Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Conversational Recommendation: Theoretical Model and Complexity Analysis   Recommender systems are software applications that help users find items of
interest in situations of information overload in a personalized way, using
knowledge about the needs and preferences of individual users. In
conversational recommendation approaches, these needs and preferences are
acquired by the system in an interactive, multi-turn dialog. A common approach
in the literature to drive such dialogs is to incrementally ask users about
their preferences regarding desired and undesired item features or regarding
individual items. A central research goal in this context is efficiency,
evaluated with respect to the number of required interactions until a
satisfying item is found. This is usually accomplished by making inferences
about the best next question to ask to the user. Today, research on dialog
efficiency is almost entirely empirical, aiming to demonstrate, for example,
that one strategy for selecting questions is better than another one in a given
application. With this work, we complement empirical research with a
theoretical, domain-independent model of conversational recommendation. This
model, which is designed to cover a range of application scenarios, allows us
to investigate the efficiency of conversational approaches in a formal way, in
particular with respect to the computational complexity of devising optimal
interaction strategies. Through such a theoretical analysis we show that
finding an efficient conversational strategy is NP-hard, and in PSPACE in
general, but for particular kinds of catalogs the upper bound lowers to
POLYLOGSPACE. From a practical point of view, this result implies that catalog
characteristics can strongly influence the efficiency of individual
conversational strategies and should therefore be considered when designing new
strategies. A preliminary empirical analysis on datasets derived from a
real-world one aligns with our findings.

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The categories of this paper are: econ
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The categories of this paper are: nucl-ex
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The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol
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The categories of this paper are: cmp-lg
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The categories of this paper are: atom-ph
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The categories of this paper are: nucl-th
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con
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The categories of this paper are: bayes-an
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The categories of this paper are: chao-dyn
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The categories of this paper are: hep-lat
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The categories of this paper are: gr-qc
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The categories of this paper are: eess
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The categories of this paper are: q-alg
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The categories of this paper are: acc-phys