Cross-language Information Retrieval
Petra Galu\v{s}\v{c}\'akov\'a, Douglas W. Oard, Suraj Nair
TL;DR
This paper reviews the current state and challenges of Cross-Language Information Retrieval (CLIR), which enables searching documents in different languages when the searcher does not understand the document language.
Contribution
It provides a comprehensive overview of CLIR techniques, discusses open research questions, and highlights the need for improved methods in multilingual information retrieval.
Findings
Identifies key challenges in CLIR
Summarizes existing techniques and their limitations
Outlines open research questions in the field
Abstract
Two key assumptions shape the usual view of ranked retrieval: (1) that the searcher can choose words for their query that might appear in the documents that they wish to see, and (2) that ranking retrieved documents will suffice because the searcher will be able to recognize those which they wished to find. When the documents to be searched are in a language not known by the searcher, neither assumption is true. In such cases, Cross-Language Information Retrieval (CLIR) is needed. This chapter reviews the state of the art for CLIR and outlines some open research questions.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsInformation Retrieval and Search Behavior · Topic Modeling · Natural Language Processing Techniques