@inproceedings{Roelleke/Fuhr:97c,
	address = {Aberdeen},
	title = {Retrieving {Complex} {Objects} with \{{HySpirit}\}},
	abstract = {Traditional Information Retrieval (IR) considers
documents as atomic units. In this paper, we show the
retrieval of the components of the documents which
satisfy best the information need. This finer
granularity eases the browsing of the retrieval result.
The approach supports multimedia and networked IR since
multimedia documents are composed of other objects and
networks combine several collections comprising the
documents. We gain a unified view on networks,
databases, and multimedia documents by considering them
as complex objects -- retrieval among a heterogeneous
document corpus can be modeled appropriately. We
present a probabilistic retrieval function where the
initial estimation of probabilistic parameters is based
on the logical structure of documents and the retrieval
process is described as probabilistic logical
inference. Probabilistic parameters and the retrieval
process are represented in probabilistic Datalog
programs which are executed by HySpirit -- a system for
processing probabilistic inference.},
	booktitle = {Proceedings of the 19th {Annual} {BCS}-{IRSG} {Colloquium} on {IR} {Research}},
	publisher = {Robert Gordon University},
	author = {Rölleke, Thomas and Fuhr, Norbert},
	editor = {Furner, J and Harper, D J},
	year = {1997},
	pages = {32--43},
}

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