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Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision [article]

Yixin Cao and Lei Hou and Juanzi Li and Zhiyuan Liu and Chengjiang Li and Xu Chen and Tiansi Dong
2018 arXiv   pre-print
Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases.  ...  It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts.  ...  One remedy is to use existing multi-lingual resources (i.e. multilingual KB).  ... 
arXiv:1811.10776v1 fatcat:rkyiznw2hvdjhdy4fylkxw4fay

Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision

Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Chengjiang Li, Xu Chen, Tiansi Dong
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases.  ...  It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts.  ...  One remedy is to use existing multi-lingual resources (i.e. multilingual KB).  ... 
doi:10.18653/v1/d18-1021 dblp:conf/emnlp/0002HLLLCD18 fatcat:bmbfxf7bb5clljirnliytkagou

Legal document retrieval across languages: topic hierarchies based on synsets [article]

Carlos Badenes-Olmedo, Jose-Luis Redondo-Garcia, Oscar Corcho
2019 arXiv   pre-print
Cross-lingual annotations of legislative texts enable us to explore major themes covered in multilingual legal data and are a key facilitator of semantic similarity when searching for similar documents  ...  Multilingual probabilistic topic models have recently emerged as a group of semi-supervised machine learning models that can be used to perform thematic explorations on collections of texts in multiple  ...  according to their relevance (i.e. semantic similarity) to the query text regardless of the language used.  ... 
arXiv:1911.12637v1 fatcat:g7nqfyztmbbb7kmsu2hro4h2s4

A Framework for Building a Multilingual Industrial Ontology: Methodology and a Case Study for Building Smartphone English-Arabic Ontology

Amany K. Alnahdi
2021 International journal of Web & Semantic Technology  
In addition, multi-lingual ontologies can also help in commercial transactions.  ...  This research paper provides a framework model for building industrial multilingual ontologies which include Corpus Determination, Filtering, Analysis, Ontology Building, and Ontology Evaluation.  ...  ACKNOWLEDGEMENTS "This work was conducted using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes  ... 
doi:10.5121/ijwest.2021.12302 fatcat:yze3t4uidbcqnna63ydejleai4

Citius at SemEval-2017 Task 2: Cross-Lingual Similarity from Comparable Corpora and Dependency-Based Contexts

Pablo Gamallo
2017 Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)  
The evaluation of the results show that our method is competitive with other cross-lingual strategies, even those using aligned and parallel texts.  ...  Our method uses comparable corpora and syntactic dependencies to extract count-based and transparent bilingual distributional contexts.  ...  Besides, in the cross-lingual task, we have built the models with non-parallel corpora instead of using aligned and parallel texts.  ... 
doi:10.18653/v1/s17-2034 dblp:conf/semeval/Gamallo17 fatcat:t2bml5rn75dqpibygfet67ky7a

Adversarial Multi-lingual Neural Relation Extraction

Xiaozhi Wang, Xu Han, Yankai Lin, Zhiyuan Liu, Maosong Sun
2018 International Conference on Computational Linguistics  
Multi-lingual relation extraction aims to find unknown relational facts from text in various languages.  ...  To address these issues, we propose an adversarial multi-lingual neural relation extraction (AMNRE) model, which builds both consistent and individual representations for each sentence to consider the  ...  Then, construct a multi-lingual NRE (MNRE) model to jointly represent text of multiple languages to enhance RE.  ... 
dblp:conf/coling/WangHL0S18 fatcat:z3nyacma75de3gg2wbmva4tugu

Expanding the Text Classification Toolbox with Cross-Lingual Embeddings [article]

Meryem M'hamdi, Robert West, Andreea Hossmann, Michael Baeriswyl, and Claudiu Musat
2019 arXiv   pre-print
for CLTC; and we move from bi- to multi-lingual word embeddings.  ...  Transfer-based approaches, such as Cross-Lingual Text Classification (CLTC) - the task of categorizing texts written in different languages into a common taxonomy, are a promising solution to the emerging  ...  Cross-Lingual Text Classification using Pre-trained Embeddings The different variations of plain text classification models to which pre-trained embeddings are directly fed are represented in Fig. 1 .  ... 
arXiv:1903.09878v2 fatcat:h3ho57z64bea5e3f36lfh2lymy

SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, Janyce Wiebe
2016 Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)  
While prior evaluations constrained themselves to just monolingual snippets of text, the 2016 shared task includes a pilot subtask on computing semantic similarity on cross-lingual text snippets.  ...  Semantic Textual Similarity (STS) seeks to measure the degree of semantic equivalence between two snippets of text.  ...  Introduction Semantic Textual Similarity (STS) assesses the degree to which the underlying semantics of two segments of text are equivalent to each other.  ... 
doi:10.18653/v1/s16-1081 dblp:conf/semeval/AgirreBCDGMRW16 fatcat:oyct7jmwsvg7ppgpv7u4vnlcii

