A., & Tasič, J.
(2011). Addressing the new user problem with a personality based user
similarity measure. In F. Ricci, G. Semeraro, M. de Gemmis, P. Lops, J.
Masthoff, F. Grasso, & J. Ham (Eds.), Joint Proceedings of the
Workshop on Decision Making and Recommendation Acceptance Issues in
Recommender Systems (DEMRA 2011) and the 2nd Workshop on User Models for
Motivational Systems: The affective and the rational routes to
persuasion (UMMS 2011). Retrieved from
http://ceur-ws.org/Vol-740/DEMRA_UMMS_2011_proceedings.pdf#page=106
- W5
-
Tkalčič, M., Odić, A., Košir, A., & Tasič, J.
(2011). Impact of Implicit and Explicit Affective Labeling on a
Recommender System’s Performance. Joint Proceedings of the Workshop on
Decision Making and Recommendation Acceptance Issues in Recommender
Systems (DEMRA 2011) and the 2nd Workshop on User Models for
Motivational Systems: The Affective and the Rational Routes to
Persuasion (UMMS 2011), 112. Retrieved from
http://ceur-ws.org/Vol-740/UMMS2011_paper7.pdf
- W4
-
Tkalčič, M., Košir, A., Tasič, J., & Kunaver, M.
(2011). Affective recommender systems: the role of emotions in
recommender systems. In A. Felfernig, L. Chen, M. Mandl, M. Willemsen,
D. Bollen, & M. Ekstrand (Eds.), Joint proceedings of the RecSys
2011 Workshop on Human Decision Making in Recommender Systems
(Decisions@RecSys’11) and User-Centric Evaluation of Recommender Systems
and Their Interfaces-2 (UCERSTI 2) affiliated with the 5th ACM
Conference on Recommender (pp. 9–13). Retrieved from
http://ceur-ws.org/Vol-811/paper2.pdf
- W3
-
Tkalčič, M., Tasič, J., & Košir, A. (2009). The
LDOS-PerAff-1 Corpus of Face Video Clips with Affective and Personality
Metadata. In M. Kipp, J.-C. Martin, P. Paggio, & D. Heylen (Eds.),
Proceedings of Multimodal Corpora: Advances in Capturing, Coding and
Analyzing Multimodality (Malta, 2010), LREC (p. 111). Retrieved from
http://embots.dfki.de/doc/MMC2010-Proceedings.pdf
- W2
-
Tkalčič, M., Kunaver, M., Tasič, J., & Košir, A.
(2009). Personality Based User Similarity Measure for a Collaborative
Recommender System. In C. Peter, E. Crane, L. Axelrod, H. Agius, S.
Afzal, & M. Balaam (Eds.), 5th Workshop on Emotion in Human-Computer
Interaction-Real World Challenges (p. 30). Retrieved from
http://publica.fraunhofer.de/documents/N-113443.html
- W1
-
Tkalčič, M., Tasič, J. F., & Košir, A. (2009).
Emotive and Personality Parameters in Multimedia Recommender Systems. In
A. Vinciarelli, C. Pelachaud, R. Cowie, & A. Nijholt (Eds.),
Affective Computing and Intelligent Interaction Proceedings of the
Doctoral Consortium 2009 (1st ed., p. 33). CTIT Workshop Proceedings
Series WP09-13. Retrieved from
http://www.utwente.nl/ctit/library/proceedings/wp0913.pdf
Books, Edited Volumes
and Book Chapters
- B18
-
Masthoff, J., Herder, E., Tintarev, N., & Tkalčič,
M. (2021). UMAP ’21: Proceedings of the 29th ACM Conference on
User Modeling, Adaptation and Personalization. Association for Computing
Machinery.
- B17
-
Masthoff, J., Herder, E., Tintarev, N., & Tkalčič,
M. (2021). UMAP ’21: Adjunct Proceedings of the 29th ACM
Conference on User Modeling, Adaptation and Personalization. Association
for Computing Machinery.
- B16
-
Delić, A., Nguyen, T. N., & Tkalčič, M. (2020).
Group Decision-Making and Designing Group Recommender Systems. In
Handbook of e-Tourism (pp. 1–23). Springer International Publishing.
https://doi.org/10.1007/978-3-030-05324-6_57-1
- B15
-
Tkalcic, M., Pera S., Proceedings of ACM RecSys 2019
Late-breaking Results (ACM RecSys LBR 2019), Copenhagen, Denmark,
September 16-20, 2019. http://ceur-ws.org/Vol-2431/
- B14
-
Tonellotto, N., Becchetti, L., Tkalčič, M., Proceedings
of the 9th Italian Information Retrieval Workshop (IIR 2018), Rome,
Italy, May, 28-30, 2018. http://ceur-ws.org/Vol-2140/
- B13
-
Felfernig, A., Boratto, L., Stettinger, M., & Tkalčič,
M. (2018). Group Recommender Systems. Springer International
Publishing. https://doi.org/10.1007/978-3-319-75067-5
- B12
-
Tkalčič, M., Delić, A., & Felfernig, A. (2018).
