Search (67 results, page 4 of 4)

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Date

26.12.2007 20:22:11

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Source

Dynamism and stability in knowledge organization: Proceedings of the 6th International ISKO-Conference, 10-13 July 2000, Toronto, Canada. Ed.: C. Beghtol et al

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Abstract

The authors propose a method for automatically generating Japanese-English bilingual thesauri based on bilingual corpora. The term bilingual thesaurus refers to a set of bilingual equivalent words and their synonyms. Most of the methods proposed so far for extracting bilingual equivalent word clusters from bilingual corpora depend heavily on word frequency and are not effective for dealing with low-frequency clusters. These low-frequency bilingual clusters are worth extracting because they contain many newly coined terms that are in demand but are not listed in existing bilingual thesauri. Assuming that single language-pair-independent methods such as frequency-based ones have reached their limitations and that a language-pair-dependent method used in combination with other methods shows promise, the authors propose the following approach: (a) Extract translation pairs based on transliteration patterns; (b) remove the pairs from among the candidate words; (c) extract translation pairs based on word frequency from the remaining candidate words; and (d) generate bilingual clusters based on the extracted pairs using a graph-theoretic method. The proposed method has been found to be significantly more effective than other methods.

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Abstract

Welcome to the very first issue of EuropeanaTech Insight, a multimedia publication about research and development within the EuropeanaTech community. EuropeanaTech is a very active community. It spans all of Europe and is made up of technical experts from the various disciplines within digital cultural heritage. At any given moment, members can be found presenting their work in project meetings, seminars and conferences around the world. Now, through EuropeanaTech Insight, we can share that inspiring work with the whole community. In our first three issues, we're showcasing topics discussed at the EuropeanaTech 2015 Conference, an exciting event that gave rise to lots of innovative ideas and fruitful conversations on the themes of data quality, data modelling, open data, data re-use, multilingualism and discovery. Welcome, bienvenue, bienvenido, Välkommen, Tervetuloa to the first Issue of EuropeanaTech Insight. Are we talking your language? No? Well I can guarantee you Europeana is. One of the European Union's great beauties and strengths is its diversity. That diversity is perhaps most evident in the 24 different languages spoken in the EU. Making it possible for all European citizens to easily and seamlessly communicate in their native language with others who do not speak that language is a huge technical undertaking. Translating documents, news, speeches and historical texts was once exclusively done manually. Clearly, that takes a huge amount of time and resources and means that not everything can be translated... However, with the advances in machine and automatic translation, it's becoming more possible to provide instant and pretty accurate translations. Europeana provides access to over 40 million digitised cultural heritage offering content in over 33 languages. But what value does Europeana provide if people can only find results in their native language? None. That's why the EuropeanaTech community is collectively working towards making it more possible for everyone to discover our collections in their native language. In this issue of EuropeanaTech Insight, we hear from community members who are making great strides in machine translation and enrichment tools to help improve not only access to data, but also how we retrieve, browse and understand it.

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Abstract

I will not attempt to draw a sharp distinction between retrieval and filtering in this survey. Although my own work on adaptive cross-language text filtering has led me to make this distinction fairly carefully in other presentations (c.f., (Oard 1997b)), such an proach does little to help understand the fundamental techniques which have been applied or the results that have been obtained in this case. Since it is still common to view filtering (detection of useful documents in dynamic document streams) as a kind of retrieval, will simply adopt that perspective here.

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Content

Enthält die Beiträge: GREFENSTETTE, G.: The Problem of Cross-Language Information Retrieval; DAVIS, M.W.: On the Effective Use of Large Parallel Corpora in Cross-Language Text Retrieval; BALLESTEROS, L. u. W.B. CROFT: Statistical Methods for Cross-Language Information Retrieval; Distributed Cross-Lingual Information Retrieval; Automatic Cross-Language Information Retrieval Using Latent Semantic Indexing; EVANS, D.A. u.a.: Mapping Vocabularies Using Latent Semantics; PICCHI, E. u. C. PETERS: Cross-Language Information Retrieval: A System for Comparable Corpus Querying; YAMABANA, K. u.a.: A Language Conversion Front-End for Cross-Language Information Retrieval; GACHOT, D.A. u.a.: The Systran NLP Browser: An Application of Machine Translation Technology in Cross-Language Information Retrieval; HULL, D.: A Weighted Boolean Model for Cross-Language Text Retrieval; SHERIDAN, P. u.a. Building a Large Multilingual Test Collection from Comparable News Documents; OARD; D.W. u. B.J. DORR: Evaluating Cross-Language Text Filtering Effectiveness