Identifying Comparable Corpora Using LDA
نویسنده
چکیده
Parallel corpora have applications in many areas of Natural Language Processing, but are very expensive to produce. Much information can be gained from comparable texts, and we present an algorithm which, given any bodies of text in multiple languages, uses existing named entity recognition software and topic detection algorithm to generate pairs of comparable texts without requiring a parallel corpus training phase. We evaluate the system’s performance firstly on data from the online newspaper domain, and secondly on Wikipedia cross-language links.
منابع مشابه
Detecting Highly Confident Word Translations from Comparable Corpora without Any Prior Knowledge
In this paper, we extend the work on using latent cross-language topic models for identifying word translations across comparable corpora. We present a novel precisionoriented algorithm that relies on per-topic word distributions obtained by the bilingual LDA (BiLDA) latent topic model. The algorithm aims at harvesting only the most probable word translations across languages in a greedy fashio...
متن کاملBuilding Comparable Corpora Based on Bilingual LDA Model
Comparable corpora are important basic resources in cross-language information processing. However, the existing methods of building comparable corpora, which use intertranslate words and relative features, cannot evaluate the topical relation between document pairs. This paper adopts the bilingual LDA model to predict the topical structures of the documents and proposes three algorithms of doc...
متن کاملParameter Estimation for LDA-Frames
LDA-frames is an unsupervised approach for identifying semantic frames from semantically unlabeled text corpora, and seems to be a useful competitor for manually created databases of selectional preferences. The most limiting property of the algorithm is such that the number of frames and roles must be predefined. In this paper we present a modification of the LDA-frames algorithm allowing the ...
متن کاملاستخراج پیکره موازی از اسناد قابلمقایسه برای بهبود کیفیت ترجمه در سیستمهای ترجمه ماشینی
Data used for training statistical machine translation method are usually prepared from three resources: parallel, non-parallel and comparable text corpora. Parallel corpora are an ideal resource for translation but due to lack of these kinds of texts, non-parallel and comparable corpora are used either for parallel text extraction. Most of existing methods for exploiting comparable corpora loo...
متن کاملA New Approach to Speeding Up Topic Modeling
Latent Dirichlet allocation (LDA) is a widely-used probabilistic topic modeling paradigm, and recently finds many applications in computer vision and computational biology. In this paper, we propose a fast and accurate batch algorithm, active belief propagation (ABP), for training LDA. Usually batch LDA algorithms require repeated scanning of the entire corpus and searching the complete topic s...
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 2012