Advances In Cross Language Information Retrieval


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Advances in Cross-Language Information Retrieval


Advances in Cross-Language Information Retrieval

Author: Martin Braschler

language: en

Publisher: Springer

Release Date: 2003-11-17


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This book presents the thoroughly refereed post-proceedings of a workshop by the Cross-Language Evaluation Forum Campaign, CLEF 2002, held in Rome, Italy in September 2002. The 43 revised full papers presented together with an introduction and run data in an appendix were carefully reviewed and revised upon presentation at the workshop. The papers are organized in topical sections on systems evaluation experiments, cross language and more, monolingual experiments, mainly domain-specific information retrieval, interactive issues, cross-language spoken document retrieval, and cross-language evaluation issues and initiatives.

Cross-Language Information Retrieval


Cross-Language Information Retrieval

Author: Jian-Yun Nie

language: en

Publisher: Morgan & Claypool Publishers

Release Date: 2010-05-05


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Search for information is no longer exclusively limited within the native language of the user, but is more and more extended to other languages. This gives rise to the problem of cross-language information retrieval (CLIR), whose goal is to find relevant information written in a different language to a query. In addition to the problems of monolingual information retrieval (IR), translation is the key problem in CLIR: one should translate either the query or the documents from a language to another. However, this translation problem is not identical to full-text machine translation (MT): the goal is not to produce a human-readable translation, but a translation suitable for finding relevant documents. Specific translation methods are thus required. The goal of this book is to provide a comprehensive description of the specific problems arising in CLIR, the solutions proposed in this area, as well as the remaining problems. The book starts with a general description of the monolingual IR and CLIR problems. Different classes of approaches to translation are then presented: approaches using an MT system, dictionary-based translation and approaches based on parallel and comparable corpora. In addition, the typical retrieval effectiveness using different approaches is compared. It will be shown that translation approaches specifically designed for CLIR can rival and outperform high-quality MT systems. Finally, the book offers a look into the future that draws a strong parallel between query expansion in monolingual IR and query translation in CLIR, suggesting that many approaches developed in monolingual IR can be adapted to CLIR. The book can be used as an introduction to CLIR. Advanced readers can also find more technical details and discussions about the remaining research challenges in the future. It is suitable to new researchers who intend to carry out research on CLIR. Table of Contents: Preface / Introduction / Using Manually Constructed Translation Systems and Resources for CLIR / Translation Based on Parallel and Comparable Corpora / Other Methods to Improve CLIR / A Look into the Future: Toward a Unified View of Monolingual IR and CLIR? / References / Author Biography

Recent Advances in Example-Based Machine Translation


Recent Advances in Example-Based Machine Translation

Author: M. Carl

language: en

Publisher: Springer Science & Business Media

Release Date: 2003-06-30


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Recent Advances in Example-Based Machine Translation is of relevance to researchers and program developers in the field of Machine Translation and especially Example-Based Machine Translation, bilingual text processing and cross-linguistic information retrieval. It is also of interest to translation technologists and localisation professionals. Recent Advances in Example-Based Machine Translation fills a void, because it is the first book to tackle the issue of EBMT in depth. It gives a state-of-the-art overview of EBMT techniques and provides a coherent structure in which all aspects of EBMT are embedded. Its contributions are written by long-standing researchers in the field of MT in general, and EBMT in particular. This book can be used in graduate-level courses in machine translation and statistical NLP.