Zobrazeno 1 - 10
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pro vyhledávání: '"Can, Burcu"'
Autor:
Bölücü, Necva, Can, Burcu
Semantic parsing provides a way to extract the semantic structure of a text that could be understood by machines. It is utilized in various NLP applications that require text comprehension such as summarization and question answering. Graph-based rep
Externí odkaz:
http://arxiv.org/abs/2110.00621
Autor:
Sen, Sevil, Can, Burcu
Android is among the most targeted platform by attackers. While attackers are improving their techniques, traditional solutions based on static and dynamic analysis have been also evolving. In addition to the application code, Android applications ha
Externí odkaz:
http://arxiv.org/abs/2107.03072
Publikováno v:
In Expert Systems With Applications 15 March 2023 214
Autor:
Ameer, Iqra, Bölücü, Necva, Siddiqui, Muhammad Hammad Fahim, Can, Burcu, Sidorov, Grigori, Gelbukh, Alexander
Publikováno v:
In Expert Systems With Applications 1 March 2023 213 Part A
Akademický článek
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Autor:
Bölücü, Necva, Can, Burcu
Publikováno v:
CICLING 2017
The number of word forms in agglutinative languages is theoretically infinite and this variety in word forms introduces sparsity in many natural language processing tasks. Part-of-speech tagging (PoS tagging) is one of these tasks that often suffers
Externí odkaz:
http://arxiv.org/abs/1705.08942
Autor:
Ozen, Serkan, Can, Burcu
In this paper, we build morphological chains for agglutinative languages by using a log-linear model for the morphological segmentation task. The model is based on the unsupervised morphological segmentation system called MorphoChains. We extend Morp
Externí odkaz:
http://arxiv.org/abs/1705.02314
In this paper, we introduce a trie-structured Bayesian model for unsupervised morphological segmentation. We adopt prior information from different sources in the model. We use neural word embeddings to discover words that are morphologically derived
Externí odkaz:
http://arxiv.org/abs/1704.07329
Sparsity is one of the major problems in natural language processing. The problem becomes even more severe in agglutinating languages that are highly prone to be inflected. We deal with sparsity in Turkish by adopting morphological features for part-
Externí odkaz:
http://arxiv.org/abs/1703.03200
Autor:
Can, Burcu
This thesis concentrates on two fields in natural language processing. The main contribution of the thesis is in the field of morphology learning. Morphology is the study of how words are formed combining different language constituents (called morph
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556255