A cloud of FAQ: A highly-precise FAQ retrieval system for the Web 2.0

• Efficient and automatic manage of large collection of documents.
• No need of handcrafted knowledge modeling.
• Highly-precise answers.
• Improved language coverage of the possible wordings users could employ when querying the system.
• Tag clouds as an interpretable representation mechanism and as a way to improve navigation and learning through the domain of knowledge.

FAQ (Frequency Asked Questions) lists have attracted increasing attention for companies and organizations. There is thus a need for high-precision and fast methods able to manage large FAQ collections. In this context, we present a FAQ retrieval system as part of a FAQ exploiting project. Following the growing trend towards Web 2.0, we aim to provide users with mechanisms to navigate through the domain of knowledge and to facilitate both learning and searching, beyond classic FAQ retrieval algorithms. To this purpose, our system involves two different modules: an efficient and precise FAQ retrieval module and, a tag cloud generation module designed to help users to complete the comprehension of the retrieved information. Empirical results evidence the validity of our approach with respect to a number of state-of-the-art algorithms in terms of the most popular metrics in the field.