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Jefrey Lijffijt
Jefrey Lijffijt
Professor at Ghent University - Data Science, Visualisation, ML & AI
Verified email at ugent.be - Homepage
Title
Cited by
Cited by
Year
Significance testing of word frequencies in corpora
J Lijffijt, T Nevalainen, T Säily, P Papapetrou, K Puolamäki, H Mannila
Digital Scholarship in the Humanities, 2014
1382014
Correction to Stefan Th. Gries’ “Dispersions and adjusted frequencies in corpora”
J Lijffijt, ST Gries
International Journal of Corpus Linguistics 17 (1), 147-149, 2012
692012
Quantifying and minimizing risk of conflict in social networks
X Chen, J Lijffijt, T De Bie
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018
632018
Conditional Network Embeddings
B Kang, J Lijffijt, T De Bie
International Conference on Learning Representations, 2019
592019
A statistical significance testing approach to mining the most informative set of patterns
J Lijffijt, P Papapetrou, K Puolamäki
Data Mining and Knowledge Discovery, 1-26, 2012
462012
Conditional t-SNE: more informative t-SNE embeddings
B Kang, D García García, J Lijffijt, R Santos-Rodríguez, T De Bie
Machine Learning 110 (10), 2905-2940, 2021
442021
An Empirical Evaluation of Network Representation Learning Methods
AC Mara, J Lijffijt, T De Bie
Big Data, 2022
39*2022
EvalNE: A framework for network embedding evaluation
A Mara, J Lijffijt, T De Bie
SoftwareX 17, 100997, 2022
37*2022
Opinion dynamics with backfire effect and biased assimilation
X Chen, P Tsaparas, J Lijffijt, T De Bie
PloS one 16 (9), e0256922, 2021
352021
Explanations for Network Embedding-based Link Predictions
B Kang, J Lijffijt, T De Bie
ECML PKDD International Workshop and Tutorial on eXplainable Knowledge …, 2021
35*2021
CEECing the baseline: Lexical stability and significant change in a historical corpus
J Lijffijt, T Säily, T Nevalainen
Helsinki Corpus Festival, 2012
312012
Size matters: Choosing the most informative set of window lengths for mining patterns in event sequences
J Lijffijt, P Papapetrou, K Puolamäki
Data Mining and Knowledge Discovery, 1-27, 2014
29*2014
SICA: subjectively interesting component analysis
B Kang, J Lijffijt, R Santos-Rodríguez, T De Bie
Data Mining and Knowledge Discovery 32 (4), 949-987, 2018
26*2018
Analyzing word frequencies in large text corpora using inter-arrival times and bootstrapping
J Lijffijt, P Papapetrou, K Puolamäki, H Mannila
European Conference on Machine Learning and Principles and Practice of …, 2011
262011
Subjectively interesting connecting trees and forests
F Adriaens, J Lijffijt, T De Bie
Data Mining and Knowledge Discovery 33 (4), 1088-1124, 2019
24*2019
A Constrained Randomization Approach to Interactive Visual Data Exploration with Subjective Feedback
B Kang, K Puolamäki, J Lijffijt, T De Bie
IEEE Transactions on Knowledge and Data Engineering, 2019
22*2019
Interactive visual data exploration with subjective feedback: An information-theoretic approach
K Puolamäki, E Oikarinen, B Kang, J Lijffijt, T De Bie
2018 IEEE 34th International Conference on Data Engineering (ICDE), 1208-1211, 2018
212018
Visually controllable data mining methods
K Puolamaki, P Papapetrou, J Lijffijt
IEEE International Conference on Data Mining Workshops (ICDMW), 409-417, 2010
192010
Benchmarking dynamic time warping for music retrieval
J Lijffijt, P Papapetrou, J Hollmén, V Athitsos
International Conference on PErvasive Technologies Related to Assistive …, 2010
192010
CSNE: Conditional Signed Network Embedding
A Mara, Y Mashayekhi, J Lijffijt, T De Bie
Proceedings of the 29th ACM International Conference on Information …, 2020
182020
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Articles 1–20