Personality, Emotions, and Group Dynamics. In A. Felfernig, L. Boratto,
Martin Stettinger, & M. Tkalčič (Eds.), Group Recommender Systems An
Introduction (pp. 157–167). https://doi.org/10.1007/978-3-319-75067-5_9
- B11
-
Tkalčič, M. (2017). Emotions and Personality in
Recommender Systems. In Encyclopedia of Social Network Analysis and
Mining (2nd ed., pp. 1–9). Springer New York.
https://doi.org/10.1007/978-1-4614-7163-9_110161-1
- B10
-
Tkalčič, M., Thakker, D., Germanakos, P., Yacef, K.,
Paris, C., & Santos, O. (Eds.). (2017). Adjunct Publication of the
25th Conference on User Modeling, Adaptation and Personalization. ACM
New York, NY, USA. Retrieved from
http://dl.acm.org/citation.cfm?id=3099023
- B9
-
Odić, A., Košir, A., & Tkalčič, M. (2016).
Affective and Personality Corpora. In M. Tkalčič, B. De Carolis, M. de
Gemmis, A. Odic, & A. Košir (Eds.), Emotions and Personality in
Personalized Services (pp. 163–178). Springer.
https://doi.org/10.1007/978-3-319-31413-6_9
- B8
-
Tkalčič, M., De Carolis, B., de Gemmis, M., Odić, A.,
& Košir, A. (2016). Introduction to Emotions and Personality in
Personalized Systems. In M. Tkalčič, B. De Carolis, M. de Gemmis, A.
Odic, & A. Košir (Eds.), Emotions and Personality in Personalized
Services (pp. 3–11). Springer.
https://doi.org/10.1007/978-3-319-31413-6_1
- B7
-
Tkalčič, M., Carolis, B. De, Gemmis, M. de, Odić, A.,
& Košir, A. (Eds.). (2016). Emotions and Personality in Personalized
Services. Springer International Publishing.
https://doi.org/10.1007/978-3-319-31413-6
- B6
-
Tkalčič, M., De Carolis, B., de Gemmis, M., Odić, A.,
& Košir, A. (2016). Proceedings of the 4th Workshop on Emotions and
Personality in Personalized Systems (EMPIRE 2016), Boston, MA, USA,
September 16, 2016. http://ceur-ws.org/Vol-1680/
- B5
-
Tkalčič, M., & Chen, L. (2015). Personality and
Recommender Systems. In F. Ricci, L. Rokach, & B. Shapira (Eds.),
Recommender Systems Handbook (2nd ed., Vol. 54, pp. 715–739). Boston,
MA: Springer US. https://doi.org/10.1007/978-1-4899-7637-6_21
- B4
-
Tkalčič, M., De Carolis, B., de Gemmis, M., Odić, A.,
& Košir, A. (2015). Proceedings of the 3rd Workshop on Emotions and
Personality in Personalized Systems 2015,
http://dl.acm.org/citation.cfm?id=2809643&preflayout=flat#source
- B3
-
Tkalčič, M., Tasič, J. F., & Košir, A. (2012). The
Need for Affective Metadata in Content-Based Recommender Systems for
Images. In M. Maybury (Ed.), Multimedia Information Extraction: Advances
in Video, Audio, and Imagery Analysis for Search, Data Mining,
Surveillance, and Authoring. Wiley - IEEE Computer Society Press.
https://doi.org/10.1002/9781118219546.ch19
- B2
-
Tkalčič, M., Košir, A., & Tasič, J. F. (2011).
Emotive and personality parameters in recommender systems: Recognition
and usage of user-centric data for user and item modeling in content
retrieval systems. LAP LAMBERT Academic Publishing.
- B1
-
Tkalčič, M., & Pogačnik, M. (2006). Tourist Adapted
Destination Selection. In R. Ovsenik & I. Kiereta (Eds.),
Destination Management (pp. 195–209). Peter Lang. Retrieved from
http://www.peterlang.de/index.cfm?event=cmp.ccc.seitenstruktur.detailseiten&seitentyp=produkt&pk=39292&CFID=200073&CFTOKEN=50206088
Other
- O4
-
Ferwerda, B., Chen, L., & Tkalčič, M. (2021).
Editorial: Psychological Models for Personalized Human-Computer
Interaction (HCI). Frontiers in Psychology, 12, 673092.
https://doi.org/10.3389/fpsyg.2021.673092
- O3
-
Tkalčič, M., Schedl, M., & Knees, P. (2020).
