A Review on the Cross and Multilingual Information Retrieval
---
paper_title: Information Storage and Retrieval

paper_content:

An information retrieval system in which a set of distinct information items map to respective nodes in an array of nodes by mutual similarity of the information items, so that similar information items map to nodes at similar positions in the array of nodes; the system comprising: a user control for defining a search criterion for selecting information items; a detector for detecting those positions within the array of nodes corresponding to the selected information items; a graphical user interface for displaying a two-dimensional display array of display points representing those positions within the array of nodes corresponding to the selected information items; and a processor responsive to the selected information items, for providing a representation which is generally representative of the information content of the selected information items.
---
paper_title: Literature review of cross-language information retrieval

paper_content:

Classical Information Retrieval (IR) is the sifting out of the documents most relevant to a user’s information requirement (expressed as a “query”), from a large electronic store of documents. A search engine performs IR by retrieving relevant web pages from the internet. Rather than regarding foreign-language documents simply as unwanted “noise”, Cross Language Information Retrieval allows the user to state their query in one language, and retrieve documents in another. Some CLIR systems use language resources such as bilingual dictionaries to translate the user’s original query, while other systems use machine translation to translate the foreign-language documents beforehand, enabling them to be retrieved by the original query. Problems arise due to ambiguity in language, the use of synonyms to express a single idea, and the lack of context available in translating a short query. This paper will discuss previous work in CLIR, current problems in CLIR, and make recommendations for future work. Keywords-Cross Language Information Retrieval, Lexical Semantics, Disambiguation, Translation.
---
paper_title: Using the web for automated translation extraction in cross-language information retrieval

paper_content:

There have been significant advances in Cross-Language Information Retrieval (CLIR) in recent years. One of the major remaining reasons that CLIR does not perform as well as monolingual retrieval is the presence of out of vocabulary (OOV) terms. Previous work has either relied on manual intervention or has only been partially successful in solving this problem. We use a method that extends earlier work in this area by augmenting this with statistical analysis, and corpus-based translation disambiguation to dynamically discover translations of OOV terms. The method can be applied to both Chinese-English and English-Chinese CLIR, correctly extracting translations of OOV terms from the Web automatically, and thus is a significant improvement on earlier work.
---
paper_title: Comparing cross-language query expansion techniques by degrading translation resources

paper_content:

The quality of translation resources is arguably the most important factor affecting the performance of a cross-language information retrieval system. While many investigations have explored the use of query expansion techniques to combat errors induced by translation, no study has yet examined the effectiveness of these techniques across resources of varying quality. This paper presents results using parallel corpora and bilingual wordlists that have been deliberately degraded prior to query translation. Across different languages, translingual resources, and degrees of resource degradation, pre-translation query expansion is tremendously effective. In several instances, pre-translation expansion results in better performance when no translations are available, than when an uncompromised resource is used without pre-translation expansion. We also demonstrate that post-translation expansion using relevance feedback can confer modest performance gains. Measuring the efficacy of these techniques with resources of different quality suggests an explanation for the conflicting reports that have appeared in the literature.
---
paper_title: Cross-lingual relevance models

paper_content:

We propose a formal model of Cross-Language Information Retrieval that does not rely on either query translation or document translation. Our approach leverages recent advances in language modeling to directly estimate an accurate topic model in the target language, starting with a query in the source language. The model integrates popular techniques of disambiguation and query expansion in a unified formal framework. We describe how the topic model can be estimated with either a parallel corpus or a dictionary. We test the framework by constructing Chinese topic models from English queries and using them in the CLIR task of TREC9. The model achieves performance around 95% of the strong mono-lingual baseline in terms of average precision. In initial precision, our model outperforms the mono-lingual baseline by 20%. The main contribution of this work is the unified formal model which integrates techniques that are essential for effective Cross-Language Retrieval.
---
paper_title: Automatic Cross-Language Retrieval Using Latent Semantic Indexing

paper_content:

