Cross-Language Mining for Acronyms and Their Completions from the Web

2005 ◽  
pp. 113-123 ◽  
Author(s):  
Udo Hahn ◽  
Philipp Daumke ◽  
Stefan Schulz ◽  
Kornél Markó
Keyword(s):  
Cross Language ◽  
The Web

Analysis and Assessment of Cross-Language Question Answering Systems

2018 ◽  
pp. 4471-4479
Author(s):  
Juncal Gutiérrez-Artacho ◽  
María-Dolores Olvera-Lobo
Keyword(s):  
Information Retrieval ◽  
Applied Research ◽  
Question Answering ◽  
General Domain ◽  
Linguistic Resources ◽  
Question Answering Systems ◽  
Cross Language ◽  
Language Question ◽  
The Web

Within the sphere of the Web, the overload of information is more notable than in other contexts. Question answering systems (QAS) are presented as an alternative to the traditional Information Retrieval (IR) systems, seeking to offer precise and understandable answers to factual questions instead of showing the user a list of documents related to a given search . Given that the QAS is presented as a substantial advance in the improvement of IR, it becomes necessary to determine its effectiveness for the final user. With this aim, 7 studies were undertaken to evaluate: a) in the first two, the linguistic resources and tools used in these systems for multilingual retrieval (Research 1; Research 2); and b) the performance and quality of the answers of the main monolingual and multilingual QA of general domain and specialized domain in the Web in response to different types of questions and subjects, so that different evaluation means can be applied (Research 3, Research 4, Research 5, Research 6, Research 7).

Analysis and Assessment of Cross-Language Question Answering Systems

2019 ◽  
pp. 226-236
Author(s):  
Juncal Gutiérrez-Artacho ◽  
María-Dolores Olvera-Lobo
Keyword(s):  
Information Retrieval ◽  
Applied Research ◽  
Question Answering ◽  
General Domain ◽  
Linguistic Resources ◽  
Question Answering Systems ◽  
Cross Language ◽  
Language Question ◽  
The Web

Within the sphere of the web, the overload of information is more notable than in other contexts. Question answering systems (QAS) are presented as an alternative to the traditional information retrieval (IR) systems seeking to offer precise and understandable answers to factual questions instead of showing the user a list of documents related to a given search. Given that the QAS is presented as a substantial advance in the improvement of IR, it becomes necessary to determine its effectiveness for the final user. With this aim, seven studies were undertaken to evaluate: 1) in the first two, the linguistic resources and tools used in these systems for multilingual retrieval (Research 1, Research 2), and 2) the performance and quality of the answers of the main monolingual and multilingual QA of general domain and specialized domain in the web in response to different types of questions and subjects, so that different evaluation means can be applied (Research 3, Research 4, Research 5, Research 6, Research 7).

scholarly journals Embedding Web-Based Statistical Translation Models in Cross-Language Information Retrieval

2003 ◽  
Vol 29 (3) ◽  
pp. 381-419 ◽  
Author(s):  
Wessel Kraaij ◽  
Jian-Yun Nie ◽  
Michel Simard
Keyword(s):  
Information Retrieval ◽  
Low Cost ◽  
Standard Test ◽  
Query Translation ◽  
Web Based ◽  
Parallel Corpora ◽  
Cross Language Information Retrieval ◽  
Cross Language ◽  
Parallel Texts ◽  
The Web

Although more and more language pairs are covered by machine translation (MT) services, there are still many pairs that lack translation resources. Cross-language information retrieval (CLIR) is an application that needs translation functionality of a relatively low level of sophistication, since current models for information retrieval (IR) are still based on a bag of words. The Web provides a vast resource for the automatic construction of parallel corpora that can be used to train statistical translation models automatically. The resulting translation models can be embedded in several ways in a retrieval model. In this article, we will investigate the problem of automatically mining parallel texts from the Web and different ways of integrating the translation models within the retrieval process. Our experiments on standard test collections for CLIR show that the Web-based translation models can surpass commercial MT systems in CLIR tasks. These results open the perspective of constructing a fully automatic query translation device for CLIR at a very low cost.

Improving Cross-Language Information Retrieval by Harnessing the Social Web

2010 ◽  
pp. 277-295
Author(s):  
Diana Irina Tanase ◽  
Epaminondas Kapetanios
Keyword(s):  
Information Retrieval ◽  
Large Scale ◽  
Social Web ◽  
Web Based ◽  
Lexical Resource ◽  
Cross Language Information Retrieval ◽  
The Social ◽  
Current Context ◽  
Cross Language ◽  
The Web

Combining existing advancements in cross-language information retrieval (CLIR) with the new usercentered Web paradigm could allow tapping into Web-based multilingual clusters of language information that are rich, up-to-date in terms of language usage, that increase in size, and have the potential to cater for all languages. In this chapter, we set out to explore existing CLIR systems and their limitations, and we argue that in the current context of a widely adopted social Web, the future of large-scale CLIR and iCLIR systems is linked to the use of the Web as a lexical resource, as a distribution infrastructure, and as a channel of communication between users. Such a synergy will lead to systems that grow organically as more users with different linguistic skills join the network, and that improve in terms of language translations disambiguation and coverage.

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