Evaluation of Cross-Language Information Retrieval Systems

2002 ◽  
Keyword(s):  
Information Retrieval ◽  
Retrieval Systems ◽  
Cross Language Information Retrieval ◽  
Information Retrieval Systems ◽  
Cross Language

scholarly journals A Comparison of Retrieval Result Relevance Judgments Between American and Chinese Users

2020 ◽  
Vol 28 (3) ◽  
pp. 148-168
Author(s):  
Jin Zhang ◽  
Yuehua Zhao ◽  
Xin Cai ◽  
Taowen Le ◽  
Wei Fei ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Relevance Judgment ◽  
Search Tasks ◽  
Retrieval Systems ◽  
Relevance Judgments ◽  
Cross Language Information Retrieval ◽  
Subject Categories ◽  
Information Retrieval Systems ◽  
Retrieval Result ◽  
Cross Language

Relevance judgment plays an extremely significant role in information retrieval. This study investigates the differences between American users and Chinese users in relevance judgment during the information retrieval process. 384 sets of relevance scores with 50 scores in each set were collected from 16 American users and 16 Chinese users as they judged retrieval records from two major search engines based on 24 predefined search tasks from 4 domain categories. Statistical analyses reveal that there are significant differences between American assessors and Chinese assessors in relevance judgments. Significant gender differences also appear within both the American and the Chinese assessor groups. The study also revealed significant interactions among cultures, genders, and subject categories. These findings can enhance the understanding of cultural impact on information retrieval and can assist in the design of effective cross-language information retrieval systems.

scholarly journals Cross Language Information Retrieval (CLIR): A Survey of Approaches for Exploring Web Across Languages

2020 ◽  
Vol 10 (1) ◽  
pp. 326-332
Keyword(s):  
Information Retrieval ◽  
The Internet ◽  
Native Languages ◽  
Retrieval Systems ◽  
Private Organizations ◽  
Almost Everywhere ◽  
Cross Language Information Retrieval ◽  
Information Retrieval Systems ◽  
Cross Language ◽  
Monolingual Information Retrieval

In the era of globalization, internet being accessible and affordable has gained huge popularity and is widely being used almost everywhere by Government, private organizations, companies, banks, etc. as well as by individuals. It has empowered its users to contribute to the creation of information on web enabling them to use their native languages which consequently has drastically increased the volume of web-accessible documents available in languages other than English. This exponential growth of information on the internet has also induced several challenges before the information retrieval systems. Most of the present monolingual information retrieval systems can retrieve documents in the language of query only, missing the information in other languages that may be more relevant to the user. The need of information retrieval systems to become multilingual has given rise to the research in Cross Language Information Retrieval (CLIR) which can cross the language barriers and retrieve more relevant results from documents in different languages. This article is a review of motivation, issues, work and challenges related to various CLIR approaches. Starting with the most fundamental approaches of translation, it is attempted to study and present a review of more advanced approaches for enhancing the retrieval results in CLIR proposed by various researchers working in this domain.

Building Proximity Models for Cross Language Information Retrieval

2015 ◽  
Vol 1 ◽  
pp. 8
Author(s):  
Lam Tung Giang ◽  
Vo Trung Hung ◽  
Huynh Cong Phap
Keyword(s):  
Information Retrieval ◽  
Information Systems ◽  
Bag Of Words ◽  
Retrieval Performance ◽  
Average Precision ◽  
Ranking Models ◽  
Retrieval Systems ◽  
Cross Language Information Retrieval ◽  
Information Retrieval Systems ◽  
Cross Language

In information retrieval systems, the proximity of query terms has been employed to enable ranking models to go beyond the ”bag of words” assumption and it can promote scores of documents where the matched query terms are close to each other. In this article, we study the integration of proximity models into cross-language information retrieval systems. The new proximity models are proposed and incorporated into existing cross-language information systems by combining the proximity score and the original score to re-rank retrieved documents. The experiment results show that the proposed models can help to improve the retrieval performance by 4%-7%, in terms of Mean Average Precision.

