Semi-Supervised Learning of Partial Cognates Using Bilingual Bootstrapping

نویسندگان

  • Oana Frunza
  • Diana Inkpen
چکیده

Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Translation tools and for Computer-Assisted Language Learning tools. In this paper we propose a supervised and a semisupervised method to disambiguate partial cognates between two languages: French and English. The methods use only automatically-labeled data; therefore they can be applied for other pairs of languages as well. We also show that our methods perform well when using corpora from different domains.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Word Sense Disambiguation by Semi-supervised Learning

In this paper we propose to use a semi-supervised learning algorithm to deal with word sense disambiguation problem. We evaluated a semi-supervised learning algorithm, local and global consistency algorithm, on widely used benchmark corpus for word sense disambiguation. This algorithm yields encouraging experimental results. It achieves better performance than orthodox supervised learning algor...

متن کامل

Word Sense Disambiguation Using Label Propagation Based Semi-Supervised Learning

Shortage of manually sense-tagged data is an obstacle to supervised word sense disambiguation methods. In this paper we investigate a label propagation based semisupervised learning algorithm for WSD, which combines labeled and unlabeled data in learning process to fully realize a global consistency assumption: similar examples should have similar labels. Our experimental results on benchmark c...

متن کامل

Machine Learning Approaches for Dealing with Limited Bilingual Training Data in Statistical Machine Translation

Statistical Machine Translation (SMT) models learn how to translate by examining a bilingual parallel corpus containing sentences aligned with their human-produced translations. However, high quality translation output is dependent on the availability of massive amounts of parallel text in the source and target languages. There are a large number of languages that are considered low-density, ei...

متن کامل

Graph-based Semi-Supervised Learning of Translation Models from Monolingual Data

Statistical phrase-based translation learns translation rules from bilingual corpora, and has traditionally only used monolingual evidence to construct features that rescore existing translation candidates. In this work, we present a semi-supervised graph-based approach for generating new translation rules that leverages bilingual and monolingual data. The proposed technique first constructs ph...

متن کامل

Semi-Supervised Learning for Semantic Relation Classification using Stratified Sampling Strategy

This paper presents a new approach to selecting the initial seed set using stratified sampling strategy in bootstrapping-based semi-supervised learning for semantic relation classification. First, the training data is partitioned into several strata according to relation types/subtypes, then relation instances are randomly sampled from each stratum to form the initial seed set. We also investig...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006