We describe a method for fully automated cross-language document retrieval in which no query translation is required. Queries in one language can retrieve documents in other languages (as well as the original language). This is accomplished by a method that automatically constructs a multilingual semantic space using Latent Semantic Indexing (LSI). Strong test results for the cross-language LSI (CLLSI) method are presented for a new French-English collection. We also provide evidence that this automatic method performs comparably to a retrieval method based on machine translation (MT-LSI), and explore several practical training methods. By all available measures, CL-LSI performs quite well and is widely applicable.
---
paper_title: Approximate String Matching Techniques for Effective CLIR Among Indian Languages

paper_content:

Commonly used vocabulary in Indian language documents found on the web contain a number of words that have Sanskrit, Persian or English origin. However, such words may be written in different scripts with slight variations in spelling and morphology. In this paper we explore approximate string matching techniques to exploit this situation of relatively large number of cognates among Indian languages, which are higher when compared to an Indian language and a non-Indian language. We present an approach to identify cognates and make use of them for improving dictionary based CLIR when the query and documents both belong to two different Indian languages. We conduct experiments using a Hindi document collection and a set of Telugu queries and report the improvement due to cognate recognition and translation.
---
paper_title: Dictionary-based techniques for cross-language information retrieval

paper_content:

Cross-language information retrieval (CLIR) systems allow users to find documents written in different languages from that of their query. Simple knowledge structures such as bilingual term lists have proven to be a remarkably useful basis for bridging that language gap. A broad array of dictionary-based techniques have demonstrated utility, but comparison across techniques has been difficult because evaluation results often span only a limited range of conditions. This article identifies the key issues in dictionary-based CLIR, develops unified frameworks for term selection and term translation that help to explain the relationships among existing techniques, and illustrates the effect of those techniques using four contrasting languages for systematic experiments with a uniform query translation architecture. Key results include identification of a previously unseen dependence of pre- and post-translation expansion on orthographic cognates and development of a query-specific measure for translation fanout that helps to explain the utility of structured query methods.
---
paper_title: Cross-Lingual Information Retrieval System for Indian Languages

paper_content:

This paper describes our attempt to build a Cross-Lingual Information Retrieval (CLIR) system as a part of the Indian language sub-task of the main Adhoc monolingual and bilingual track in CLEF competition. In this track, the task required retrieval of relevant documents from an English corpus in response to a query expressed in different Indian languages including Hindi, Tamil, Telugu, Bengali and Marathi. Groups participating in this track were required to submit a English to English monolingual run and a Hindi to English bilingual run with optional runs in rest of the languages. Our submission consisted of a monolingual English run and a Hindi to English cross-lingual run. ::: ::: We used a word alignment table that was learnt by a Statistical Machine Translation (SMT) system trained on aligned parallel sentences, to map a query in the source language into an equivalent query in the language of the document collection. The relevant documents are then retrieved using a Language Modeling based retrieval algorithm. On the CLEF 2007 data set, our official cross-lingual performance was 54.4% of the monolingual performance and in the post submission experiments we found that it can be significantly improved up to 76.3%.
---
paper_title: User-Assisted Query Translation for Interactive Cross-Language Information Retrieval

paper_content:

Interactive Cross-Language Information Retrieval (CLIR), a process in which searcher and system collaborate to find documents that satisfy an information need regardless of the language in which those documents are written, calls for designs in which synergies between searcher and system can be leveraged so that the strengths of one can cover weaknesses of the other. This paper describes an approach that employs user-assisted query translation to help searchers better understand the system's operation. Supporting interaction and interface designs are introduced, and results from three user studies are presented. The results indicate that experienced searchers presented with this new system evolve new search strategies that make effective use of the new capabilities, that they achieve retrieval effectiveness comparable to results obtained using fully automatic techniques, and that reported satisfaction with support for cross-language searching increased. The paper concludes with a description of a freely available interactive CLIR system that incorporates lessons learned from this research.
---
paper_title: UCLIR: a Multilingual Information Retrieval Tool

paper_content:

In this paper the Unicode Cross-Language Information Retrieval system (UCLIR) is described. UCLIR accepts a query in one language and then retrieves relevant documents in any of several languages. The core process involves a suite of technologies including machine translation and standard monolingual information retrieval.
---
paper_title: Supporting Multilingual Information Retrieval in Web Applications: An English-Chinese Web Portal Experiment

paper_content:

