  Customer reviews represent a very rich data source from which we can extract
very valuable information about different online shopping experiences. The
amount of the collected data may be very large especially for trendy items
(products, movies, TV shows, hotels, services...), where the number of
available customers' opinions could easily surpass thousands. In fact, while a
good number of reviews could indeed give a hint about the quality of an item, a
potential customer may not have time or effort to read all reviews for the
purpose of making an informed decision (buying, renting, booking...). Thus, the
need for the right tools and technologies to help in such a task becomes a
necessity for the buyer as for the seller. My research goal in this thesis is
to develop reputation systems that can automatically provide E-commerce
customers with valuable information to support them during their online
decision-making process by mining online reviews expressed in natural language.
