Results 71 to 80 of about 15,951 (231)

Stock Portfolio Management Based on AI Technology

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting stock performance is crucial for formulating a profitable trading approach aimed at achieving significant gains. In addition, prediction results serve as essential prerequisites for creating and optimizing active investment portfolios.
Alejandro Moreno Alonso, Joaquín Ordieres‐Meré   +1 more
wiley   +1 more source

SemEval-2007 task 07 [PDF]

Proceedings of the 4th International Workshop on Semantic Evaluations - SemEval '07, 2007
This paper presents the coarse-grained English all-words task at SemEval-2007. We describe our experience in producing a coarse version of the WordNet sense inventory and preparing the sense-tagged corpus for the task. We present the results of participating systems and discuss future directions.
NAVIGLI, ROBERTO, K. LITKOWSKI, O. HARGRAVES   +2 more
openaire   +2 more sources

JokeMeter at SemEval-2020 Task 7: Convolutional Humor [PDF]

Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020
This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investigate the system on the official dataset, and we provide more insight to model itself to see how the learned inner features look.
Docekal, Martin, Fajcik, Martin, Jon, Josef, Smrz, Pavel   +3 more
openaire   +2 more sources

Classifier Performance on Long‐Tail Distributions

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 18, Issue 4, August 2025.
ABSTRACT This paper introduces a Gaussian mixture model designed to explore the implications of long‐tailedness on classification performance. Our study reveals that simple under‐specified classifiers are inherently limited in reducing generalization error within this framework, a limitation overcome by well‐specified and even more complex over ...
Artur Pak, Maxat Tezekbayev, Arman Bolatov, Igor Melnykov, Kaisar Dauletbek, Zhenisbek Assylbekov   +5 more
wiley   +1 more source

Assessing State-of-the-Art Sentiment Models on State-of-the-Art Sentiment Datasets

, 2017
There has been a good amount of progress in sentiment analysis over the past 10 years, including the proposal of new methods and the creation of benchmark datasets.
Barnes, Jeremy, Klinger, Roman, Walde, Sabine Schulte im   +2 more
core   +1 more source

BUT-FIT at SemEval-2020 Task 4: Multilingual Commonsense [PDF]

Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020
This paper describes work of the BUT-FIT's team at SemEval 2020 Task 4 - Commonsense Validation and Explanation. We participated in all three subtasks. In subtasks A and B, our submissions are based on pretrained language representation models (namely ALBERT) and data augmentation.
Jon, Josef, Fajčík, Martin, Dočekal, Martin, Smrž, Pavel   +3 more
openaire   +2 more sources

Joint Extraction Method for Spatial Relations in Chinese Geological Texts

Earth and Space Science, Volume 12, Issue 8, August 2025.
Abstract Extracting spatial relations of geological entities is an important prerequisite for achieving natural language processing tasks such as geological knowledge question answering and semantic search, and is an important means to achieve structural reconstruction of unstructured geological data.
Chuan Chen, Xiuguo Liu, Weihua Hua, Xinling Zeng, Zihan Cao, Peng Li, Chunyu Qi, Yu Huang, Jiameng Chen, Wencheng Wei   +9 more
wiley   +1 more source

Multi-task transfer learning for the prediction of entity modifiers in clinical text: application to opioid use disorder case detection

Journal of Biomedical Semantics
Background The semantics of entities extracted from a clinical text can be dramatically altered by modifiers, including entity negation, uncertainty, conditionality, severity, and subject.
Abdullateef I. Almudaifer, Whitney Covington, JaMor Hairston, Zachary Deitch, Ankit Anand, Caleb M. Carroll, Estera Crisan, William Bradford, Lauren A. Walter, Ellen F. Eaton, Sue S. Feldman, John D. Osborne   +11 more
doaj   +1 more source

Aspect-Based Sentiment Analysis of Twitter Influencers to Predict the Trend of Cryptocurrencies Based on Hybrid Deep Transfer Learning Models

IEEE Access, 2023
With the expansion of social networks, sentiment analysis has become one of the hot topics in machine learning. However, in traditional sentiment analysis, the text is considered of a general nature and ignores the different aspects that may exist in the
Kia Jahanbin, Mohammad Ali Zare Chahooki
doaj   +1 more source

Complex Word Identification: Challenges in Data Annotation and System Performance

, 2017
This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task. We use ensemble classifiers to investigate how well computational methods can discriminate between complex and non-complex words.
Malmasi, Shervin, Paetzold, Gustavo, Specia, Lucia, Zampieri, Marcos   +3 more
core   +1 more source