We introduce an error mining technique for automatically detecting errors in resources that are used in parsing systems. We applied this technique on parsing results produced on several million words by two distinct parsing systems, which share the syntactic lexicon and the pre-parsing processing chain. We were thus able to identify missing and erroneous information in these resources.

Mining a Bilingual Lexicon of MultiWord Expressions : A Statistical Machine Translation Evaluation Perspective This paper describes a method aiming to construct a bilingual lexicon of MultiWord Expressions (MWES) from a French-English parallel corpus. We first extract monolingual MWES from each part of the parallel corpus. The second step consists in acquiring bilingual correspondences of MWEs....

Sentiment lexicon is an important tool for identifying the sentiment polarity of words and texts. How to automatically construct sentiment lexicons has become a research topic in the field of sentiment analysis and opinion mining. Recently there were some attempts to employ representation learning algorithms to construct a sentiment lexicon with sentiment-aware word embedding. However, these me...

For mining intellectual property texts (patents), a broad-coverage lexicon that covers general English words together with terminology from the patent domain is indispensable. The patent domain is very diffuse as it comprises a variety of technical domains (e.g. Human Necessities, Chemistry & Metallurgy and Physics in the International Patent Classification). As a result, collecting a lexicon t...

Center for Biomedical Informatics Research, Stanford University, Stanford, CA Domain specific biomedical lexicons are extensively used by researchers for natural language processing tasks. Currently these lexicons are created manually by expert curators and there is a pressing need for automated methods to compile such lexicons. The Lexicon Builder Web service addresses this need and reduces th...

The growth of web 2.0 application, consumer feedback about product is analyzed to improve the quality of the product. The consumer feedback or reviews are extracted from the social media and then determine the polarity (positive, negative or objective) is called sentiment analysis. It is also known as opinion mining or appraisal extraction or review mining. The sentiment lexicon plays an import...

Sentiment shifters, i.e., words and expressions that can affect text polarity, play an important role in opinion mining. However, the limited ability of current automated opinion mining systems to handle shifters represents a major challenge. The majority of existing approaches rely on a manual list of shifters; few attempts have been made to automatically identify shifters in text. Most of the...

In this paper, we present a combined approach that automatically extracts opinions from Arabic documents. Most research efforts in the area of opinion mining deal with English texts and little work with Arabic text. Unlike English, from our experiments, we found that using only one method on Arabic opinioned documents produce a poor performance. So, we used a combined approach that consists of ...