Stacking
Related Papers
Ensemble Models for Dependency Parsing: Cheap and Good?
Previous work on dependency parsing used various kinds of combination models but a systematic analysis and comparison of these approaches is lacking. In this paper we imple- mented such a …...
Stacking of Dependency and Phrase Structure Parsers
We investigate the stacking of dependency and phrase structure parsers, i.e. we define features from the output of a phrase structure parser for a dependency parser and vice versa. Our …...
Efficient Collective Entity Linking with Stacking
Entity disambiguation works by linking am- biguous mentions in text to their correspond- ing real-world entities in knowledge base. Re- cent collective disambiguation methods en- force coherence among contextual decisions …...
HENRY-CORE: Domain Adaptation and Stacking for Text Similarity
This paper describes a system for automat- ically measuring the semantic similarity be- tween two texts, which was the aim of the 2013 Semantic Textual Similarity (STS) task (Agirre et …...
Automatic Identification of Expressions of Locations in Tweet Messages using Conditional Random Fields
In this paper, we propose an automatic identification model, capable of extract- ing expressions of locations (EoLs) within Twitter messages. Moreover, we partici- pated in the competition of ALTA Shared …...
Neural Network for Heterogeneous Annotations
Multiple treebanks annotated under heteroge- neous standards give rise to the research ques- tion of best utilizing multiple resources for im- proving statistical models. Prior research has focused on discrete …...
Evaluating Recognizing Question Entailment Methods for a Portuguese Community Question-Answering System about Diabetes Mellitus
AbstractThis study describes the development of a Portuguese Community-Question Answering benchmark in the domain of Diabetes Mellitus using a Recognizing Question Entailment (RQE) approach. Given a premise question, RQE aims …...
On the Cost-Effectiveness of Stacking of Neural and Non-Neural Methods for Text Classification: Scenarios and Performance Prediction
Neural network algorithms such as those based on transformers and attention models have ex- celled on Automatic Text Classification (ATC) tasks. However, such enhanced performance comes at high computational costs. …...