4,242 research outputs found
ANNIS: a linguistic database for exploring information structure
In this paper, we discuss the design and implementation of our first version of the database "ANNIS" (ANNotation of Information Structure). For research based on empirical data, ANNIS provides a uniform environment for storing this data together with its linguistic annotations. A central database promotes standardized annotation, which facilitates interpretation and comparison of the data. ANNIS is used through a standard web browser and offers tier-based visualization of data and annotations, as well as search facilities that allow for cross-level and cross-sentential queries. The paper motivates the design of the system, characterizes its user interface, and provides an initial technical evaluation of ANNIS with respect to data size and query processing
Unity in diversity : integrating differing linguistic data in TUSNELDA
This paper describes the creation and preparation of TUSNELDA, a collection of corpus data built for linguistic research. This collection contains a number of linguistically annotated corpora which differ in various aspects such as language, text sorts / data types, encoded annotation levels, and linguistic theories underlying the annotation. The paper focuses on this variation on the one hand and the way how these heterogeneous data are integrated into one resource on the other hand
ATLAS: A flexible and extensible architecture for linguistic annotation
We describe a formal model for annotating linguistic artifacts, from which we
derive an application programming interface (API) to a suite of tools for
manipulating these annotations. The abstract logical model provides for a range
of storage formats and promotes the reuse of tools that interact through this
API. We focus first on ``Annotation Graphs,'' a graph model for annotations on
linear signals (such as text and speech) indexed by intervals, for which
efficient database storage and querying techniques are applicable. We note how
a wide range of existing annotated corpora can be mapped to this annotation
graph model. This model is then generalized to encompass a wider variety of
linguistic ``signals,'' including both naturally occuring phenomena (as
recorded in images, video, multi-modal interactions, etc.), as well as the
derived resources that are increasingly important to the engineering of natural
language processing systems (such as word lists, dictionaries, aligned
bilingual corpora, etc.). We conclude with a review of the current efforts
towards implementing key pieces of this architecture.Comment: 8 pages, 9 figure
Towards a query language for annotation graphs
The multidimensional, heterogeneous, and temporal nature of speech databases
raises interesting challenges for representation and query. Recently,
annotation graphs have been proposed as a general-purpose representational
framework for speech databases. Typical queries on annotation graphs require
path expressions similar to those used in semistructured query languages.
However, the underlying model is rather different from the customary graph
models for semistructured data: the graph is acyclic and unrooted, and both
temporal and inclusion relationships are important. We develop a query language
and describe optimization techniques for an underlying relational
representation.Comment: 8 pages, 10 figure
The relationship between IR and multimedia databases
Modern extensible database systems support multimedia data through ADTs. However, because of the problems with multimedia query formulation, this support is not sufficient.\ud
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Multimedia querying requires an iterative search process involving many different representations of the objects in the database. The support that is needed is very similar to the processes in information retrieval.\ud
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Based on this observation, we develop the miRRor architecture for multimedia query processing. We design a layered framework based on information retrieval techniques, to provide a usable query interface to the multimedia database.\ud
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First, we introduce a concept layer to enable reasoning over low-level concepts in the database.\ud
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Second, we add an evidential reasoning layer as an intermediate between the user and the concept layer.\ud
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Third, we add the functionality to process the users' relevance feedback.\ud
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We then adapt the inference network model from text retrieval to an evidential reasoning model for multimedia query processing.\ud
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We conclude with an outline for implementation of miRRor on top of the Monet extensible database system
A Modular and Flexible Architecture for an Integrated Corpus Query System
The paper describes the architecture of an integrated and extensible corpus
query system developed at the University of Stuttgart and gives examples of
some of the modules realized within this architecture. The modules form the
core of a corpus workbench. Within the proposed architecture, information
required for the evaluation of queries may be derived from different knowledge
sources (the corpus text, databases, on-line thesauri) and by different means:
either through direct lookup in a database or by calling external tools which
may infer the necessary information at the time of query evaluation. The
information available and the method of information access can be stated
declaratively and individually for each corpus, leading to a flexible,
extensible and modular corpus workbench.Comment: 10 pages, uuencoded gzip'ped PostScript; presented at COMPLEX'9
Annotation Graphs and Servers and Multi-Modal Resources: Infrastructure for Interdisciplinary Education, Research and Development
Annotation graphs and annotation servers offer infrastructure to support the
analysis of human language resources in the form of time-series data such as
text, audio and video. This paper outlines areas of common need among empirical
linguists and computational linguists. After reviewing examples of data and
tools used or under development for each of several areas, it proposes a common
framework for future tool development, data annotation and resource sharing
based upon annotation graphs and servers.Comment: 8 pages, 6 figure
Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project
The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and understanding. Relevant research areas include: content-based multimedia analysis and automatic annotation of semantic multimedia content, combined textual and multimedia information retrieval, semantic -web, MPEG-7 and MPEG-21 standards, user interfaces and human factors. In this paper, recent advances in content-based analysis, indexing and retrieval of digital media within the SCHEMA Network are presented. These advances will be integrated in the SCHEMA module-based, expandable reference system
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