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ORCIDNada Lavrac
Nada Lavrač
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- unicode name: Nada Lavrač
- affiliation: University of Nova Gorica, Slovenia
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2020 – today
- 2024
[c131]Boshko Koloski, Nada Lavrac, Bojan Cestnik, Senja Pollak, Blaz Skrlj, Andrej Kastrin:
AHAM: Adapt, Help, Ask, Model Harvesting LLMs for Literature Mining. IDA (1) 2024: 254-265- [e12]Slawomir Nowaczyk
, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part I. Communications in Computer and Information Science 1947, Springer 2024, ISBN 978-3-031-50395-5 [contents] - [e11]Slawomir Nowaczyk, Przemyslaw Biecek, Neo Christopher Chung, Mauro Vallati, Pawel Skruch, Joanna Jaworek-Korjakowska, Simon Parkinson, Alexandros Nikitas, Martin Atzmüller, Tomás Kliegr, Ute Schmid, Szymon Bobek, Nada Lavrac, Marieke Peeters, Roland van Dierendonck, Saskia Robben, Eunika Mercier-Laurent, Gülgün Kayakutlu, Mieczyslaw Lech Owoc, Karl Mason, Abdul Wahid, Pierangela Bruno, Francesco Calimeri, Francesco Cauteruccio, Giorgio Terracina, Diedrich Wolter, Jochen L. Leidner, Michael Kohlhase, Vania Dimitrova:
Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30 - October 4, 2023, Proceedings, Part II. Communications in Computer and Information Science 1948, Springer 2024, ISBN 978-3-031-50484-6 [contents] - [i20]Luka Andrensek, Boshko Koloski, Andraz Pelicon, Nada Lavrac, Senja Pollak, Matthew Purver:
Evaluating and explaining training strategies for zero-shot cross-lingual news sentiment analysis. CoRR abs/2409.20054 (2024) - 2023
- [j98]Blaz Skrlj, Matej Bevec, Nada Lavrac:
Multimodal AutoML via Representation Evolution. Mach. Learn. Knowl. Extr. 5(1): 1-13 (2023) - [c130]Boshko Koloski, Marko Pranjic, Nada Lavrac, Blaz Skrlj, Senja Pollak:
Inducing Document Representations from Graphs: A Blueprint. Tiny Papers @ ICLR 2023 - [i19]Jan Kralj, Blaz Skrlj, Ziva Ramsak, Nada Lavrac, Kristina Gruden:
DDeMON: Ontology-based function prediction by Deep Learning from Dynamic Multiplex Networks. CoRR abs/2302.03907 (2023) - [i18]Boshko Koloski, Blaz Skrlj, Senja Pollak, Nada Lavrac:
Latent Graph Powered Semi-Supervised Learning on Biomedical Tabular Data. CoRR abs/2309.15757 (2023) - [i17]Boshko Koloski, Nada Lavrac, Bojan Cestnik, Senja Pollak, Blaz Skrlj, Andrej Kastrin:
AHAM: Adapt, Help, Ask, Model - Harvesting LLMs for literature mining. CoRR abs/2312.15784 (2023) - 2022
- [j97]Tadej Skvorc, Nada Lavrac, Marko Robnik-Sikonja:
NeSyChair: Automatic Conference Scheduling Combining Neuro-Symbolic Representations and Constrained Clustering. IEEE Access 10: 10880-10897 (2022) - [j96]Blaz Skrlj, Jan Kralj, Janez Konc, Marko Robnik-Sikonja, Nada Lavrac:
Deep node ranking for neuro-symbolic structural node embedding and classification. Int. J. Intell. Syst. 37(1): 914-943 (2022) - [j95]Sebastian Meznar, Matej Bevec, Nada Lavrac, Blaz Skrlj:
