[Ltg] LTG Seminar [Robert Dale 2007-09-17, E6A 357, 11am]

[Marc Tilbrook]

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    LTG Seminar
     - see: http://www.clt.mq.edu.au/Events/Seminars.html

     Monday, 17th September , 2007, 11am
     Macquarie University, E6A, Room 357
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Title: Dialogue Behavior Management in Conversational Recommender Systems
A PhD thesis by Pontus Wärnestål
Presented by Robert Dale

Recently, I was the opponent in a Swedish PhD defense, which meant that I
had to give a one hour presentation of the material in the thesis.

I found the thesis (and the experience!) very interesting, so I aim to give
pretty much the same talk that I gave as part of that process.  I've
provided Pontus's own abstract below, so you can get a sense of what the
thesis is about.

Abstract:

This thesis examines recommendation dialogue, in the context of dialogue
strategy design for conversational recommender systems. The purpose of a
recommender system is to produce personalized recommendations of potentially
useful items from a large space of possible options. In a conversational
recommender system, this task is approached by utilizing natural language
recommendation dialogue for detecting user preferences, as well as for
providing recommendations. The fundamental idea of a conversational
recommender system is that it relies on dialogue sessions to detect,
continuously update, and utilize the user’s preferences in order to predict
potential interest in domain items modeled in a system. Designing the
dialogue strategy management is thus one of the most important tasks for
such systems.

Based on empirical studies as well as design and implementation of
conversational recommender systems, a behavior-based dialogue model called
bcorn is presented. bcorn is based on three constructs, which are presented
in the thesis. It utilizes a user preference modeling framework (preflets)
that supports and utilizes natural language dialogue, and allows for
descriptive, comparative, and superlative preference statements, in various
situations. Another component of bcorn is its message-passing formalism,
pcql, which is a notation used when describing preferential and factual
statements and requests. bcorn is designed to be a generic recommendation
dialogue strategy with conventional, information-providing, and
recommendation capabilities, that each describes a natural chunk of a
recommender agent’s dialogue strategy, modeled in dialogue behavior diagrams
that are run in parallel to give rise to coherent, flexible, and effective
dialogue in conversational recommender systems.

Three empirical studies have been carried out in order to explore the
problem space of recommendation dialogue, and to verify the solutions put
forward in this work. Study I is a corpus study in the domain of movie
recommendations. The result of the study is a characterization of
recommendation dialogue, and forms a base for a first prototype
implementation of a human-computer recommendation dialogue control strategy.
Study II is an end-user evaluation of the acorn system that implements the
dialogue control strategy and results in a verification of the effectiveness
and usability of the dialogue strategy. There are also implications that
influence the refinement of the model that are used in the bcorn dialogue
strategy model. Study III is an overhearer evaluation of a functional
conversational recommender system called CoreSong, which implements the
bcorn model. The result of the study is indicative of the soundness of the
behavior-based approach to conversational recommender system design, as well
as the informativeness, naturalness, and coherence of the individual bcorn
dialogue behaviors.