649 research outputs found
An analysis of machine translation errors on the effectiveness of an Arabic-English QA system
The aim of this paper is to investigate
how much the effectiveness of a Question
Answering (QA) system was affected
by the performance of Machine
Translation (MT) based question translation.
Nearly 200 questions were selected
from TREC QA tracks and ran through a
question answering system. It was able to
answer 42.6% of the questions correctly
in a monolingual run. These questions
were then translated manually from English
into Arabic and back into English using
an MT system, and then re-applied to
the QA system. The system was able to
answer 10.2% of the translated questions.
An analysis of what sort of translation error
affected which questions was conducted,
concluding that factoid type
questions are less prone to translation error
than others
Miracle’s 2005 Approach to Cross-lingual Information Retrieval
This paper presents the 2005 Miracle’s team approach to Bilingual and Multilingual Information Retrieval. In the multilingual track, we have concentrated our work on the merging process of the results of monolingual runs to get the multilingual overall result, relying on available translations. In the bilingual and multilingual tracks, we have used available translation resources, and in some cases we have using a combining approach
Report of MIRACLE team for the Ad-Hoc track in CLEF 2006
This paper presents the 2006 MIRACLE’s team approach to the AdHoc Information Retrieval track. The experiments for this campaign keep on testing our IR approach. First, a baseline set of runs is obtained, including standard components: stemming, transforming, filtering, entities detection and extracting, and others. Then, a extended set of runs is obtained using several types of combinations of these baseline runs. The improvements introduced for this campaign have been a few ones: we have used an entity recognition and indexing prototype tool into our tokenizing scheme, and we have run more combining experiments for the robust multilingual case than in previous campaigns. However, no significative improvements have been achieved. For the this campaign, runs were submitted for the following languages and tracks: - Monolingual: Bulgarian, French, Hungarian, and Portuguese. - Bilingual: English to Bulgarian, French, Hungarian, and Portuguese; Spanish to French and Portuguese; and French to Portuguese. - Robust monolingual: German, English, Spanish, French, Italian, and Dutch. - Robust bilingual: English to German, Italian to Spanish, and French to Dutch. - Robust multilingual: English to robust monolingual languages. We still need to work harder to improve some aspects of our processing scheme, being the most important, to our knowledge, the entities recognition and normalization
Dublin City University at QA@CLEF 2008
We describe our participation in Multilingual Question Answering at CLEF 2008 using German and English as our source and target languages respectively. The system was built using UIMA (Unstructured Information Management Architecture) as underlying framework
Cross-language Information Retrieval
Two key assumptions shape the usual view of ranked retrieval: (1) that the
searcher can choose words for their query that might appear in the documents
that they wish to see, and (2) that ranking retrieved documents will suffice
because the searcher will be able to recognize those which they wished to find.
When the documents to be searched are in a language not known by the searcher,
neither assumption is true. In such cases, Cross-Language Information Retrieval
(CLIR) is needed. This chapter reviews the state of the art for CLIR and
outlines some open research questions.Comment: 49 pages, 0 figure
Web 2.0, language resources and standards to automatically build a multilingual named entity lexicon
This paper proposes to advance in the current state-of-the-art of automatic Language Resource (LR) building by taking into consideration three elements: (i) the knowledge available in existing LRs, (ii) the vast amount of information available from the collaborative paradigm that has emerged from the Web 2.0 and (iii) the use of standards to improve interoperability. We present a case study in which a set of LRs for different languages (WordNet for English and Spanish and Parole-Simple-Clips for Italian) are
extended with Named Entities (NE) by exploiting Wikipedia and the aforementioned LRs. The practical result is a multilingual NE lexicon connected to these LRs and to two ontologies: SUMO and SIMPLE. Furthermore, the paper addresses an important problem which affects the Computational Linguistics area in the present, interoperability, by making use of the ISO LMF standard to encode this lexicon. The different steps of the procedure (mapping, disambiguation, extraction, NE identification and postprocessing) are comprehensively explained and evaluated. The resulting resource contains 974,567, 137,583 and 125,806 NEs for English, Spanish and Italian respectively. Finally, in order to check the usefulness of the constructed resource, we apply it into a state-of-the-art Question Answering system and evaluate its impact; the NE lexicon improves the system’s accuracy by 28.1%. Compared to previous approaches to build NE repositories, the current proposal represents a step forward in terms of automation, language independence, amount of NEs acquired and richness of the information represented
An evaluation resource for geographic information retrieval
In this paper we present an evaluation resource for geographic information retrieval developed within the Cross Language Evaluation
Forum (CLEF). The GeoCLEF track is dedicated to the evaluation of geographic information retrieval systems. The resource
encompasses more than 600,000 documents, 75 topics so far, and more than 100,000 relevance judgments for these topics. Geographic
information retrieval requires an evaluation resource which represents realistic information needs and which is geographically
challenging. Some experimental results and analysis are reported
iCLEF 2006 Overview: Searching the Flickr WWW photo-sharing repository
This paper summarizes the task design for iCLEF 2006 (the CLEF interactive track).
Compared to previous years, we have proposed a radically new task: searching images
in a naturally multilingual database, Flickr, which has millions of photographs shared
by people all over the planet, tagged and described in a wide variety of languages.
Participants are expected to build a multilingual search front-end to Flickr (using
Flickr’s search API) and study the behaviour of the users for a given set of searching
tasks. The emphasis is put on studying the process, rather than evaluating its outcome
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