A Robust Linguistic Platform for Efficient and Domain specific Web
  Content Analysis
  Web semantic access in specific domains calls for specialized search engines
with enhanced semantic querying and indexing capacities, which pertain both to
information retrieval (IR) and to information extraction (IE). A rich
linguistic analysis is required either to identify the relevant semantic units
to index and weight them according to linguistic specific statistical
distribution, or as the basis of an information extraction process. Recent
developments make Natural Language Processing (NLP) techniques reliable enough
to process large collections of documents and to enrich them with semantic
annotations. This paper focuses on the design and the development of a text
processing platform, Ogmios, which has been developed in the ALVIS project. The
Ogmios platform exploits existing NLP modules and resources, which may be tuned
to specific domains and produces linguistically annotated documents. We show
how the three constraints of genericity, domain semantic awareness and
performance can be handled all together.