Towards Zero-shot Cross-lingual Image Retrieval and Tagging [article]

Pranav Aggarwal, Ritiz Tambi, Ajinkya Kale
2021 arXiv   pre-print
We also demonstrate how a cross-lingual model can be used for downstream tasks like multi-lingual image tagging in a zero shot manner.  ...  We try to bridge this gap with a zero-shot approach for learning multi-modal representations using cross-lingual pre-training on the text side.  ...  We experiment with two state-of-theart cross-lingual models -LASER [3] and Multi-lingual USE (or mUSE) [6, 38] .  ... 
arXiv:2109.07622v1 fatcat:hvegymlhybgjhjqgj3ysnljmlu

A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis [article]

Qi Zhang, Jie Zhou, Qin Chen, Qingchun Bai, Jun Xiao, Liang He
2022 arXiv   pre-print
First, we design an adversarial embedding adapter for learning an informative and robust representation by capturing implicit semantic information from diverse multi-lingual embeddings adaptively.  ...  Notably, we propose a Knowledge-Enhanced Adversarial Model () with both implicit distributed and explicit structural knowledge to enhance the cross-lingual transfer.  ...  Moreover, the performance of various multi-lingual embeddings is very different due to various multi-lingual embeddings having different semantic information.  ... 
arXiv:2205.15514v1 fatcat:6hqs2ok5qrfmdmnrkusqtaesya

Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems [article]

Zihan Liu, Genta Indra Winata, Zhaojiang Lin, Peng Xu, Pascale Fung
2019 arXiv   pre-print
using existing bilingual dictionaries.  ...  It leverages very few task-related parallel word pairs to generate code-switching sentences for learning the inter-lingual semantics across languages.  ...  EN denotes an English text, IT denotes an Italian text, and CS denotes a code-switching text (i.e., a mixed-language sentence).  ... 
arXiv:1911.09273v1 fatcat:bazx4femujbntnwgb4j6bjmfxm

Multi-Lingual Dialogue Act Recognition with Deep Learning Methods

Jiří Martínek, Pavel Král, Ladislav Lenc, Christophe Cerisara
2019 Interspeech 2019  
Cross-lingual Model The cross-lingual model relies on a semantic space transforma- tion.  ...  Multi-lingual DA Recognition This section starts by describing the two methods we use to achieve multi-linguality.  ... 
doi:10.21437/interspeech.2019-1691 dblp:conf/interspeech/MartinekKLC19 fatcat:nwhkm4bn3nbbbopfrhyfw5z4ru

Multi-Lingual Sentiment Analysis of Social Data Based on Emotion-Bearing Patterns

Carlos Argueta, Yi-Shin Chen
2014 Proceedings of the Second Workshop on Natural Language Processing for Social Media (SocialNLP)  
The experiments demonstrate that our approach performs an effective multi-lingual sentiment analysis of microblog data with little more than a 100 emotion-bearing patterns.  ...  The proposed multi-lingual framework consists of two stages: Filter and Refine approach.  ...  Multi-lingual Sentiment Analysis on Microblog Data The following Filter and Refine approach is employed to determine the polarity of posts from microblog data.  ... 
doi:10.3115/v1/w14-5906 dblp:conf/acl-socialnlp/ArguetaC14 fatcat:qijt4ywjmnarhaal46dzp2praq

Scalable Cross-lingual Document Similarity through Language-specific Concept Hierarchies

Carlos Badenes-Olmedo, José Luis Redondo-García, Oscar Corcho
2019 Proceedings of the 10th International Conference on Knowledge Capture - K-CAP '19  
Multilingual probabilistic topic models have recently emerged as a group of semi-supervised machine learning models that can be used to perform thematic explorations on collections of texts in multiple  ...  With the ongoing growth in number of digital articles in a wider set of languages and the expanding use of different languages, we need annotation methods that enable browsing multi-lingual corpora.  ...  Multi-lingual topic models discover language-specific descriptions of each topic from documents in multi-lingual corpora.  ... 
doi:10.1145/3360901.3364444 dblp:conf/kcap/Badenes-OlmedoG19 fatcat:ddnsb5mohfgollh7sd6u253ofm

Attention-Informed Mixed-Language Training for Zero-Shot Cross-Lingual Task-Oriented Dialogue Systems

Zihan Liu, Genta Indra Winata, Zhaojiang Lin, Peng Xu, Pascale Fung
2020 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
using existing bilingual dictionaries.  ...  It leverages very few task-related parallel word pairs to generate code-switching sentences for learning the inter-lingual semantics across languages.  ...  EN denotes an English text, IT denotes an Italian text, and CS denotes a code-switching text (i.e., a mixed-language sentence).  ... 
doi:10.1609/aaai.v34i05.6362 fatcat:h322k7c6zfa5rnfy2g5vnxs2pe
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