Ontology Completion with Graph-Based Machine Learning: A Comprehensive Evaluation. Mach. Learn. Knowl. Extr. 4(4): 1107-1123 (2022) - [j94]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: feature ranking in high-dimensional spaces via manifold embeddings. Mach. Learn. 111(1): 273-317 (2022) - 2021
- [j93]Blaz Skrlj, Nika Erzen, Nada Lavrac, Tanja Kunej, Janez Konc:
CaNDis: a web server for investigation of causal relationships between diseases, drugs and drug targets. Bioinform. 37(6): 885-887 (2021) - [j92]Sebastian Meznar, Nada Lavrac, Blaz Skrlj:
Transfer Learning for Node Regression Applied to Spreading Prediction. Complex Syst. 30(4): 457-481 (2021) - [j91]Blaz Skrlj, Matej Martinc, Jan Kralj, Nada Lavrac, Senja Pollak:
tax2vec: Constructing Interpretable Features from Taxonomies for Short Text Classification. Comput. Speech Lang. 65: 101104 (2021) - [j90]Blaz Skrlj, Enja Kokalj, Nada Lavrac:
PubMed-Scale Chemical Concept Embeddings Reconstruct Physical Protein Interaction Networks. Frontiers Res. Metrics Anal. 6: 644614 (2021) - [j89]Blaz Skrlj, Matej Martinc, Nada Lavrac, Senja Pollak:
autoBOT: evolving neuro-symbolic representations for explainable low resource text classification. Mach. Learn. 110(5): 989-1028 (2021) - [c129]Anita Valmarska, Nada Lavrac, Marko Robnik-Sikonja:
Stratification of Parkinson's Disease Patients via Multi-view Clustering. AIME 2021: 229-239 - [c128]Blaz Skrlj, Marko Jukic, Nika Erzen, Senja Pollak, Nada Lavrac:
Prioritization of COVID-19-Related Literature via Unsupervised Keyphrase Extraction and Document Representation Learning. DS 2021: 204-217 - [c127]Enja Kokalj, Blaz Skrlj, Nada Lavrac, Senja Pollak, Marko Robnik-Sikonja:
BERT meets Shapley: Extending SHAP Explanations to Transformer-based Classifiers. EACL (Hackashop) 2021: 16-21 - [c126]Senja Pollak, Marko Robnik-Sikonja, Matthew Purver, Michele Boggia, Ravi Shekhar, Marko Pranjic, Salla Salmela, Ivar Krustok, Tarmo Paju, Carl-Gustav Linden, Leo Leppänen, Elaine Zosa, Matej Ulcar, Linda Freienthal, Silver Traat, Luis Adrián Cabrera-Diego, Matej Martinc, Nada Lavrac, Blaz Skrlj, Martin Znidarsic, Andraz Pelicon, Boshko Koloski, Vid Podpecan, Janez Kranjc, Shane Sheehan, Emanuela Boros, José G. Moreno, Antoine Doucet, Hannu Toivonen:
EMBEDDIA Tools, Datasets and Challenges: Resources and Hackathon Contributions. EACL (Hackashop) 2021: 99-109 - [c125]Senja Pollak, Vid Podpecan, Janez Kranjc, Borut Lesjak, Nada Lavrac:
Scientific Question Generation: Pattern-Based and Graph-Based RoboCHAIR Methods. ICCC 2021: 140-148 - [i16]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
ReliefE: Feature Ranking in High-dimensional Spaces via Manifold Embeddings. CoRR abs/2101.09577 (2021) - [i15]Sebastian Meznar, Nada Lavrac, Blaz Skrlj:
Transfer Learning for Node Regression Applied to Spreading Prediction. CoRR abs/2104.00088 (2021) - [i14]Timen Stepisnik Perdih, Nada Lavrac, Blaz Skrlj:
Semantic Reasoning from Model-Agnostic Explanations. CoRR abs/2106.15433 (2021) - [i13]Blaz Skrlj, Marko Jukic, Nika Erzen, Senja Pollak, Nada Lavrac:
Prioritization of COVID-19-related literature via unsupervised keyphrase extraction and document representation learning. CoRR abs/2110.08874 (2021) - [i12]Sebastian Meznar, Matej Bevec, Nada Lavrac, Blaz Skrlj:
Link Analysis meets Ontologies: Are Embeddings the Answer? CoRR abs/2111.11710 (2021) - 2020
- [j88]Sebastian Meznar, Nada Lavrac, Blaz Skrlj:
SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations. IEEE Access 8: 212568-212588 (2020) - [j87]Dominik Kozjek, Rok Vrabic, Borut Rihtarsic, Nada Lavrac, Peter Butala:
Advancing manufacturing systems with big-data analytics: A conceptual framework. Int. J. Comput. Integr. Manuf. 33(2): 169-188 (2020) - [j86]Nada Lavrac, Blaz Skrlj, Marko Robnik-Sikonja:
Propositionalization and embeddings: two sides of the same coin. Mach. Learn. 109(7): 1465-1507 (2020) - [j85]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Embedding-based Silhouette community detection. Mach. Learn. 109(11): 2161-2193 (2020) - [j84]Nada Lavrac, Matej Martinc, Senja Pollak, Marusa Pompe-Novak, Bojan Cestnik:
Bisociative Literature-Based Discovery: Lessons Learned and New Word Embedding Approach. New Gener. Comput. 38(4): 773-800 (2020) - [c124]Anita Valmarska, Dragana Miljkovic, Nada Lavrac, Marko Robnik-Sikonja:
Multi-view Clustering with mvReliefF for Parkinson's Disease Patients Subgroup Detection. AIME 2020: 287-298 - [c123]Sebastian Meznar, Nada Lavrac, Blaz Skrlj:
Prediction of the Effects of Epidemic Spreading with Graph Neural Networks. COMPLEX NETWORKS (1) 2020: 420-431 - [c122]Matej Martinc, Blaz Skrlj, Sergej Pirkmajer, Nada Lavrac, Bojan Cestnik, Martin Marzidovsek, Senja Pollak:
COVID-19 Therapy Target Discovery with Context-Aware Literature Mining. DS 2020: 109-123 - [c121]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. ECAI 2020: 1491-1498 - [c120]Nada Lavrac, Matej Martinc, Senja Pollak, Bojan Cestnik:
Bisociative Literature-Based Discovery: Lessons Learned and New Prospects. ICCC 2020: 139-145 - [i11]Blaz Skrlj, Saso Dzeroski, Nada Lavrac, Matej Petkovic:
Feature Importance Estimation with Self-Attention Networks. CoRR abs/2002.04464 (2020) - [i10]Nada Lavrac, Blaz Skrlj, Marko Robnik-Sikonja:
Propositionalization and Embeddings: Two Sides of the Same Coin. CoRR abs/2006.04410 (2020) - [i9]Matej Martinc, Blaz Skrlj, Sergej Pirkmajer, Nada Lavrac, Bojan Cestnik, Martin Marzidovsek, Senja Pollak:
COVID-19 therapy target discovery with context-aware literature mining. CoRR abs/2007.15681 (2020) - [i8]Sebastian Meznar, Nada Lavrac, Blaz Skrlj:
SNoRe: Scalable Unsupervised Learning of Symbolic Node Representations. CoRR abs/2009.04535 (2020)
2010 – 2019
- 2019
- [j83]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Py3plex toolkit for visualization and analysis of multilayer networks. Appl. Netw. Sci. 4(1): 94:1-94:24 (2019) - [j82]Vid Podpecan, Ziva Ramsak, Kristina Gruden, Hannu Toivonen, Nada Lavrac:
Interactive exploration of heterogeneous biological networks with Biomine Explorer. Bioinform. 35(24): 5385-5388 (2019) - [j81]Ping Xiao, Hannu Toivonen, Oskar Gross, Amílcar Cardoso, João Correia, Penousal Machado, Pedro Martins, Hugo Gonçalo Oliveira, Rahul Sharma, Alexandre Miguel Pinto, Alberto Díaz, Virginia Francisco, Pablo Gervás, Raquel Hervás, Carlos León, Jamie Forth, Matthew Purver, Geraint A. Wiggins, Dragana Miljkovic, Vid Podpecan, Senja Pollak, Jan Kralj, Martin Znidarsic, Marko Bohanec, Nada Lavrac, Tanja Urbancic, Frank van der Velde, Stuart Adam Battersby:
Conceptual Representations for Computational Concept Creation. ACM Comput. Surv. 52(1): 9:1-9:33 (2019) - [j80]Pedro Martins, Hugo Gonçalo Oliveira, João Gonçalves, António Cruz, Amílcar Cardoso, Martin Znidarsic, Nada Lavrac, Simo Linkola, Hannu Toivonen, Raquel Hervás, Gonzalo Méndez, Pablo Gervás:
Computational creativity infrastructure for online software composition: A conceptual blending use case. IBM J. Res. Dev. 63(1): 9:1-9:17 (2019) - [j79]Blaz Skrlj, Jan Kralj, Nada Lavrac:
CBSSD: community-based semantic subgroup discovery. J. Intell. Inf. Syst. 53(2): 265-304 (2019) - [j78]Jan Kralj, Marko Robnik-Sikonja, Nada Lavrac:
NetSDM: Semantic Data Mining with Network Analysis. J. Mach. Learn. Res. 20: 32:1-32:50 (2019) - [j77]Dragan Gamberger, Tjasa Stare, Dragana Miljkovic, Kristina Gruden, Nada Lavrac:
Discovery of Relevant Response in Infected Potato Plants from Time Series of Gene Expression Data. Mach. Learn. Knowl. Extr. 1(1): 400-413 (2019) - [j76]Blaz Skrlj, Jan Kralj, Nada Lavrac, Senja Pollak:
Towards Robust Text Classification with Semantics-Aware Recurrent Neural Architecture. Mach. Learn. Knowl. Extr. 1(2): 575-589 (2019) - [c119]Anita Valmarska, Dragana Miljkovic, Marko Robnik-Sikonja, Nada Lavrac:
Connection Between the Parkinson's Disease Subtypes and Patients' Symptoms Progression. AIME 2019: 263-268 - [c118]Blaz Skrlj, Nada Lavrac, Jan Kralj:
Symbolic Graph Embedding Using Frequent Pattern Mining. DS 2019: 261-275 - [p14]Nada Lavrac, Matjaz Jursic, Borut Sluban, Matic Perovsek, Senja Pollak, Tanja Urbancic, Bojan Cestnik:
Bisociative Knowledge Discovery for Cross-domain Literature Mining. Computational Creativity 2019: 121-139 - [i7]Blaz Skrlj, Matej Martinc, Jan Kralj, Nada Lavrac, Senja Pollak:
tax2vec: Constructing Interpretable Features from Taxonomies for Short Text Classification. CoRR abs/1902.00438 (2019) - [i6]Blaz Skrlj, Jan Kralj, Janez Konc, Marko Robnik-Sikonja, Nada Lavrac:
Deep Node Ranking: an Algorithm for Structural Network Embedding and End-to-End Classification. CoRR abs/1902.03964 (2019) - [i5]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Embedding-based Silhouette Community Detection. CoRR abs/1908.02556 (2019) - [i4]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Symbolic Graph Embedding using Frequent Pattern Mining. CoRR abs/1910.13314 (2019) - 2018
- [j75]Anita Valmarska, Dragana Miljkovic, Spiros Konitsiotis, Dimitris Gatsios, Nada Lavrac, Marko Robnik-Sikonja:
Symptoms and medications change patterns for Parkinson's disease patients stratification. Artif. Intell. Medicine 91: 82-95 (2018) - [j74]Dragana Miljkovic, Nada Lavrac, Marko Bohanec, Biljana Mileva-Boshkoska:
Discovering dependencies between domains of redox potential and plant defence through triplet extraction and copulas. Int. J. Intell. Eng. Informatics 6(1/2): 61-77 (2018) - [j73]Matej Martinc, Martin Znidarsic, Nada Lavrac, Senja Pollak:
