Title :
A parallel cross-language retrieval system for patent documents
Author :
Xin Shen;Heyan Huang;Lingzhi Li;Yonggang Huang
Author_Institution :
Beijing Engineering Research Center of High Volume Language Information Processing &
Abstract :
In order to help people obtain useful information from patent documents in different languages. This paper proposes a cross-language retrieval system to search Chinese and English patent documents simultaneously. This system consists of query translation module, document retrieval module and user interaction module. Query translation module is used to translate query based on bilingual dictionaries. Document retrieval module consists of monolingual retrieval system using standard vector space model. In order to retrieve in highly parallel, we use the MapReduce model to calculate the similarity. User interaction module provides users with interactive mechanism used to improve the retrieval accuracy in the system. It contains two parts: the second translation and relevance feedback. The experimental results show that our system has good performance.
Keywords :
"Patents","Dictionaries","Context","Data processing","Accuracy","Machine learning algorithms"
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2015 6th IEEE International Conference on
Print_ISBN :
978-1-4799-8352-0
Electronic_ISBN :
2327-0594
DOI :
10.1109/ICSESS.2015.7339147