FAQtory: A framework to provide high-quality FAQ retrieval systems

To facilitate access to information, companies usually try to anticipate and answer most typical customer’s questions by creating Frequently Asked Questions (FAQs) lists. In this scenario, FAQ retrieval is the area of study concerned with recovering the most relevant Question/Answer pairs contained in FAQ compilations. Despite the amount of effort that has been devoted to investigate FAQ retrieval methods, how to create an maintain high quality FAQs has received less attention. In this article, we propose an entire framework to use, create and maintain intelligent FAQs. Usage mining techniques have been developed to take advantage of usage information in order to provide FAQ managers with meaningful information to improve their FAQs. Usage mining techniques include weaknesses detection and knowledge gaps discovery. In this way, the management of the FAQ is no longer directed only by expert knowledge but also by users requirements.

► Actual user’s information needs lead the task of FAQ maintenance. ► FAQ managers are not expected to be IR experts-knowledge modelling is not required. ► Summarization and visualization tools present usage information to FAQ managers in a meaningful manner. ► Analysis of user queries helps to automatically discover knowledge gaps in the FAQ.