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.

[1]  Peter W. Foltz,et al.  An introduction to latent semantic analysis , 1998 .

[2]  Rung Ching Chen,et al.  Using Domain Ontology to Implement a Frequently Asked Questions system , 2009, 2009 WRI World Congress on Computer Science and Information Engineering.

[3]  Sheng-Yuan Yang.  Developing of an ontological interface agent with template-based linguistic processing technique for FAQ services , 2009, Expert Syst. Appl..

[4]  Eriks Sneiders,et al.  Automated FAQ Answering: Continued Experience with Shallow Language Understanding , 1999 .

[5]  Chung-Hsien Wu,et al.  Domain-specific FAQ retrieval using independent aspects , 2005, TALIP.

[6]  Vibhu O. Mittal,et al.  Bridging the lexical chasm: statistical approaches to answer-finding , 2000, SIGIR '00.

[7]  Kristian J. Hammond,et al.  Question Answering from Frequently Asked Question Files: Experiences with the FAQ FINDER System , 1997, AI Mag..

[8]  Ren-Hua Wang,et al.  Supervised Learning Approach to Optimize Ranking Function for Chinese FAQ-Finder , 2007, PAKDD.

[9]  Kristian J. Hammond,et al.  FAQ finder: a case-based approach to knowledge navigation , 1995, Proceedings the 11th Conference on Artificial Intelligence for Applications.

[10]  Research and Implementation of Ontological QA System Based on FAQ , 2010, J. Convergence Inf. Technol..

[11]  Che-Yu Yang.  A Semantic FAQ System for Online Community Learning , 2009, J. Softw..

[12]  Juan Luis Castro,et al.  A high-performance FAQ retrieval method using minimal differentiator expressions , 2012, Knowl. Based Syst..

[13]  Hewijin Christine Jiau,et al.  A FAQ Finding Process in Open Source Project Forums , 2010, 2010 Fifth International Conference on Software Engineering Advances.

[14]  Alexander Maedche,et al.  Ontology-Based User Modeling for Knowledge Management Systems , 2003, User Modeling.

[15]  Jungyun Seo,et al.  Cluster-Based FAQ Retrieval Using Latent Term Weights , 2008, IEEE Intelligent Systems.

[16]  Marco Botta,et al.  Learning Profiles Based on Hierarchical Hidden Markov Model , 2005, ISMIS.

[17]  Steven D. Whitehead.  Auto-FAQ: An Experiment in Cyberspace Leveraging , 1995, Comput. Networks ISDN Syst..

[18]  Kehinde K. Agbele,et al.  Applying a Novel Query Reformulation Keywords Algorithm in A Mobile Healthcare Retrieval Context , 2011 .

[19]  Valentin Jijkoun,et al.  Retrieving answers from frequently asked questions pages on the web , 2005, CIKM '05.

[20]  Jungyun Seo,et al.  High-performance FAQ retrieval using an automatic clustering method of query logs , 2006, Inf. Process. Manag..

[21]  Mario Lenz,et al.  Question Answering with Textual CBR , 1998, FQAS.