Cross-language information retrieval (CLIR) and multilingual information retrieval (MLIR) techniques have been widely studied, but they are not often applied to and evaluated for Web applications. In this paper, we present our research in developing and evaluating a multilingual English-Chinese Web portal in the business domain. A dictionary-based approach has been adopted that combines phrasal translation, co-occurrence analysis, and pre- and post-translation query expansion. The approach was evaluated by domain experts and the results showed that co-occurrence-based phrasal translation achieved a 74.6% improvement in precision when compared with simple word-by-word translation.
---
paper_title: SyDoM: A Multilingual Information Retrieval System for Digital Libraries.

paper_content:

Fluorine-substituted vitamin D compounds, methods for preparation of such compounds and fluorinated intermediate compounds used in such methods are disclosed. The fluorine-substituted vitamin D compounds are characterized by vitamin D-like activity in stimulating intestinal calcium transport and bone mobilization and in promoting the calcification of rachitic bone.
---
paper_title: Evaluating multi-lingual information retrieval and clustering at ULIS

paper_content:

This paper describes our retrieval system for NTCIR-2 Japanese/English CLIR and MLIR tasks. We integrate query and document translation with monolingual retrieval to improve retrieval accuracy, and perform clustering to improve browsing efficiency. We also introduce an entropy-driven technique in evaluating clustering methods.
---
paper_title: Description of NTU Approach to NTCIR3 Multilingual Information Retrieval

paper_content:

This paper deals with Chinese, English and Japanese multilingual information retrieval. Several merging strategies, including raw-score merging, round-robin merging, normalized-score merging, and normalizedby-top-k merging, were investigated. Experimental results show that centralized approach is better than distributed approach. In distributed approach, normalized-by-top-k with consideration of translation penalty outperforms the other merging strategies.
---
paper_title: An Ontology Based Approach to Multilingual Information Retrieval

paper_content:

Today, to effectively meet the needs of users, multilingual information retrieval is an important issue regarding to the continually increasing volume of information in various languages. This paper addresses indexing and retrieval in a trilingual corpus: Arabic, French, English. The proposed system is founded on a knowledge representation formalism, namely semantic graphs which supports a domain ontology. Documents and queries are also represented in this formalism. The domain ontology constitutes the kernel of the system and is used both for indexing and retrieval.
---

Title: A Review on the Cross and Multilingual Information Retrieval

Section 1: Introduction
Description 1: Provide an overview of information retrieval (IR), the importance of cross-lingual IR (CLIR) and multilingual IR (MLIR), and the organization of the paper.

Section 2: IR Methods
Description 2: Discuss classical IR methods and introduce the need for variants like bilingual, cross-lingual, and multilingual IR. Explain different translation methods including query translation, document translation, and the primary tools used for translations (dictionaries, machine translation systems, parallel corpora).

Section 3: Dictionary Based
Description 3: Describe the use of bilingual dictionaries for translation, including translation probabilities and their application in IR.

Section 4: Machine Translation
Description 4: Explain the method of using machine translation systems for translating documents or queries, and discuss its computational challenges.

Section 5: Parallel Corpora
Description 5: Highlight the benefits and challenges of using parallel corpora for translation in IR, and detail the coverage and quality issues associated with corpus-based translation.

Section 6: CLIR
Description 6: Provide a comprehensive overview of Cross-Lingual Information Retrieval, including its goals, methods (primarily translation), and major research problems in the field.

Section 7: CLIR survey for Indian languages and Foreign Languages
Description 7: Summarize the research works and advancements in CLIR for both Indian and foreign languages, including the techniques and evaluation initiatives used.

Section 8: MLIR
Description 8: Outline the concept and significance of Multilingual Information Retrieval, its relationship to traditional IR, and the methods used (query and document translations).

Section 9: MLIR Survey for Indian Languages and Foreign Languages
Description 9: Review the research works and methodologies applied in MLIR for foreign languages, and discuss the lack of works in Indian languages.

Section 10: Conclusion
Description 10: Sum up the findings, challenges, and methodologies in cross-lingual and multi-lingual IR, and describe the importance of ongoing research for efficient and comprehensive information retrieval across languages.