Parallel Text Mining for SMT

Problem: given a relatively large collection of parallel texts and a state-of-the-art SMT system, how to incrementally & automatically mine the parallel texts available on the Web. The newly added texts should ensure to improve the current SMT system.

Papers related:

1) Large Scale Parallel Document Mining for Machine Translation. COLING 2010. Link.
2) TBA

Managing news

Link: http://www.managingnews.com/

AlchemyAPI - transforming text into knowledge

http://www.alchemyapi.com/

Intro

AlchemyAPI provides content owners and web developers with a rich suite of content analysis and meta-data annotation tools.

Expose the semantic richness hidden in any content, using named entity extraction, keyword extraction, sentiment analysis, document categorization, concept tagging, language detection, and structured content scraping. Use AlchemyAPI to enhance your website, blog, content management system, or semantic web application.

AlchemyAPI uses statistical natural language processing technology and machine learning algorithms to analyze your content, extracting semantic meta-data: information about people, places, companies, topics, languages, and more.

Mining scientific texts

This post is to collect all papers related to mining scientific texts (entity & relation extraction, summarization, ...).

1) http://www.lrec-conf.org/proceedings/lrec2008/pdf/773_paper.pdf
(Extracting and Querying Relations in Scientific Papers on Language Technology)

2)

Web Services for Text Mining and NLP Tools

http://ontology.csse.uwa.edu.au/

(key request: http://ontology.csse.uwa.edu.au/research/api.pl)