Technical Reports and Project Deliverables
2010
Miguel Garcia, Anastasia Izmaylova, and Sibylle Schupp.
Extending Scala with database query capability.
Journal of Object Technology, 8, July-August 2010.
To appear. Preprint at
http://www.sts.tu-harburg.de/people/mi.garcia/pubs/2009/jot/scalaql-preprint.pdf.
Bibtex entry
Oliver Gries, Ralf Möller, Anahita Nafissi, Maurice Rosenfeld, Kamil
Sokolski, and Michael Wessel.
Meta-level reasoning engine, Report on meta-level reasoning for
disambiguation and preference elicitation.
Technical report, CASAM Project Deliverable D3.4, 2010.
Bibtex entry Paper (PDF)
Abstract
In the CASAM deliverable D3.3 an agent was presented that builds interpretations upon multimedia annotations by incrementally consuming analysis results as well as input from a human annotator. These interpretations are based on background knowledge of a specific domain, e.g. an environmental domain as it was exemplarily chosen for the CASAM project. As a result of the interpretation process, multiple interpretation alternatives are possible. A preference measure for the alternatives is realised by a probabilistic scoring function. As an extension of the interpretation agent, a mechanism for meta-level reasoning is presented with the aim to disambiguate interpretation alternatives. This is achieved by generating queries from a set of interpretation alternatives and stating them to the human annotator. Queries themselves are ranked by an importance value, representing the benefit of an answer to a query for the disambiguation process.
After a revision of the interpretation process the query generation mechanism is explained, followed by a detailed description of different query types, together with the format they are communicated in. Furthermore, the processing of responses to queries is addressed.
Oliver Gries, Ralf Möller, Anahita Nafissi, Maurice Rosenfeld, Kamil
Sokolski, and Michael Wessel.
A Probabilistic Abduction Engine for Media Interpretation (Extended
Version).
Technical report, Hamburg University of Technology, 2010.
Bibtex entry Paper (PDF)
Abstract
For multimedia interpretation, and in particular for the combined interpretation of information com-
ing from different modalities, a semantically well-founded formalization is required in the context of an
agent-based scenario. Low-level percepts, which are represented symbolically, define the observations of
an agent, and interpretations of content are defined as explanations for the observations. We propose an
abduction-based formalism that uses description logics for the ontology and Horn rules for defining the
space of hypotheses for explanations (i.e., the space of possible interpretations of media content), and we
use Markov logic to define the motivation for the agent to generate explanations on the one hand, and
for ranking different explanations on the other.
This work has been funded by the European Community with the project CASAM (Contract FP7-217061 CASAM) and
by the German Science Foundation with the project PRESINT (DFG MO 801/1-1).
Oliver Gries, Ralf Möller, Anahita Nafissi, Maurice Rosenfeld, Kamil
Sokolski, and Michael Wessel.
Probabilistic abduction engine: Report on algorithms and the optimization
techniques used in the implementation.
Technical report, CASAM Project Deliverable D3.3, 2010.
Bibtex entry Paper (PDF)
Abstract
For multimedia interpretation, a semantically well-founded formalization is required. In accordance
with previous work, in CASAM a well-founded abduction-based approach is pursued. Extending
previous work, abduction is controlled by probabilistic knowledge, and it is done in terms of firstorder
logic.
This report describes the probabilistic abduction engine and the optimization techniques for
multimedia interpretation. It extends deliverable D3.2 by providing a probabilistic scoring function
for ranking interpretation alternatives. Parameters for the CASAM Abduction Engine (CAE)
introduced already in D3.2 are now appropriately formalized such that CAE is better integrated
into the probabilistic framework. In addition, this deliverable describes how media interpretation
services can be provided that work incrementally, i.e., are able to consume new analysis results,
or new input from a human annotator, and produce notifications for additional interpretation
results or, in some cases, revision descriptions for previous interpretations. Incremental processing
is nontrivial and is realized using an Abox di erence operator, which is used to interpretation
results obtained for extended inputs with one(s) previously obtained such that notifications about
additions and revisions can be computed.
Sebastian Wandelt and Ralf Möller.
Distributed Island-based Query Answering for Expressive Ontologies.
Technical report, Institute for Software Systems (STS), Hamburg University of
Technology, Germany, 2010.
See http://www.sts.tu-harburg.de/tech-reports/papers.html.
Bibtex entry Paper
(PDF)
Abstract
Scalability of reasoning systems is one of the main criteria which will determine the success of Semantic Web systems in the future.
The focus of recent work is either on (a) systems which rely on in-memory structures or (b) not so expressive ontology languages, which can be dealt with by using database technologies.
In this paper we introduce a method to perform query answering for semi-expressive ontologies without the limit of in-memory structures.
Our main idea is to compute small and characteristic representations of the assertional part of the input ontology. Query answering is then more eciently performed over a reduced set of these small representations. We show that query answering can be distributed in a network of description logic reasoning systems to scale for reasoning. Our initial results are encouraging.
Sebastian Wandelt and Ralf Möller.
Distributed Island-based Query Answering for Semi-Expressive Ontologies
(Extended Version).
Technical report, Hamburg University of Technology, 2010.
Bibtex entry Paper (PDF)
