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Some researches I am interesting in:



Terminology extraction

Terminology extraction identifies and collects candidate terms that occur in a monolingual corpus of a specialised domain. Some questions raise in terminology extraction:
  • the specialised corpus: the delimitation of the specialised domain, its size, a collection of native texts, text genres, communicative intentions in specialised domains;
  • the candidate terms: single terms and multi-word terms;
  • the method to identify the candidate terms in texts;
  • the measures and methods to rank, to filter, to cluster the candidate terms;
  • the definition of a unified framework to evaluate term extraction tools.
Two tools dedicated to terminology extraction in the public domain:
  • TermSuite: a tool suite for multilingual terminology extraction from comparable corpora. This tool suite offers a user-friendly graphical interface for designing UIMA-based tool chains whose components:
    • form a functional architecture,
    • manage 7 languages of 5 different families: English, French, German, Spanish, Latvian, Chinese and Russian.
    • support standardised file formats,
    • extract single- and multi- word terms languages by languages
    • and align them by pairs of languages.
    TermSuite has been developed within TTC project funded from the European Community’s Seventh Framework Programme.
  • ACABIT is a terminology extraction that proposes as output a list of multi-word term (MWT) candidates. It is available for French and English. It has been adapted to Japanese, Malagasy, Spanish and Italian.



Term alignment from comparable corpora

Given two corpora of a specialised domain in two languages, term alignment is about finding for a term in a source language, its translations in a target languages. Some questions that are raised with bilingual terminology extraction from comparable corpora:
  • to ensure a good comparable corpora
  • the vector-based method to align terms from comparable corpora: adopting the vector model, how to obtain the best configuration of parameters to obtain the context the most representative of a meaning of a term, the best ranking of the candidate translations
  • the adaptation of the vector model to compute the context of multi-word terms
  • a unified framework for evaluation term alignment from comparable corpora



Multi-word expressions

  • Multi-word terms
    • Linguistic specification and semantics of multi-word terms
    • Compound term segmentation
  • Term variants
    • Typology of the linguistic operations leading to a term variant
    • Inference of semantic links between terms through term variation
    • Diachronic variants
    • Multilingual variants
  • Collocations



Sentiment analysis

Fine-grained sentiment analysis extract subjectivity textual segments and label them with several features: axiological polarity, discursive role (judgement (moral/ethic), assessment (intellect/ pragmatic/esthetic/affect), agreement and disagreement), enunciative strategy, speaker engagement (does he assume his subjectivity or does he try to hide it?) according to linguistic theories on sentiment language. Fine-grained sentiment analysis require lexical and semantic resources and an sentiment grammar. Some questions raise in sentiment mining:
  • Automatic lexical enhancement of sentiments resources
  • Sentiment topic detection
  • multilingual and multimodal sentiment analysis
The tool Aposis performs fine-grained sentiment analysis in French . It has been developed within the national project Blogoscopie (2006-2008) funded by ANR.
Last Updated ( vendredi, 01 septembre 2017 )
 
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