233 research outputs found
Collaborating on Referring Expressions
This paper presents a computational model of how conversational participants
collaborate in order to make a referring action successful. The model is based
on the view of language as goal-directed behavior. We propose that the content
of a referring expression can be accounted for by the planning paradigm. Not
only does this approach allow the processes of building referring expressions
and identifying their referents to be captured by plan construction and plan
inference, it also allows us to account for how participants clarify a
referring expression by using meta-actions that reason about and manipulate the
plan derivation that corresponds to the referring expression. To account for
how clarification goals arise and how inferred clarification plans affect the
agent, we propose that the agents are in a certain state of mind, and that this
state includes an intention to achieve the goal of referring and a plan that
the agents are currently considering. It is this mental state that sanctions
the adoption of goals and the acceptance of inferred plans, and so acts as a
link between understanding and generation.Comment: 32 pages, 2 figures, to appear in Computation Linguistics 21-
Distributional Measures of Semantic Distance: A Survey
The ability to mimic human notions of semantic distance has widespread
applications. Some measures rely only on raw text (distributional measures) and
some rely on knowledge sources such as WordNet. Although extensive studies have
been performed to compare WordNet-based measures with human judgment, the use
of distributional measures as proxies to estimate semantic distance has
received little attention. Even though they have traditionally performed poorly
when compared to WordNet-based measures, they lay claim to certain uniquely
attractive features, such as their applicability in resource-poor languages and
their ability to mimic both semantic similarity and semantic relatedness.
Therefore, this paper presents a detailed study of distributional measures.
Particular attention is paid to flesh out the strengths and limitations of both
WordNet-based and distributional measures, and how distributional measures of
distance can be brought more in line with human notions of semantic distance.
We conclude with a brief discussion of recent work on hybrid measures
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