Towards Creative Software Blending: Computational Infrastructure and Use Cases. Informatica (Slovenia) 42(1) (2018) - [j72]Senja Pollak, Geraint A. Wiggins, Martin Znidarsic, Nada Lavrac:
Computational Creativity in Slovenia. Informatica (Slovenia) 42(1) (2018) - [j71]Jan Kralj, Marko Robnik-Sikonja, Nada Lavrac:
HINMINE: heterogeneous information network mining with information retrieval heuristics. J. Intell. Inf. Syst. 50(1): 29-61 (2018) - [j70]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription mining augmented with random forest of multi-target predictive clustering trees. J. Intell. Inf. Syst. 50(1): 63-96 (2018) - [j69]Anita Valmarska, Dragana Miljkovic, Nada Lavrac, Marko Robnik-Sikonja:
Analysis of medications change in Parkinson's disease progression data. J. Intell. Inf. Syst. 51(2): 301-337 (2018) - [j68]Anita Valmarska, Dragana Miljkovic, Nada Lavrac, Marko Robnik-Sikonja:
Correction to: Analysis of medications change in Parkinson's disease progression data. J. Intell. Inf. Syst. 51(2): 339-340 (2018) - [c117]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Py3plex: A Library for Scalable Multilayer Network Analysis and Visualization. COMPLEX NETWORKS (1) 2018: 757-768 - [c116]Anita Valmarska, Dragana Miljkovic, Marko Robnik-Sikonja, Nada Lavrac:
Visualization and Analysis of Parkinson's Disease Status and Therapy Patterns. DS 2018: 466-479 - [c115]Geraint A. Wiggins, Nada Lavrac, Vid Podpecan, Senja Pollak:
Conceptualising Computational Creativity: Towards automated historiography of a research field. ICCC 2018: 288-295 - [c114]Blaz Skrlj, Jan Kralj, Nada Lavrac:
Targeted End-to-End Knowledge Graph Decomposition. ILP 2018: 157-171 - 2017
- [j67]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. Expert Syst. Appl. 68: 196-215 (2017) - [j66]Anita Valmarska, Nada Lavrac, Johannes Fürnkranz, Marko Robnik-Sikonja:
Refinement and selection heuristics in subgroup discovery and classification rule learning. Expert Syst. Appl. 81: 147-162 (2017) - [j65]Donatella Gubiani, Elsa Fabbretti, Bojan Cestnik, Nada Lavrac, Tanja Urbancic:
Outlier based literature exploration for cross-domain linking of Alzheimer's disease and gut microbiota. Expert Syst. Appl. 85: 386-396 (2017) - [j64]Janez Kranjc, Roman Orac, Vid Podpecan, Nada Lavrac, Marko Robnik-Sikonja:
ClowdFlows: Online workflows for distributed big data mining. Future Gener. Comput. Syst. 68: 38-58 (2017) - [c113]Anita Valmarska, Dragana Miljkovic, Spiros Konitsiotis, Dimitris Gatsios, Nada Lavrac, Marko Robnik-Sikonja:
Combining Multitask Learning and Short Time Series Analysis in Parkinson's Disease Patients Stratification. AIME 2017: 116-125 - [c112]Blaz Skrlj, Jan Kralj, Anze Vavpetic, Nada Lavrac:
Community-Based Semantic Subgroup Discovery. NFMCP@PKDD/ECML 2017: 182-196 - [r2]Petra Kralj Novak, Nada Lavrac, Geoffrey I. Webb:
Supervised Descriptive Rule Induction. Encyclopedia of Machine Learning and Data Mining 2017: 1210-1213 - [i3]Matej Mihelcic, Goran Simic, Mirjana Babic Leko, Nada Lavrac, Saso Dzeroski, Tomislav Smuc:
