Kairit Sirts
Title
Cited by
Cited by
Year
STransE: a novel embedding model of entities and relationships in knowledge bases
DQ Nguyen, K Sirts, L Qu, M Johnson
Proceedings of the 2016 Conference of the North American Chapter of the …, 2016
1112016
Minimally-supervised morphological segmentation using adaptor grammars
K Sirts, S Goldwater
Transactions of the Association for Computational Linguistics 1, 255-266, 2013
522013
A comparative study of minimally supervised morphological segmentation
T Ruokolainen, O Kohonen, K Sirts, SA Grönroos, M Kurimo, S Virpioja
Computational Linguistics 42 (1), 91-120, 2016
342016
Neighborhood Mixture Model for Knowledge Base Completion
DQ Nguyen, K Sirts, L Qu, M Johnson
Proceedings of the 20th SIGNLL Conference on Computational Natural Language …, 2016
322016
A hierarchical Dirichlet process model for joint part-of-speech and morphology induction
K Sirts, T Alumäe
Proceedings of the 2012 Conference of the North American Chapter of the …, 2012
192012
Linear Ensembles of Word Embedding Models
A Muromägi, K Sirts, S Laur
Proceedings of the 21st Nordic Conference of Computational Linguistics, 96-104, 2017
162017
Idea density for predicting Alzheimer’s disease from transcribed speech
K Sirts, O Piguet, M Johnson
Proceedings of the 21st Conference on Computational Natural Language …, 2017
102017
Query-based single document summarization using an ensemble noisy auto-encoder
MY Azar, K Sirts, D Molla, L Hamey
Proceedings of the Australasian Language Technology Association Workshop …, 2015
92015
POS induction with distributional and morphological information using a distance-dependent Chinese restaurant process
K Sirts, J Eisenstein, M Elsner, S Goldwater
Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014
92014
Improving topic coherence with latent feature word representations in map estimation for topic modeling
DQ Nguyen, K Sirts, M Johnson
Proceedings of the Australasian Language Technology Association Workshop …, 2015
82015
Modeling composite labels for neural morphological tagging
A Tkachenko, K Sirts
arXiv preprint arXiv:1810.08815, 2018
62018
Simple App Review Classification with Only Lexical Features
FA Shah, K Sirts, P Dietmar
Proceedings of the 13th International Conference on Software Technologies …, 2018
62018
Simulating the Impact of Annotation Guidelines and Annotated Data on Extracting App Features from App Reviews.
FA Shah, K Sirts, D Pfahl
ICSOFT, 384-396, 2019
52019
Is the SAFE approach too simple for app feature extraction? a replication study
FA Shah, K Sirts, D Pfahl
International Working Conference on Requirements Engineering: Foundation for …, 2019
42019
Neural Morphological Tagging for Estonian.
A Tkachenko, K Sirts
Baltic HLT, 166-174, 2018
42018
Multimodal sequential fashion attribute prediction
HS Arslan, K Sirts, M Fishel, G Anbarjafari
Information 10 (10), 308, 2019
22019
Using app reviews for competitive analysis: tool support
FA Shah, K Sirts, D Pfahl
Proceedings of the 3rd ACM SIGSOFT International Workshop on App Market …, 2019
22019
Non-parametric Bayesian models for computational morphology
K Sirts
TUT Press, 2015
22015
Noisy-Channel Spelling Correction Models for Estonian Learner Language Corpus Lemmatisation.
K Sirts
Baltic HLT, 213-220, 2012
22012
Deep learning textual entailment system for sinhala language
SH Jayasinghe, K Sirts
12019
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Articles 1–20