Dynamic “Intelligent Handler” of Frequently Asked Questions Dick Ng’ambi Multimedia Education Group, University of Cape Town, South Africa 7700
[email protected] lacks ability to indicate relative popularity or importance of questions from users perspective.
Abstract In this paper an ongoing research into dynamic intelligent handler of frequently asked questions (FAQs) is described. Although, the use of FAQs is widely used, there is no evidence that most FAQs contain frequently asked questions. This doubt arises due to the lack of a count of the number of times particular questions are asked; lack of indicators of the most recently asked question and a profile of users who asked these questions, and when these questions were last asked. These inadequacies render FAQs less useful for gauging user information needs and for devising appropriate interventions for different categories of users. Thus, a consulting environment in which an “intelligent handler” gets questions, dynamically creates FAQs with views based on user profiles, allows users to respond to questions and choose best response to questions is being developed.
Motivation This project emerged from the need to create an institutional memory of knowledge acquisition through questioning enquiry. Users are provided with a learning activity, which forms a domain in which questions are asked. These user questions create a question pool (figure 1) from which FAQs are dynamically created.
Keywords Frequently Asked Questions, Intelligent FAQs, Dynamic FAQs, Institutional Memory, Consulting environment, FAQ Pareto Analysis Introduction Most FAQs exhibit the following characteristics [5]: no indication of the recently reference questions; no indication of the most frequently asked questions; no indication of “age” of questions; no multiple sources of information sources or “answers”. Tolksdrorf [1] observed that instead of a single answer to a single query, users are interested in integrated results from multiple information sources.
Figure 1: Dynamic FAQ real world abstraction Users may respond to FAQs thus creating a response pool of one-to-many relationship between question and response. With the help of different FAQ views (based on user profiles) users are allowed to choose the best response to a question hence providing useful feedback to educators on possible misunderstandings while dynamically creating user-driven responses to FAQs. This allows the environment to learn from its users and creates an institutional memory of knowledge acquisition through questions and attempting responses to FAQs. Most current programs do not learn from their own users [4] as knowledge is not extracted from users but rather statically encoded in the formal language. Example 1 (below) shows a typical case where an FAQ lacks ability to “learn” from new questions.
These features are important if FAQ are to be used both for feedback purposes and as an effective consulting environment. Previous work in this area such as the answer garden [2] which allows users to seek answers to commonly asked questions and the FAQFinder [3] which retrieves existing questions found in frequently-asked question files do not dynamically create FAQs from user questions and Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. IUI’02, January 13-16, 2002, San Francisco, California, USA. Copyright 2002 ACM 1-58113-459-2/02/0001…$5.00.
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WARNING: If you ask a question that already appears within the FAQ Knowledge Base then your question might be ignored. It is strongly recommended that you use the following search form to search the entire irt.org site before asking a question. Example 1: A typical problem [www.irt.org/utility/question.html]
Description of FAQ Architecture Our current work is concerned with dynamically creating and maintaining FAQs. In this paper we describe the architecture (figure 2) of the environment for creating, searching, frequency distribution ranking and most recent referenced question ranking. An “intelligent handler” creates a question pool and dynamically builds FAQs. We define an Intelligent Handler as a mobile agent that moves through the Internet searching for and interacting with services on the user’s behalf. This mobility is presently limited to scaffolding users when providing responses to FAQs. Users are currently using Ask Jeeves (http://www.aj.com) to provide responses.
Figure 2: Architecture of a Dynamic FAQ Conclusion This paper has described current work on dynamic Intelligent Handler of FAQs. Although the work is in its prototyping phase, preliminary experiments indicate that dynamic FAQs will potentially contribute to creation of knowledge acquisition memory while providing interactive feedback between users and educators. Future work includes dynamic maintenance of user profiles and analysis of questions to gauge understanding of user’s mental intent when they ask questions. Some of the current challenges are: 1) Automating the mapping of many questions to many responses and 2) Creating optimal algorithms for the Q&A Ranker.
Intelligent Question and Answer Handler
This creates and maintains the question and response pools. It has the following three specialised functions: Question Search, Q(uestion) & A(nswer) Handling and Q&A Ranking. Each of these is described below: Question Search
Used to search and retrieve questions pertaining to different user profiles. The search engine searches the question pool of the knowledge base.
References [1] Tolksdorf R, On Coordinating Information Agents and Mobility, In Intelligent Information Agents, Springer, ISBN: 3-540-65112-8, ACM, 1999, pp 397-411
Q&A Handler
The purpose of this handler is to use “found” questions to retrieve “appropriate” responses and to pass the “not found” back to the user with closely related questions with possible responses for the user to choose from.
[2] Ackerman M S, Augmenting the Organizational Memory: A Field Study of Answer Garden, In Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW94), Nov. 1994, pp. 243-252
Q&A Ranker
The Ranker maintains three types of lists: the most recently referenced questions (question age ranking), questions with the greatest likelihood (popularity by frequency) of being referenced and the FAQ pareto analysis (80:20 rule: majority of questions (80%) are based on a few key causes (20%)). By responding to 20% of key causes 80% of questions can be answered. In the question age ranking, questions drop down the list as new questions are referenced. In the popularity by frequency, questions “climb up” the list the more they are referenced.
[3]
Burke R D, Hammond K J, Kulyukin V A, Lytinen S L, Tomuro N & Schoenberg, Question Answering from FAQ Files: Experiences with the FAQ Finder System, 1997, http://citeseer.nj.nec.com/25442.html
[4] Luger F G and Stubblefield A W, Artificial Intelligence – Structures and Strategies for Complex Problem Solving, Addison Wesley, 1998 [5] Ng’ambi D, Dynamic Handling of FAQs, In proceedings of the Education Student’s Research Conference, Cape Town, 28-29 Sept 2001, pp43
Knowledge Base
There are three mappings in the knowledge base: questionresponse-user profile mapping.
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