Results 11 to 20 of about 155,742 (245)

SAppKG: Mobile App Recommendation Using Knowledge Graph and Side Information-A Secure Framework

IEEE Access, 2023
Due to the rapid development of technology and the widespread usage of smartphones, the number of mobile applications is exponentially growing. Finding a suitable collection of apps that aligns with users’ needs and preferences can be challenging.
Daksh Dave, Aditya Sharma, Shafi'i Muhammad Abdulhamid, Adeel Ahmed, Adnan Akhunzada, Rashid Amin   +5 more
doaj   +1 more source

Advances and challenges in semantic communications: A systematic review

National Science Open, 2023
Inspired by the recent success of machine learning (ML), the concept of semantic communication introduced by Weaver in 1949 has gained significant attention and has become a promising research direction.
Zhang Ping, Liu Yiming, Song Yile, Zhang Jiaxiang   +3 more
doaj   +1 more source

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

Computers, 2019
The vision of On-the-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language.
Frederik S. Bäumer, Joschka Kersting, Michaela Geierhos   +2 more
doaj   +1 more source

Speech Emotion Recognition Using Semantic Information [PDF]

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021
Speech emotion recognition is a crucial problem manifesting in a multitude of applications such as human computer interaction and education. Although several advancements have been made in the recent years, especially with the advent of Deep Neural Networks (DNN), most of the studies in the literature fail to consider the semantic information in the ...
Tzirakis, Panagiotis, Nguyen, Anh, Zafeiriou, Stefanos, Schuller, Björn W.   +3 more
openaire   +2 more sources

Keyphrase Extraction Combining Word and Document Embeddings

Jisuanji kexue yu tansuo, 2021
With the increasing amount of text data in various application fields, how to quickly and accurately extract the main information has become the main task of keyphrase extraction.
ZU Xian, XIE Fei, LIU Xiaojian
doaj   +1 more source

DA-FSOD: A Novel Data Augmentation Scheme for Few-Shot Object Detection

IEEE Access, 2023
Deep learning techniques continue to be used in various applications in recent years. However, when it is difficult to obtain adequate training samples, the performance of the depth model will degrade.
Jian Yao, Tianyun Shi, Xiaoping Che, Jie Yao, Liuyi Wu   +4 more
doaj   +1 more source

Predicting Informativeness Of Semantic Triples [PDF]

Proceedings of the Conference Recent Advances in Natural Language Processing - Deep Learning for Natural Language Processing Methods and Applications, 2021
Many automatic semantic relation extraction\ud tools extract subject-predicate-object triples\ud from unstructured text. However, a large quantity of these triples merely represent background knowledge. We explore using full texts\ud of biomedical publications to create a training\ud corpus of informative and important semantic\ud triples based on the ...
openaire   +2 more sources

Discourse Semantics with Information Structure [PDF]

Journal of Semantics, 2018
The property of projection poses a challenge to formal semantic theories, due to its apparent non-compositional nature. Projected content is therefore typically analyzed as being different from and independent of asserted content. Recent evidence, however, suggests that these types of content in fact closely interact, thereby calling for a more ...
Venhuizen, Noortje J., Bos, Johan, Hendriks, Petra, Brouwer, Harm   +3 more
openaire   +2 more sources

Finding One’s Bearings in the Hyperparameter Landscape of a Wide-Kernel Convolutional Fault Detector

IEEE Access
State-of-the-art algorithms are reported to be almost perfect at distinguishing the vibrations arising from healthy and damaged machine bearings, according to benchmark datasets at least. However, what about their application to new data?
Dan Hudson, Jurgen van den Hoogen, Martin Atzmueller   +2 more
doaj   +1 more source

A Method for LSTM-Based Trajectory Modeling and Abnormal Trajectory Detection

IEEE Access, 2020
Nowadays, massive data has been brought by the rapid development of technology. When finding whether trajectory to be detected is abnormal under the premise of given normal trajectories, we innovatively propose 1) Seq2Seq model based on LSTM prediction ...
Yufan Ji, Lunwen Wang, Weilu Wu, Hao Shao, Yanqing Feng   +4 more
doaj   +1 more source