Bilingual Terminology Mining - Using Brain, not brawn comparable corpora
نویسندگان
چکیده
Current research in text mining favours the quantity of texts over their quality. But for bilingual terminology mining, and for many language pairs, large comparable corpora are not available. More importantly, as terms are defined vis-à-vis a specific domain with a restricted register, it is expected that the quality rather than the quantity of the corpus matters more in terminology mining. Our hypothesis, therefore, is that the quality of the corpus is more important than the quantity and ensures the quality of the acquired terminological resources. We show how important the type of discourse is as a characteristic of the comparable corpus.
منابع مشابه
Using WordNet and Semantic Similarity for Bilingual Terminology Mining from Comparable Corpora
This paper presents an extension of the standard approach used for bilingual lexicon extraction from comparable corpora. We study of the ambiguity problem revealed by the seed bilingual dictionary used to translate context vectors. For this purpose, we augment the standard approach by a Word Sense Disambiguation process relying on a WordNet-based semantic similarity measure. The aim of this pro...
متن کاملWord Co-occurrence Counts Prediction for Bilingual Terminology Extraction from Comparable Corpora
Methods dealing with bilingual lexicon extraction from comparable corpora are often based on word co-occurrence observation and are by essence more effective when using large corpora. In most cases, specialized comparable corpora are of small size, and this particularity has a direct impact on bilingual terminology extraction results. In order to overcome insufficient data coverage and to make ...
متن کاملEfficient Data Selection for Bilingual Terminology Extraction from Comparable Corpora
Comparable corpora are the main alternative to the use of parallel corpora to extract bilingual lexicons. Although it is easier to build comparable corpora, specialized comparable corpora are often of modest size in comparison with corpora issued from the general domain. Consequently, the observations of word co-occurrences which are the basis of context-based methods are unreliable. We propose...
متن کاملCombining Bilingual Terminology Mining and Morphological Modeling for Domain Adaptation in SMT
Translating in technical domains is a wellknown problem in SMT, as the lack of parallel documents causes significant problems of sparsity. We discuss and compare different strategies for enriching SMT systems built on general domain data with bilingual terminology mined from comparable corpora. In particular, we focus on the targetlanguage inflection of the terminology data and present a pipeli...
متن کاملEM-based Hybrid Model for Bilingual Terminology Extraction from Comparable Corpora
In this paper, we present an unsupervised hybrid model which combines statistical, lexical, linguistic, contextual, and temporal features in a generic EMbased framework to harvest bilingual terminology from comparable corpora through comparable document alignment constraint. The model is configurable for any language and is extensible for additional features. In overall, it produces considerabl...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2007