AKT EPrints Archive
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Publications from the Advanced Knowledge Technologies project (AKT).
Mostrando recursos 1 - 20 de 273
1.
Dealing with Dependencies between Content Planning and Surface Realisation in a Pipeline Generation Architecture - Bontcheva, Dr Kalina; Wilks, Prof Yorick
The majority of existing language generation
systems have a pipeline architecture which offers efficient sequential execution of modules, but does not allow decisions about text content to be revised in later stages. However, as exemplified in this paper, in some cases choosing appropriate content can depend on text length and
formatting, which in a pipeline architecture are determined after content planning is completed. Unlike pipelines, interleaved and revision-based architectures can deal with such dependencies but tend to be more expensive computationally. Since our system needs to generate acceptable hypertext explanations reliably and quickly, the pipeline architecture was modified instead to allow additional...
2.
An Expressive Constraint Language for Semantic Web Applications - Gray, Prof Peter; Hui, Dr Kit; Preece, Dr Alun
We present a framework for semantic web applications based on constraint interchange and processing. At the core of the framework is a well-established semantic data model (P/FDM) with an associated expressive constraint language (Colan). To allow data instances to be transported across a network, we map our data model to the RDF Schema specification. To allow constraints to be transported, we define a Constraint Interchange Format (CIF) in the form of an RDF Schema for Colan, allowing each constraint to be defined as a resource in its own right. We show that, because Colan is essentially a syntactically-sugared form of...
3.
A Grammar-Driven Knowledge Acquisition Tool that incorporates Constraint Propagation - White, Dr Simon; Sleeman, Prof Derek
To acquire knowledge that is fit for a specific purpose, it is very desirable to have a structured, declarative expression of the knowledge that is needed. This paper introduces a stand-alone knowledge acquisition tool, called COCKATOO (Constraint-Capable Knowledge Acquisition Tool), which uses constraint technology to specify the knowledge it requires. The language in which these speci-fications are given is based on the meta-language notation of context-free grammars. However, we also took the op-portunity to build a tool that is both more flexible and pow-erful by augmenting context-free grammars with the ex-pressiveness of constraints. COCKATOO was imple-mented using the SCREAMER+ declarative...
4.
Initiating Organizational Memories using Ontology-based Network Analysis as a Bootstrapping Tool - Alani, Harith; Kalfoglou, Yannis; O'Hara, Kieron; Shadbolt, Nigel
An important problem for many kinds of knowledge systems is their initial set-up. It is difficult to choose the right information to include in such systems, and the right information is also a prerequisite for maximizing the uptake and relevance. To tackle this problem, most developers adopt heavyweight solutions and rely on a faithful continuous interaction with users to create and improve content. In this paper, we explore the use of an automatic, lightweight ontology-based solution to the bootstrapping problem, in which domain-describing ontologies are analysed to uncover significant yet implicit relationships between instances. We illustrate the approach by using...
5.
Melita: Active Document Enrichment using Adaptive Information Extraction from Text - Ciravegna, Dr. Fabio; Dingli, Mr. Alexiei; Petrelli, Dr. Daniela
The traditional process of document annotation for
knowledge identification and extraction in the Semantic
Web (SW) is complex and time consuming, as it requires
human manual annotation. There is currently a strong
interest in Text Mining technologies (and in particular in
Human Language-based Technologies), for reducing the
burden of text annotation e.g. for Knowledge Management
[Maybury2001]. In this poster we present Melita,
an annotation interface that uses Adaptive Information
Extraction from texts (IE) for reducing the burden of
text annotation. In Melita, adaptation starts with the
definition of a scenario, including a tag set for annotation
(possibly organized as an...
6.
Adaptive Information Extraction from Text by Rule Induction and Generalisation - Ciravegna, Dr. Fabio
(LP)2 is a covering algorithm for adaptive Information
Extraction from text (IE). It induces
symbolic rules that insert SGML tags into texts
by learning from examples found in a userdefined
tagged corpus. Training is performed in
two steps: initially a set of tagging rules is
learned; then additional rules are induced to
correct mistakes and imprecision in tagging. Induction
is performed by bottom-up generalization
of examples in the training corpus. Shallow
knowledge about Natural Language Processing
(NLP) is used in the generalization process. The
algorithm has a considerable success story.
