A joint-space model for cross-lingual distributed representations generalizes language-invariant semantic features. In this paper, we present a matrix cofactorization framework for learning cross-lingual word embeddings. We explicitly define monolingual training objectives in the form of matrix decomposition, and induce cross-lingual constraints for simultaneously factorizing monolingual matric...

Structural isomorphism between languages benefits the performance of cross-lingual applications. We propose an automatic algorithm for cross-lingual similarization of dependency grammars, which automatically learns grammars with high cross-lingual similarity. The algorithm similarizes the annotation styles of the dependency grammars for two languages in the level of classification decisions, an...

Though great progress has been made in the Aspect-Based Sentiment Analysis(ABSA) task through research, most of previous work focuses on English-based ABSA problems, and there are few efforts other languages mainly due to lack training data. In this paper, we propose an approach for performing a Cross-Lingual Aspect Classification (CLASC) which leverages rich resources one language (source lang...

Cross-lingual word embeddings are used for cross-lingual information retrieval or domain adaptations. In this paper, we extend Eigenwords, spectral monolingual word embeddings based on canonical correlation analysis (CCA), to crosslingual settings with sentence-alignment. For incorporating cross-lingual information, CCA is replaced with its generalization based on the spectral graph embeddings....

Objectives: To develop a system that accepts cross-lingual spoken reviews consisting of two to four languages, translate target language text for Indic languages namely Kannada, Hindi, Telugu and/or English termed as cross lingual speech identification and translation system. Methods: Hybridization software engineering models are used in natural pre-processing such noise removal splitting obtai...

Cross-lingual document clustering (CLDC) is the task to automatically organize a large collection of cross-lingual documents into groups considering content or topic. Different from the traditional hard matching strategy, this paper extends traditional generalized vector space model (GVSM) to handle cross-lingual cases, referred to as CLGVSM, by incorporating cross-lingual word similarity measu...

Cross-lingual adaptation aims to learn a prediction model in a label-scarce target language by exploiting labeled data from a labelrich source language. An effective crosslingual adaptation system can substantially reduce the manual annotation effort required in many natural language processing tasks. In this paper, we propose a new cross-lingual adaptation approach for document classification ...