Using Redescription Mining to Relate Clinical and Biological Characteristics of Cognitively Impaired and Alzheimer's Disease Patients. CoRR abs/1702.06831 (2017) - 2016
- [j63]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Netta Shachar, Nada Lavrac:
Clusters of male and female Alzheimer's disease patients in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Brain Informatics 3(3): 169-179 (2016) - [j62]Prem Raj Adhikari, Anze Vavpetic, Jan Kralj, Nada Lavrac, Jaakko Hollmén:
Explaining mixture models through semantic pattern mining and banded matrix visualization. Mach. Learn. 105(1): 3-39 (2016) - [j61]Matic Perovsek, Janez Kranjc, Tomaz Erjavec, Bojan Cestnik, Nada Lavrac:
TextFlows: A visual programming platform for text mining and natural language processing. Sci. Comput. Program. 121: 128-152 (2016) - [c111]Dragana Miljkovic, Nada Lavrac, Marko Bohanec, Biljana Mileva-Boshkoska:
Detection of dependencies between literature domains through relation extraction and copulas. CoDIT 2016: 302-307 - [c110]Senja Pollak, Biljana Mileva-Boshkoska, Dragana Miljkovic, Geraint A. Wiggins, Nada Lavrac:
Computational Creativity Conceptualisation Grounded on ICCC Papers. ICCC 2016: 123-130 - [c109]Martin Znidarsic, Amílcar Cardoso, Pablo Gervás, Pedro Martins, Raquel Hervás, Ana Oliveira Alves, Hugo Gonçalo Oliveira, Ping Xiao, Simo Linkola, Hannu Toivonen, Janez Kranjc, Nada Lavrac:
Computational Creativity Infrastructure for Online Software Composition: A Conceptual Blending Use Case. ICCC 2016: 371-379 - [c108]Jasmina Smailovic, Miha Grcar, Nada Lavrac, Martin Znidarsic:
Dynamic Parameter Adaptation of SVM Based Active Learning Methodology. AL@iKNOW 2016: 17-24 - [c107]Jan Kralj, Anze Vavpetic, Michel Dumontier, Nada Lavrac:
Network Ranking Assisted Semantic Data Mining. IWBBIO 2016: 752-764 - [c106]Anita Valmarska, Dragana Miljkovic, Marko Robnik-Sikonja, Nada Lavrac:
Multi-view Approach to Parkinson's Disease Quality of Life Data Analysis. NFMCP@PKDD/ECML 2016: 163-178 - [c105]Tadej Skvorc, Nada Lavrac, Marko Robnik-Sikonja:
Co-Bidding Graphs for Constrained Paper Clustering. SLATE 2016: 1:1-1:13 - [p13]Matic Perovsek, Matjaz Jursic, Bojan Cestnik, Nada Lavrac:
Empowering Bridging Term Discovery for Cross-Domain Literature Mining in the TextFlows Platform. Machine Learning for Health Informatics 2016: 59-98 - [p12]Dragana Miljkovic, Darko Aleksovski, Vid Podpecan, Nada Lavrac, Bernd Malle, Andreas Holzinger:
Machine Learning and Data Mining Methods for Managing Parkinson's Disease. Machine Learning for Health Informatics 2016: 209-220 - [i2]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
A framework for redescription set construction. CoRR abs/1606.03935 (2016) - 2015
- [j60]Matic Perovsek, Anze Vavpetic, Janez Kranjc, Bojan Cestnik, Nada Lavrac:
Wordification: Propositionalization by unfolding relational data into bags of words. Expert Syst. Appl. 42(17-18): 6442-6456 (2015) - [j59]Borut Sluban, Nada Lavrac:
Relating ensemble diversity and performance: A study in class noise detection. Neurocomputing 160: 120-131 (2015) - [j58]Janez Kranjc, Jasmina Smailovic, Vid Podpecan, Miha Grcar, Martin Znidarsic, Nada Lavrac:
Active learning for sentiment analysis on data streams: Methodology and workflow implementation in the ClowdFlows platform. Inf. Process. Manag. 51(2): 187-203 (2015) - [c104]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Nada Lavrac:
Identification of Gender Specific Biomarkers for Alzheimer's Disease. BIH 2015: 57-66 - [c103]Pedro Martins, Tanja Urbancic, Senja Pollak, Nada Lavrac, Amílcar Cardoso:
The Good, the Bad, and the AHA! Blends. ICCC 2015: 166-173 - [c102]Dragan Gamberger, Bernard Zenko, Alexis Mitelpunkt, Nada Lavrac:
Multilayer Clustering: Biomarker Driven Segmentation of Alzheimer's Disease Patient Population. IWBBIO (1) 2015: 134-145 - [c101]Nada Lavrac, Anze Vavpetic:
Relational and Semantic Data Mining - - Invited Talk -. LPNMR 2015: 20-31 - [c100]Jan Kralj, Anita Valmarska, Marko Robnik-Sikonja, Nada Lavrac:
Mining Text Enriched Heterogeneous Citation Networks. PAKDD (1) 2015: 672-683 - [c99]Matej Mihelcic, Saso Dzeroski, Nada Lavrac, Tomislav Smuc:
Redescription Mining with Multi-target Predictive Clustering Trees. NFMCP 2015: 125-143 - [c98]Jan Kralj, Marko Robnik-Sikonja, Nada Lavrac:
Heterogeneous Network Decomposition and Weighting with Text Mining Heuristics. NFMCP 2015: 194-208 - [c97]Senja Pollak, Borut Lesjak, Janez Kranjc, Vid Podpecan, Martin nidaric, Nada Lavrac:
RoboCHAIR: Creative Assistant for Question Generation and Ranking. SSCI 2015: 1468-1475 - 2014
- [j57]Dany Morisset, Petra Kralj Novak, Darko Zupanic, Kristina Gruden, Nada Lavrac, Jana Zel:
GMOseek: a user friendly tool for optimized GMO testing. BMC Bioinform. 15: 258 (2014) - [j56]Borut Sluban, Dragan Gamberger, Nada Lavrac:
Ensemble-based noise detection: noise ranking and visual performance evaluation. Data Min. Knowl. Discov. 28(2): 265-303 (2014) - [j55]Dragana Miljkovic, Matjaz Depolli, Tjasa Stare, Igor Mozetic, Marko Petek, Kristina Gruden, Nada Lavrac:
Plant defence model revisions through iterative minimisation of constraint violations. Int. J. Comput. Biol. Drug Des. 7(1): 61-79 (2014) - [j54]Jasmina Smailovic, Miha Grcar, Nada Lavrac, Martin Znidarsic:
Stream-based active learning for sentiment analysis in the financial domain. Inf. Sci. 285: 181-203 (2014) - [j53]Anze Vavpetic, Vid Podpecan, Nada Lavrac:
Semantic subgroup explanations. J. Intell. Inf. Syst. 42(2): 233-254 (2014) - [c96]Prem Raj Adhikari, Anze Vavpetic, Jan Kralj, Nada Lavrac, Jaakko Hollmén:
Explaining Mixture Models through Semantic Pattern Mining and Banded Matrix Visualization. Discovery Science 2014: 1-12 - [c95]Dragan Gamberger, Matej Mihelcic, Nada Lavrac:
Multilayer Clustering: A Discovery Experiment on Country Level Trading Data. Discovery Science 2014: 87-98 - [c94]Maria Teresa Llano, Rose Hepworth, Simon Colton, Jeremy Gow, John William Charnley, Nada Lavrac, Martin Znidarsic, Matic Perovsek, Mark Granroth-Wilding, Stephen Clark:
Baseline Methods for Automated Fictional Ideation. ICCC 2014: 211-219 - [c93]