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otherentity ID: datasparsity

Related Papers

The Haves and the Have-Nots: Leveraging Unlabelled Corpora for Sentiment Analysis

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

Expensive feature engineering based on WordNet senses has been shown be useful for document level sentimentto classification. A plausible reason for such a performance improvement is the reduction in data …...

40270

Class-Based Language Modeling for Translating into Morphologically Rich Languages

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

Class-based language modeling (LM) is a long-studied and effective approach to overcome data sparsity in the context of n-gram model training. In statistical machine translation (SMT), differ- ent forms of …...

5661

Stripping Adjectives: Integration Techniques for Selective Stemming in SMT Systems

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

In this paper we present an approach to re- duce data sparsity problems when translat- ing from morphologically rich languages into less inflected languages by selectively stemming certain word types. …...

3136

Advancing Linguistic Features and Insights by Label-informed Feature Grouping: An Exploration in the Context of Native Language Identification

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractWe propose a hierarchical clustering approach designed to group linguistic features for supervised machine learning that is inspired by variationist linguistics. The method makes it possible to abstract away from …...

4545

Consistent Word Segmentation, Part-of-Speech Tagging and Dependency Labelling Annotation for Chinese Language

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractIn this paper, we propose a new annotation approach to Chinese word segmentation, part-of-speech (POS) tagging and dependency labelling that aims to overcome the two major issues in traditional morphology-based …...

4586

Learning grammatical categories using paradigmatic representations: Substitute words for language acquisition

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractLearning syntactic categories is a fundamental task in language acquisition. Previous studies show that co-occurrence patterns of preceding and following words are essential to group words into categories. However, the …...

4549

Predicting proficiency levels in learner writings by transferring a linguistic complexity model from expert-written coursebooks

Authors: nan

Publication: TIPSTER (2016)

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AbstractThe lack of a sufficient amount of data tailored for a task is a well-recognized problem for many statistical NLP methods. In this paper, we explore whether data sparsity can …...

4419

Addressing the Data Sparsity Issue in Neural AMR Parsing

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractNeural attention models have achieved great success in different NLP tasks. However, they have not fulfilled their promise on the AMR parsing task due to the data sparsity issue. In …...

43132

A LSTM Approach with Sub-Word Embeddings for Mongolian Phrase Break Prediction

Authors: nan

Publication: TIPSTER (2018)

DOI: nan

AbstractIn this paper, we first utilize the word embedding that focuses on sub-word units to the Mongolian Phrase Break (PB) prediction task by using Long-Short-Term-Memory (LSTM) model. Mongolian is an …...

5311

Solving Data Sparsity for Aspect Based Sentiment Analysis Using Cross-Linguality and Multi-Linguality

Authors: nan

Publication: TIPSTER (2018)

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AbstractEfficient word representations play an important role in solving various problems related to Natural Language Processing (NLP), data mining, text mining etc. The issue of data sparsity poses a great …...

22323

Out-of-Task Training for Dialog State Tracking Models

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractDialog state tracking (DST) suffers from severe data sparsity. While many natural language processing (NLP) tasks benefit from transfer learning and multi-task learning, in dialog these methods are limited by …...

3773

Incorporating translation quality estimation into Chinese-Korean neural machine translation

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractExposure bias and poor translation diversity are two common problems in neural machine trans-lation (NMT) which are caused by the general of the teacher forcing strategy for training inthe NMT …...

5582

Semantic Representation for Dialogue Modeling

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractAlthough neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities. To this end, we exploit Abstract …...

8442