Parallel Web Pages Research Articles

Sentence Alignment For Web Page Text Based On Vector Space Model

There exist noisy, unparallel sentences in parallel web pages. Web page structure is subjected to some limitation for sentences alignment task for web page text. The most straightforward way of aligning sentences is using a translation lexicon. However, a major obstacle to this approach is the lack of dictionary for training. This paper presents a method for automatically align Mongolian-Chinese parallel text on the Web via vector space model. Vector space model is an algebraic model for representing any object as vectors of identifiers, such as index terms. In the statistically based vector-space model, a sentence is conceptually represented by a vector of keywords extracted from the text. Extracted keywords are composed by content words, known as terms and the weight of a term in a sentence vector can be determined tf-idf method. CHI is used to compute the association between bilingual words. Once the term weights are determined, the similarity between sentence vectors is computed via cosine measure. The experimental results indicate that the method is accurate and efficient enough to apply without human intervention.

Combining Content-Based and URL-Based Heuristics to Harvest Aligned Bitexts from Multilingual Sites with Bitextor

Nowadays, many websites in the Internet are multilingual and may be considered sources of parallel corpora. In this paper we will describe the free/open-source tool Bitextor, created to harvest aligned bitexts from these multilingual websites, which may be used to train corpusbased machine translation systems. This tool uses the work developed in previous approaches with modifications and improvements in order to obtain a tool as adaptable as possible to make it easier to process any kind of websites and work with any pairs of languages. Content-based and URL-based heuristics and algorithms applied to identify and align the parallel web pages in a website will be described and, finally, some results will be presented to show the functionality of the application and set the future work lines for this project.

CzEng 0.9: Large Parallel Treebank with Rich Annotation

CzEng 0.9: Large Parallel Treebank with Rich Annotation We describe our ongoing efforts in collecting a Czech-English parallel corpus CzEng. The paper provides full details on the current version 0.9 and focuses on its new features: (1) data from new sources were added, most importantly a few hundred electronically available books, technical documentation and also some parallel web pages, (2) the full corpus has been automatically annotated up to the tectogrammatical layer (surface and deep syntactic analysis), (3) sentence segmentation has been refined, and (4) several heuristic filters to improve corpus quality were implemented. In total, we provide a sentence-aligned automatic parallel treebank of about 8.0 million sentences, 93 million English and 82 million Czech words. CzEng 0.9 is freely available for non-commercial research purposes.