Social media content analysis: Natural language processing and beyond
Publication Type
Book Chapter
Publication Date
2-2017
Abstract
Cross-language mining is a task of text mining dealing with the extraction of entities and their counterparts expressed in different languages. The interested entities may be of various granularities from acronyms, synonyms, cognates, proper names to comparable or parallel corpora. Cross-Language Information Retrieval (CLIR) is a sub-field of information retrieval dealing with the retrieval of documents across language boundaries, i.e., the language of the retrieved documents is not the same as the language of the queries. Cross-language mining usually acts as an effective means to improve the performance of CLIR by complementing the translation resources exploited by CLIR systems.
Discipline
Databases and Information Systems
Research Areas
Data Science and Engineering
Publication
Series on language processing, pattern recognition, and intelligent systems
Volume
3
Editor
Ching Y Suen; Lu Qin
ISBN
9789813223608
Identifier
10.1142/10535
Publisher
World Scientific Publishing
Citation
WONG, Kam-Fai; GAO, Wei; XU, Ruifeng; and LI, Wenjie.
Social media content analysis: Natural language processing and beyond. (2017). Series on language processing, pattern recognition, and intelligent systems. 3,.
Available at: https://ink.library.smu.edu.sg/sis_research/4609
Additional URL
https://doi.org/10.1142/10535