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Cross-Lingual Information Retrieval

Cross-Lingual Information Retrieval (CLIR) is a retrieval task in which search queries and candidate documents are written in different languages. CLIR can be very useful in some scenarios. For example, a reporter may want to search foreign language news to obtain different perspectives for her story; an inventor may explore the patents in another country to understand prior art.

Papers

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Showing 51–68 of 68 papers

TitleStatusHype
Cross-Lingual Learning-to-Rank with Shared Representations—0
Unsupervised Cross-Lingual Information Retrieval using Monolingual Data OnlyCode0
Learning Multilingual Embeddings for Cross-Lingual Information Retrieval in the Presence of Topically Aligned Corpora—0
A Resource-Light Method for Cross-Lingual Semantic Textual SimilarityCode0
Evaluating Translation Quality and CLIR Performance of Query Sessions—0
Bag-of-Words Forced Decoding for Cross-Lingual Information Retrieval—0
A Probabilistic Translation Method for Dictionary-based Cross-lingual Information Retrieval in Agglutinative Languages—0
Learning to Translate: A Query-Specific Combination Approach for Cross-Lingual Information Retrieval—0
Findings of the 2014 Workshop on Statistical Machine Translation—0
Multilingual Test Sets for Machine Translation of Search Queries for Cross-Lingual Information Retrieval in the Medical Domain—0
Building a Dataset of Multilingual Cognates for the Romanian Lexicon—0
A Supervised Model for Extraction of Multiword Expressions, Based on Statistical Context Features—0
Cross-Lingual Information Retrieval and Semantic Interoperability for Cultural Heritage Repositories—0
MT Quality Estimation: The CMU System for WMT’13—0
Chinese Characters Mapping Table of Japanese, Traditional Chinese and Simplified Chinese—0
Biomedical Chinese-English CLIR Using an Extended CMeSH Resource to Expand Queries—0
HunOr: A Hungarian---Russian Parallel Corpus—0
Adaptation of Statistical Machine Translation Model for Cross-Lingual Information Retrieval in a Service Context—0
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