Joint Event Extraction Model based on Multi-feature Fusion
نویسندگان
چکیده
منابع مشابه
Combination Model for Sentiment Classification Based on Multi-feature Fusion
Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. This paper focuses on the word level sentiment classification. A combination model for word level sentiment classification based on multi-feature fusion is proposed in this paper. Firstly, different combinations models of various features are gotten and the Naive Bayes classifier is tr...
متن کاملGlacier Information Extraction Based on Multi-feature Combination Model
As a typical landform class of Qinghai-Tibetan Plateau, glacier is widely distributed in alpine terrain. However, field measurement is impossible in those areas because of complex terrain and adverse weather. At first, on the basis of analyzing the features of glacier image spectrum, object shape, spatial relations and environment distribution including terrain and climate, this paper combines ...
متن کاملmortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولMulti-Layer Model Based on Multi-Scale and Multi-Feature Fusion for SAR Images
A multi-layer classification approach based on multi-scales and multi-features (ML–MFM) for synthetic aperture radar (SAR) images is proposed in this paper. Firstly, the SAR image is partitioned into superpixels, which are local, coherent regions that preserve most of the characteristics necessary for extracting image information. Following this, a new sparse representation-based classification...
متن کاملJoint Event Extraction Based on Skip-Window Convolutional Neural Networks
Traditional approaches to the task of ACE event extraction are either the joint model with elaborately designed features which may lead to generalization and data-sparsity problems, or the word-embedding model based on a twostage, multi-class classification architecture, which suffers from error propagation since event triggers and arguments are predicted in isolation. This paper proposes a nov...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2020
ISSN: 1877-0509
DOI: 10.1016/j.procs.2020.06.066