English-Marathi Cross Language Information Retrieval System

2017 ◽  
Vol 7 (8) ◽  
pp. 112
Author(s):  
Kalyani Lokhande ◽  
Dhanashree Tayade
Keyword(s):  
Information Retrieval ◽  
Retrieval System ◽  
Information Retrieval System ◽  
Indian Languages ◽  
Query Translation ◽  
Retrieval Systems ◽  
Cross Language Information Retrieval ◽  
Different Types ◽  
Information Retrieval Systems ◽  
Cross Language

Nowadays, different types of content in different languages are available on World Wide Web and their usage is increasing rapidly. Cross Language Information Retrieval (CLIR) deals with retrieval of documents in another language than the language of the requested query. Various researchers worked on Cross Language Information Retrieval systems for Indian languages using different translation approaches. There is still CLIR system to be developed which allow user to retrieve Marathi documents when English query is given. In the proposed English to Marathi Cross Language Information Retrieval system, translation is based on query translation approach. The proposed system retrieves Marathi documents depending on matching terms in query. The performance of the proposed system is improved by query pre-processing and query expansion using WordNet.

MorphoSaurus

2005 ◽  
Vol 44 (04) ◽  
pp. 537-545 ◽  
Author(s):  
S. Schulz ◽  
U. Hahn ◽  
K. Markó
Keyword(s):  
Document Retrieval ◽  
Retrieval Performance ◽  
Direct Translation ◽  
Retrieval Systems ◽  
Cross Language Information Retrieval ◽  
Information Retrieval Systems ◽  
Document Collection ◽  
Cross Language ◽  
Medical Document ◽  
User Queries

Summary Objectives: We propose an interlingua-based indexing approach to account for the particular challenges that arise in the design and implementation of cross-language document retrieval systems for the medical domain. Methods: Documents, as well as queries, are mapped to a language-independent conceptual layer on which retrieval operations are performed. We contrast this approach with the direct translation of German queries to English ones which, subsequently, are matched against English documents. Results: We evaluate both approaches, interlingua-based and direct translation, on a large medical document collection, the OHSUMED corpus. A substantial benefit for interlingua-based document retrieval using German queries on English texts is found, which amounts to 93% of the (monolingual) English baseline. Conclusions: Most state-of-the-art cross-language information retrieval systems translate user queries to the language(s) of the target documents. In contradistinction to this approach, translating both documents and user queries into a language-independent, concept-like representation format is more beneficial to enhance cross-language retrieval performance.

Relevance Predictability in Information Retrieval Systems

1967 ◽  
Vol 06 (02) ◽  
pp. 45-51 ◽  
Author(s):  
A. Kent ◽  
J. Belzer ◽  
M. Kuhfeerst ◽  
E. D. Dym ◽  
D. L. Shirey ◽  
...  
Keyword(s):  
Information Retrieval ◽  
Experimental Conditions ◽  
Treatment Groups ◽  
Retrieval Systems ◽  
Significant Difference ◽  
Information Retrieval Systems ◽  
High Predictability ◽  
Intermediate Response ◽  
Quantitative Indicators ◽  
Level Of Processing

An experiment is described which attempts to derive quantitative indicators regarding the potential relevance predictability of the intermediate stimuli used to represent documents in information retrieval systems. In effect, since the decision to peruse an entire document is often predicated upon the examination of one »level of processing« of the document (e.g., the citation and/or abstract), it became interesting to analyze the properties of what constitutes »relevance«. However, prior to such an analysis, an even more elementary step had to be made, namely, to determine what portions of a document should be examined.An evaluation of the ability of intermediate response products (IRPs), functioning as cues to the information content of full documents, to predict the relevance determination that would be subsequently made on these documents by motivated users of information retrieval systems, was made under controlled experimental conditions. The hypothesis that there might be other intermediate response products (selected extracts from the document, i.e., first paragraph, last paragraph, and the combination of first and last paragraph), that would be as representative of the full document as the traditional IRPs (citation and abstract) was tested systematically. The results showed that:1. there is no significant difference among the several IRP treatment groups on the number of cue evaluations of relevancy which match the subsequent user relevancy decision on the document;2. first and last paragraph combinations have consistently predicted relevancy to a higher degree than the other IRPs;3. abstracts were undistinguished as predictors; and4. the apparent high predictability rating for citations was not substantive.Some of these results are quite different than would be expected from previous work with unmotivated subjects.

Sign in / Sign up

Export Citation Format

Share Document