Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Abbas Akkasi"'
Autor:
Abbas Akkasi
Publikováno v:
Natural Language Processing Journal, Vol 9, Iss , Pp 100102- (2024)
The rapid digitization of the economy is transforming the job market, creating new roles and reshaping existing ones. As skill requirements evolve, identifying essential competencies becomes increasingly critical. This paper introduces a novel ensemb
Externí odkaz:
https://doaj.org/article/80be188df2d34b718ae8555f0b0b34bd
Publikováno v:
Applied Sciences, Vol 10, Iss 15, p 5262 (2020)
In this survey, we discuss the task of automatically classifying medical documents into the taxonomy of the International Classification of Diseases (ICD), by the use of deep neural networks. The literature in this domain covers different techniques.
Externí odkaz:
https://doaj.org/article/c0e36dd47b664595a98cbd2d29c4dca5
Word sense induction using leader-follower clustering of automatically generated lexical substitutes
Autor:
Jan Šnajder, Abbas Akkasi
Word Sense Induction (WSI) concerns the automatic identification of the various senses of polysemous words. Any improvement in this process can directly affect the quality of the applications in which knowing the word’s senses is important. For exa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8e75b42b837e77966907f19009eb7d5
https://doi.org/10.1016/j.eswa.2021.115162
https://doi.org/10.1016/j.eswa.2021.115162
Publikováno v:
Iran Journal of Computer Science. 1:187-197
Long-Term Evolution (LTE) is a promising technology to be applied for different applications due to its high penetration, high data rate, reliability, and QoS support. One of the emerging applications for LTE is vehicular networks. Vehicular networks
Autor:
Abbas Akkasi
Publikováno v:
Iran Journal of Computer Science. 1:165-174
Named entity recognition (NER), as one of the crucial tasks of information extraction (IE), has important effect on the quality of its subsequent applications such as answering the question, co-reference resolution, relation discovery, etc. NER can b
Causal relationship extraction from biomedical text using deep neural models: A comprehensive survey
Autor:
Marie-Francine Moens, Abbas Akkasi
Publikováno v:
Journal of Biomedical Informatics. 119:103820
The identification of causal relationships between events or entities within biomedical texts is of great importance for creating scientific knowledge bases and is also a fundamental natural language processing (NLP) task. A causal (cause-effect) rel
Publikováno v:
Applied Intelligence. 48:1965-1978
The class imbalance problem is a key factor that affects the performance of many classification tasks when using machine learning methods. This mainly refers to the problem where the number of samples in certain classes is much greater than in others
Publikováno v:
SemEval@NAACL-HLT
We describe two systems for semantic relation classification with which we participated in the SemEval 2018 Task 7, subtask 1 on semantic relation classification: an SVM model and a CNN model. Both models combine dense pretrained word2vec features an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3687f5a0ea6eb806a79d0d2de7e245a
http://hdl.handle.net/11574/190306
http://hdl.handle.net/11574/190306
Publikováno v:
International Journal of Computer Applications. 125:1-5
Current age is age of information explosion. Ever-expanding of the World Wide Web makes the finding required information difficult. Search engines play a principle role in finding info and a high volume of internet traffic related to them. Despite th
Autor:
Mohammad Ali Zeinaly, Abbas Akkasi
Publikováno v:
International Journal of Computer Applications. 119:7-10
Agents must work. After years of practical research into evolutionary programming, we validate the deployment of the Ethernet, which embodies the appropriate principles of electrical engineering. Our focus in this work is not on whether the seminal m