Exploiting Wikipedia for cross-lingual and multilingual information retrieval

2012 ◽  
Vol 74 ◽  
pp. 26-45 ◽  
Author(s):  
P. Sorg ◽  
P. Cimiano
Keyword(s):  
Information Retrieval ◽  
Multilingual Information Retrieval ◽  
Cross Lingual

scholarly journals The data-driven Bulgarian WordNet: BTBWN

2018 ◽  
Author(s):  
Petya Osenova ◽  
Kiril Simov
Keyword(s):  
Information Retrieval ◽  
Machine Translation ◽  
Semantic Information ◽  
Data Driven ◽  
Lexical Resources ◽  
Multilingual Information Retrieval ◽  
Cross Lingual ◽  
Princeton Wordnet ◽  
Word Senses

The data-driven Bulgarian WordNet: BTBWNThe paper presents our work towards the simultaneous creation of a data-driven WordNet for Bulgarian and a manually annotated treebank with semantic information. Such an approach requires synchronization of the word senses in both - syntactic and lexical resources, without limiting the WordNet senses to the corpus or vice versa. Our strategy focuses on the identification of senses used in BulTreeBank, but the missing senses of a lemma also have been covered through exploration of bigger corpora. The identified senses have been organized in synsets for the Bulgarian WordNet. Then they have been aligned to the Princeton WordNet synsets. Various types of mappings are considered between both resources in a cross-lingual aspect and with respect to ensuring maximum connectivity and potential for incorporating the language specific concepts. The mapping between the two WordNets (English and Bulgarian) is a basis for applications such as machine translation and multilingual information retrieval. Oparty na danych WordNet bułgarski: BTBWNW artykule przedstawiono naszą pracę na rzecz jednoczesnej budowy opartego na danych wordnetu dla języka bułgarskiego oraz ręcznie oznaczonego informacjami semantycznymi banku drzew. Takie podejście wymaga uzgodnienia znaczeń słów zarówno w zasobach składniowych, jak i leksykalnych, bez ograniczania znaczeń umieszczanych w wordnecie do tych obecnych w korpusie, jak i odwrotnie. Nasza strategia koncentruje się na identyfikacji znaczeń stosowanych w BulTreeBank, przy czym brakujące znaczenia lematu zostały również zbadane przez zgłębienie większych korpusów. Zidentyfikowane znaczenia zostały zorganizowane w synsety bułgarskiego wordnetu, a następnie powiązane z synsetami Princeton WordNet. Rozmaite rodzaje rzutowań są rozpatrywane pomiędzy obydwoma zasobami w kontekście międzyjęzykowym, a także w odniesieniu do zapewnienia maksymalnej łączności i możliwości uwzględnienia pojęć specyficznych dla języka bułgarskiego. Rzutowanie między dwoma wordnetami (angielskim i bułgarskim) jest podstawą dla aplikacji, takich jak tłumaczenie maszynowe i wielojęzyczne wyszukiwanie informacji.

Issues and Challenges in Building Multilingual Information Access Systems

2013 ◽  
pp. 171-202
Author(s):  
Vasudeva Varma ◽  
Aditya Mogadala
Keyword(s):  
Machine Learning ◽  
Information Retrieval ◽  
Query Processing ◽  
Information Access ◽  
Knowledge Based ◽  
Research Areas ◽  
Multilingual Information Retrieval ◽  
Cross Language Information Retrieval ◽  
Cross Lingual ◽  
Cross Language

In this chapter, the authors start their discussion highlighting the importance of Cross Lingual and Multilingual Information Retrieval and access research areas. They then discuss the distinction between Cross Language Information Retrieval (CLIR), Multilingual Information Retrieval (MLIR), Cross Language Information Access (CLIA), and Multilingual Information Access (MLIA) research areas. In addition, in further sections, issues and challenges in these areas are outlined, and various approaches, including machine learning-based and knowledge-based approaches to address the multilingual information access, are discussed. The authors describe various subsystems of a MLIA system ranging from query processing to output generation by sharing their experience of building a MLIA system and discuss its architecture. Then evaluation aspects of the MLIA and CLIA systems are discussed at the end of this chapter.

A study of user profile representation for personalized cross-language information retrieval

2016 ◽  
Vol 68 (4) ◽  
pp. 448-477 ◽  
Author(s):  
Dong Zhou ◽  
Séamus Lawless ◽  
Xuan Wu ◽  
Wenyu Zhao ◽  
Jianxun Liu
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
User Profile ◽  
User Profiles ◽  
Content Type ◽  
Cross Language Information Retrieval ◽  
Cross Lingual ◽  
Cross Language ◽  
Representation Techniques ◽  
Comprehensive Study

Purpose – With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach – The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings – Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level. Originality/value – Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

scholarly journals MIRACLE Approaches to Multilingual Information Retrieval: A Baseline for Future Research

2004 ◽  
pp. 210-219 ◽  
Author(s):  
José L. Martínez ◽  
Julio Villena ◽  
Jorge Fombella ◽  
Ana G. Serrano ◽  
Paloma Martínez ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Future Research ◽  
Multilingual Information Retrieval
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