From a scientific point of view, experiments report
excellent results...
7.
(LP)2, an Adaptive Algorithm for Information Extraction from Web-related Texts - Ciravegna, Dr. Fabio
(LP)2 is an algorithm for adaptive Information
Extraction from Web-related text that induces
symbolic rules by learning from a corpus tagged
with SGML tags. Induction is performed by
bottom-up generalisation of examples in a
training corpus. Training is performed in two
steps: initially a set of tagging rules is learned;
then additional rules are induced to correct
mistakes and imprecision in tagging. Shallow
NLP is used to generalise rules beyond the flat
word structure. Generalization allows a better
coverage on unseen texts, as it limits data
sparseness and overfitting in the training phase.
In experiments on publicly available corpora the...
8.
User Involvement in Adaptive Information Extraction: Position Paper - Ciravegna, Dr. Fabio; Petrelli, Dr. Daniella
In the last years, research on adaptive Information Extraction from text (IE) has largely focused on algorithms and systems adaptable to new Web-related applications/ scenarios by users with analysts knowledge, i.e. knowledge on the domain/scenario only, [Kushme rick 1997], [Califf 1998], [Muslea 1998], [Freitag 1999], [Soderland 1999], [Freitag 2000], [Ciravegna 2001]. Successful comme rcial products have been created and there is an increasing interest on IE in the Internet market. The more the focus is on the user, the more the need for user-specific tools arises. Most of the current approaches are based on an adaptation phase in which the...
9.
User-System Cooperation in Document Annotation based on Information Extraction - Ciravegna, Dr. Fabio; Dingli, Mr. Alexiei; Petrelli, Dr. Daniella; Wilks, Prof. Yorick
The process of document annotation for the Semantic Web is complex and time consuming, as it requires a great deal of manual annotation. Information extraction from texts (IE) is a technology used by some very recent systems for reducing the burden of annotation. The integration of IE systems in
annotation tools is quite a new development and there is still the necessity of thinking the impact of the IE system on the whole annotation process. In this paper we initially discuss a number of requirements for the use of IE as upport
for annotation. Then we present and discuss a...
10.
S-CREAM Semi-automatic CREAtion of
Metadata - Handschuh, Dr. Siegfried; Staab, Dr. Steffen; Ciravegna, Dr. Fabio
Richly interlinked, machine-understandable data constitute
the basis for the Semantic Web. We provide a framework, S-CREAM,that allows for creation of metadata and is trainable for a speci¯c domain. Annotating web documents is one of the major techniques for creating metadata on the web. The implementation of S-CREAM, Ont-O-Mat supports now the semi-automatic annotation of web pages. This semi-
automatic annotation is based on the information extraction component Amilcare. Ont-O-Mat extract with the help of Amilcare knowledge structure from web pages through the use of knowledge extraction rules. These rules are the result of a learning-cycle based on already annotated pages.
11.
User-Centred Onlology Learning for Knowledge Management - Brewster, Mr. Christopher; Ciravegna, Dr. Fabio; Wilks, Prof. Yorick
Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisa-tions). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an...
12.
Challenges in Information Extraction from Text for Knowledge
Management - Ciravegna, Dr. Fabio
Nowadays, most knowledge is stored in an unstructured textual format. We cant query it in simple
ways, thus automatic systems cant use the contained knowledge and humans cant easily manage it. The
traditional knowledge management process for knowledge engineers has been to manually identify and
extract knowledgea complex and time-consuming process that requires a great deal of manual input. As
an example consider the collection of interviews to experts (protocols) and their analysis by knowledge
engineers in order to codify, model and extract the knowledge of an expert in a particular domain. In this
context, information extraction from texts is one of the most promising areas...
13.
Techniques for Automated Taxonomy Building: Towards Ontologies for Knowledge Management - Brewster, Mr. Christopher
Ontologies have become widely accepted as the main method for representing knowledge in Knowledge Management (KM) applica-tions. Given the continuous and rapid change and dynamic nature of knowledge in all fields, automated methods for construct-ing ontologies are of great importance. All ontologies or taxonomies currently in use have been hand built and require consider-able manpower to keep up to date. Taxono-mies are less logically rigorous than ontolo-gies, and in this paper we consider the re-quirements for a system which automatically constructed taxonomies. There are a number of potentially useful methods for construct-ing hierarchically organised concepts from a collection of texts...
