Zobrazeno 1 - 10
of 407
pro vyhledávání: '"FRASINCAR, FLAVIUS"'
Autor:
Schuurmans, Jetze, Frasincar, Flavius
This paper presents a framework in which hierarchical softmax is used to create a global hierarchical classifier. The approach is applicable for any classification task where there is a natural hierarchy among classes. We show empirical results on fo
Externí odkaz:
http://arxiv.org/abs/2308.01210
Autor:
Brauwers, Gianni, Frasincar, Flavius
Publikováno v:
ACM Computing Surveys (CSUR), 2021
With the constantly growing number of reviews and other sentiment-bearing texts on the Web, the demand for automatic sentiment analysis algorithms continues to expand. Aspect-based sentiment classification (ABSC) allows for the automatic extraction o
Externí odkaz:
http://arxiv.org/abs/2203.14266
Autor:
Brauwers, Gianni, Frasincar, Flavius
Publikováno v:
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021
Attention is an important mechanism that can be employed for a variety of deep learning models across many different domains and tasks. This survey provides an overview of the most important attention mechanisms proposed in the literature. The variou
Externí odkaz:
http://arxiv.org/abs/2203.14263
Autor:
Dunn, Bastiaan C., Frasincar, Flavius, Matsiiako, Vladyslav, Boekestijn, David, van der Knaap, Finn
Publikováno v:
In Expert Systems With Applications 15 October 2024 252 Part A
The increasing popularity of the Web has subsequently increased the abundance of reviews on products and services. Mining these reviews for expressed sentiment is beneficial for both companies and consumers, as quality can be improved based on this i
Externí odkaz:
http://arxiv.org/abs/2111.14988
Publikováno v:
The 36th ACM/SIGAPP Symposium on Applied Computing (SAC '21), March 22--26, 2021, Virtual Event, Republic of Korea
Most of the existing recommender systems are based only on the rating data, and they ignore other sources of information that might increase the quality of recommendations, such as textual reviews, or user and item characteristics. Moreover, the majo
Externí odkaz:
http://arxiv.org/abs/2111.08538
Publikováno v:
In Knowledge-Based Systems 21 June 2024 294
Many high performance machine learning models for Aspect-Based Sentiment Classification (ABSC) produce black box models, and therefore barely explain how they classify a certain sentiment value towards an aspect. In this paper, we propose explanation
Externí odkaz:
http://arxiv.org/abs/2103.15927
Data augmentation is a way to increase the diversity of available data by applying constrained transformations on the original data. This strategy has been widely used in image classification but has to the best of our knowledge not yet been used in
Externí odkaz:
http://arxiv.org/abs/2103.15912