Preface to the Special Issue on user modeling for personalized
interaction with music. User Modeling and User-Adapted Interaction,
0123456789, 1–4. https://doi.org/10.1007/s11257-020-09264-6
- O2
-
Tkalčič, M., Quercia, D., & Graf, S. (2016).
Preface to the special issue on personality in personalized systems.
User Modeling and User-Adapted Interaction, 26(2–3), 103–107.
https://doi.org/10.1007/s11257-016-9175-9 (non peer reviewed)
- O1
-
Gemmis, M. de, Carolis, N. De, Košir, A., & Tkalčič,
M. (2016). Emotions and Personality in Personalized Systems.
Interaction Design and Architecture(s) Journal - IxD&A, 28, 105–109.
(non peer reviewed)
Invited Talks
- 2021
-
Invited talk at the University of Bergen, Norway within
the Media Futures project, Computational Psychology in Recommender
Systems, 8. June 2021,
https://mediafutures.no/event/seminar-computational-psychology-in-recommender-systems-marko-tkalcic-university-of-primorska-slovenia/
- 2020
-
Keynote talk at the ISMIS 2020 conference,
Complementing Behavioural Modeling with Cognitive Modeling for
Better Recommendations. In Lecture Notes in Computer Science
(including subseries Lecture Notes in Artificial Intelligence and
Lecture Notes in Bioinformatics): Vol. 12117 LNAI (pp. 3–8).
https://doi.org/10.1007/978-3-030-59491-6_1
- 2020
-
Invited talk at Durham University, UK, Emotions and
Personality for Better Recommendations, 9. March 2020
- 2020
-
Invited talk at the Graz University of Technology,
Austria, 27. February 2020
- 2019
-
Keynote talk at the AI Journey conference in Moscow,
Russia, From Behavioural to Cognitive Modeling in Recommender
Systems,
https://ai-journey.ru/en/conference-moscow/science-day-program
- 2019
-
Invited talk at the Robert Bosch GmbH Center for Research and
Development, Stuttgart, Germany 19. February 2019
- 2017
-
Invited talk at the Alpen-Adria-Universität Klagenfurt,
Austria, Affective Personalization - from Psychology to
Algorithms, 21. December 2017,
https://www.ftf.or.at/2017/12/affective-personalization-from-psychology-to-algorithms/
- 2017
-
Invited talk at the Jonkoping University, Sweden,
Bridging computer-science and psychological models for
personalization 5. October 2017
- 2017
-
Invited talk at the Vienna University of Technology,
Austria Psychologically-driven Personalization, 10. April 2017
- 2016
-
Invited talk at the University in Ljubljana, Slovenia
Faculty of Computer Science: Psychologically-driven
Personalization,
https://www.fri.uni-lj.si/en/news/article/fri-piskot-seminar-Tkalčič-psychologically-driven-personalization,
22. December 2016
- 2016
-
Invited talk at the Johannes Kepler University, Linz,
Austria: Learning from User-generated Data, 21. June 2016
- 2015
-
Invited talk at the Brain Week 2015 conference,
Ljubljana: Tell me what you like and I tell you who you are: social
media, personality and emotions, 18. March 2015,
http://www.sinapsa.org/tm/program/2015-03-18/Ljubljana
- 2015
-
Invited talk at the Graz University of Technology,
Austria, Affect- and Personality-based Recommendations, 26.
January 2015, http://ase.ist.tugraz.at/ASE/?page_id=224
- 2014
-
Invited talk at the International Workshop on Decision Making
and Recommender Systems 2014, Bolzano, Italy: Decision
Making, Personality and Emotions (with Giovanni Semeraro and Marco
de Gemmis), 18. September 2014, http://dmrsworkshop.inf.unibz.it/2014/
- 2013
-
Invited talk at the Johannes Kepler University Linz,
Austria, Emotions, personality and recommender systems,
Department of Computational Perception, 12. February, 2013
- 2012
-
Invited talk at the Conference of Cognitive Sciences –
Information Society 2012: Automatic Detection of
Emotions, 8-12. October, 2012, Jožef Stefan Institute, Ljubljana,
Slovenia
http://is.ijs.si/is/is2012/konference/Kognitivna/KZ-IS-2012-ENG.pdf
- 2012
-
Invited talk at the Free University of Bolzano, Italy:
Affect in recommender systems. Bolzano: Libera Università, 4.
September 2012 https://www.inf.unibz.it/dis/wp/?page_id=100#Tkalčič
Tutorials and Summer Schools
- 2018
-
ACM RecSys 2018, Vancouver: Tutorial Emotions and Personality in
Recommender Systems
- 2017
-
ACM Summer School on Recommender Systems, Bozen-Bolzano, 21-25 August
2017 Affect and Personality-Based RS