14.
Knowledge Maintenance and the Frame Problem - Brewster, Mr. Christopher
Knowledge maintenance is a major challenge for both knowledge management and the Semantic Web. Operating over the Semantic Web, there will be a network of collaborating agents, each with their own ontologies or knowledge bases. Change in the knowledge state of one agent may need to be propagated across a number of agents and their associated ontologies. The challenge is to decide how to propagate a change of knowl-edge state. The effects of a change in knowledge state cannot be known in advance, and so an agent cannot know who should be informed unless it adopts a simple tell everyone...
15.
Knowledge Life Cycle Management over a Distributed Architecture - Schorlemmer, Dr Marco; Potter, Dr Stephen; Robertson, Dr David; Sleeman, Prof Derek
In order to address problems stemming from the dynamic nature of distributed systems, there is a need to be able to express the often neglected notions of the evolution and change of the knowledge components of such systems. This need becomes more pressing when one considers the potential of the Internet for distributed knowledge-based problem solving --- and the pragmatic issues surrounding knowledge integrity.
In this paper, we introduce a formal calculus for describing transformations in the `life cycles' of knowledge components, along with ideas about the nature of distributed environments in which the ideas underpinning the calculus can be realised....
16.
Enabling Services for Distributed Environments: Ontology Extraction and Knowledge-Base Characterisation - Sleeman, Prof Derek; Robertson, Dr David; Potter, Dr Stephen; Schorlemmer, Dr Marco
Existing knowledge base resources have the potential to be valuable components of the Semantic Web and similar knowledge-based environments. However, from the perspective of these environments, these resources are often undercharacterised, lacking the ontological and structural characterisation that would enable them to be exploited fully.
In this paper we discuss two currently independent services, both integrated with their environment via a brokering mechanism. The first of these services is an ontology extraction tool, which can be used to identify ontological knowledge implicit in a knowledge base. The second service involves characterising a given knowledge base in terms of the topic it...
17.
Duality in Knowledge Sharing - Schorlemmer, Dr Marco
I propose a formalisation of knowledge sharing scenarios that aims at capturing the crucial role played by an existing duality between ontological theories to be merged and particular situations to be linked. I use diagrams in the Chu category and cocones and colimits over these diagrams to account for the reliability and optimality of knowledge sharing systems and show the advantage of this approach by re-analysing a system that shares knowledge between a probabilistic logic program and Bayesian belief networks.
18.
Automated Support for Composition of Transformational Components in Knowledge Engineering - Schorlemmer, Dr Marco; Robertson, Dr David; Potter, Dr Stephen
The knowledge engineering world provides a rich source of software components for transforming formally expressed knowledge on a large scale, such as induction systems, knowledge base refiners and ontology merging tools. Although most of these systems have been designed as stand-alone components, there is interest in making them accessible on the Web, with the ultimate goal in mind that a knowledge engineer should be able, with a small amount of intellectual effort, to locate and assemble sequences of these components to perform complex transformations on large repositories of knowledge. The sorts of transformations used in knowledge engineering are not always...
19.
Knowledge Acquisition for Knowledge Management: Position Paper - Brewster, Mr Christopher; Ciravegna, Dr. Fabio; Wilks, Prof. Yorick
Knowledge is only of value when it can be used effectively and efficiently. The management of knowledge is a key element in extracting its value. In this position paper we have outlined how we are addressing the issue of automating the Knowledge Acquisition process in order to reduce both required time and cost of KA, and subjectivity in the resulting ontology. Overall we believe, this will make knowledge management not only more acceptable in a commercial environment but also contribute to the overall productivity of the economy.
20.
Identifying Communities of Practice through Ontology Network Analysis - Alani, Harith; Dasmahapatra, Srinandan; O'Hara, Kieron; Shadbolt, Nigel
Communities of practicegroups of individuals interested in a particular job, procedure, or work domaininformally swap insights on work-related tasks, often through quick chats by the water cooler. They act as corporate memories, transfer best practice, provide mechanisms for situated learning, and act as foci for innovation. Increasingly, organizations are harnessing communities of practice to carry out important knowledge management functions. However, a significant first step is identifying the community, which often doesnt designate itself as such, and its members, who dont know they belong! So, this step involves determining which people in a community of practice have common interests in...
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