191,971 research outputs found
Towards OWL-based Knowledge Representation in Petrology
This paper presents our work on development of OWL-driven systems for formal
representation and reasoning about terminological knowledge and facts in
petrology. The long-term aim of our project is to provide solid foundations for
a large-scale integration of various kinds of knowledge, including basic terms,
rock classification algorithms, findings and reports. We describe three steps
we have taken towards that goal here. First, we develop a semi-automated
procedure for transforming a database of igneous rock samples to texts in a
controlled natural language (CNL), and then a collection of OWL ontologies.
Second, we create an OWL ontology of important petrology terms currently
described in natural language thesauri. We describe a prototype of a tool for
collecting definitions from domain experts. Third, we present an approach to
formalization of current industrial standards for classification of rock
samples, which requires linear equations in OWL 2. In conclusion, we discuss a
range of opportunities arising from the use of semantic technologies in
petrology and outline the future work in this area.Comment: 10 pages. The paper has been accepted by OWLED2011 as a long
presentatio
Conversational Sensing
Recent developments in sensing technologies, mobile devices and context-aware
user interfaces have made it possible to represent information fusion and
situational awareness as a conversational process among actors - human and
machine agents - at or near the tactical edges of a network. Motivated by use
cases in the domain of security, policing and emergency response, this paper
presents an approach to information collection, fusion and sense-making based
on the use of natural language (NL) and controlled natural language (CNL) to
support richer forms of human-machine interaction. The approach uses a
conversational protocol to facilitate a flow of collaborative messages from NL
to CNL and back again in support of interactions such as: turning eyewitness
reports from human observers into actionable information (from both trained and
untrained sources); fusing information from humans and physical sensors (with
associated quality metadata); and assisting human analysts to make the best use
of available sensing assets in an area of interest (governed by management and
security policies). CNL is used as a common formal knowledge representation for
both machine and human agents to support reasoning, semantic information fusion
and generation of rationale for inferences, in ways that remain transparent to
human users. Examples are provided of various alternative styles for user
feedback, including NL, CNL and graphical feedback. A pilot experiment with
human subjects shows that a prototype conversational agent is able to gather
usable CNL information from untrained human subjects
Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach
With more advanced manufacturing technologies, small and medium sized enterprises can compete with low-wage labor by providing customized and high quality products. For small production series, robotic systems can provide a cost-effective solution. However, for robots to be able to perform on par with human workers in manufacturing industries, they must become flexible and autonomous in their task execution and swift and easy to instruct. This will enable small businesses with short production series or highly customized products to use robot coworkers without consulting expert robot programmers. The objective of this thesis is to explore programming solutions that can reduce the programming effort of sensor-controlled robot tasks. The robot motions are expressed using constraints, and multiple of simple constrained motions can be combined into a robot skill. The skill can be stored in a knowledge base together with a semantic description, which enables reuse and reasoning. The main contributions of the thesis are 1) development of ontologies for knowledge about robot devices and skills, 2) a user interface that provides simple programming of dual-arm skills for non-experts and experts, 3) a programming interface for task descriptions in unstructured natural language in a user-specified vocabulary and 4) an implementation where low-level code is generated from the high-level descriptions. The resulting system greatly reduces the number of parameters exposed to the user, is simple to use for non-experts and reduces the programming time for experts by 80%. The representation is described on a semantic level, which means that the same skill can be used on different robot platforms. The research is presented in seven papers, the first describing the knowledge representation and the second the knowledge-based architecture that enables skill sharing between robots. The third paper presents the translation from high-level instructions to low-level code for force-controlled motions. The two following papers evaluate the simplified programming prototype for non-expert and expert users. The last two present how program statements are extracted from unstructured natural language descriptions
Controlled Natural Language Processing as Answer Set Programming: an Experiment
Most controlled natural languages (CNLs) are processed with the help of a
pipeline architecture that relies on different software components. We
investigate in this paper in an experimental way how well answer set
programming (ASP) is suited as a unifying framework for parsing a CNL, deriving
a formal representation for the resulting syntax trees, and for reasoning with
that representation. We start from a list of input tokens in ASP notation and
show how this input can be transformed into a syntax tree using an ASP grammar
and then into reified ASP rules in form of a set of facts. These facts are then
processed by an ASP meta-interpreter that allows us to infer new knowledge
Architecture of a Web-based Predictive Editor for Controlled Natural Language Processing
In this paper, we describe the architecture of a web-based predictive text
editor being developed for the controlled natural language PENG^{ASP). This
controlled language can be used to write non-monotonic specifications that have
the same expressive power as Answer Set Programs. In order to support the
writing process of these specifications, the predictive text editor
communicates asynchronously with the controlled natural language processor that
generates lookahead categories and additional auxiliary information for the
author of a specification text. The text editor can display multiple sets of
lookahead categories simultaneously for different possible sentence
completions, anaphoric expressions, and supports the addition of new content
words to the lexicon
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