Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning

Highly frequent in language and communication, metaphor represents a significant challenge for Natural Language Processing (NLP) applications. Computational work on metaphor has traditionally evolved around the use of hand-coded knowledge, making the systems hard to scale. Recent years have witnessed a rise in statistical approaches to metaphor processing. However, these approaches often requir...

متن کامل

Unsupervised and Semi-Supervised Multilingual Learning for Resource-Poor Languages

Název práce: Neř́ızené a poloř́ızené v́ıcejazyčné učeńı pro jazyky s nedostatkem zdroj̊u Autor: Manh-Ke Tran Katedra: Ústav formálńı a aplikované lingvistiky Vedoućı diplomové práce: RNDr. Daniel Zeman, Ph.D., Ústav formálńı a aplikované lingvistiky & Marco A. Wiering, Assistant professor, Artificial Intelligence department, University of Groningen Abstrakt: Práce se zaměřuje na neř́ızenou morfologi...

متن کامل

Ensemble learning with trees and rules: Supervised, semi-supervised, unsupervised

In this article, we propose several new approaches for post processing a large ensemble of conjunctive rules for supervised, semi-supervised and unsupervised learning problems. We show with various examples that for high dimensional regression problems the models constructed by post processing the rules with partial least squares regression have significantly better prediction performance than ...

متن کامل

Contributions to Unsupervised and Semi-Supervised Learning

This thesis studies two problems in theoretical machine learning. The first part of the thesis investigates the statistical stability of clustering algorithms. In the second part, we study the relative advantage of having unlabeled data in classification problems. Clustering stability was proposed and used as a model selection method in clustering tasks. The main idea of the method is that from...

متن کامل

Splitting the Unsupervised and Supervised Components of Semi-Supervised Learning

In this paper we investigate techniques for semi-supervised learning that split their unsupervised and supervised components — that is, an initial unsupervised phase is followed by a supervised learning phase. We first analyze the relative value of labeled and unlabeled data. We then present methods that perform “split” semi-supervised learning and show promising empirical results.

متن کامل

ذخیره 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: Computational Linguistics

سال: 2017

ISSN: 0891-2017,1530-9312

DOI: 10.1162/coli_a_00275