Ranking structured documents using utility theory in the Bayesian network retrieval model

In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the first stage, with the expected utility of retrieving them. The experimental work has been developed using the Shakespeare structured collection and the results show an improvement of the effectiveness of this new approach

A multi-layered Bayesian network model for structured document retrieval

New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since this class of mathematical models enable to represent and quantify the relations between the structural components of the document. Some preliminary results on the system implementation are also presented

Behaviour of composite beam with trapezoid web profiled steel section in sub-assemblage frame

The objective of this paper is to present the behaviour of composite beam using Trapezoid Web Profiled (TWP) steel section by determining the moment resistance and the deflection of the beam with composite and non-composite connections. The TWP steel section is a built up section where the flange is of S355 steel section and the corrugated web of S275 steel section. Three full scales testing setting-up as sub-assemblage frame have been carried out. It was concluded that the use of composite connection and extended end-plate has reduced significantly the deflection and has significantly increased the loading capacity of composite beam

A Friendly and Intelligent Approach to Data Retrieval in a Multimedia DBMS

Manipulation of multimedia data is not straightforward as in conventional database. One main problem is the retrieval of multimedia data from the database with the need to match the contents of multimedia data to a user query. In order to achieve a content based retrieval in our approach, we use natural language captions which allow the user to describe the contents of multimedia data. In a similar manner, users will specify their queries on multimedia data contents in natural language form. A problem is that different or even the same user describe the same thing differently at different times which results in the descriptions of the contents of multimedia data to rarely exactly match the descriptions of the user queries. Hence, partial or approximate match between descriptions of multimedia data and user queries is generally required during multimedia data retrieval. We propose an intelligent approach to approximate match by integrating both object-oriented and natural language understanding techniques. In order to make the query specification process easier we also develop a graphical user interface supporting incremental query specification and a natural way of expressing joins. The Multimedia Database Management System (MDBMS) described in this paper incorporates the capabilities as mentioned aboveNaval Ocean Systems Center, San Diego, CAhttp://archive.org/details/friendlyintellig00keimOM&N Direct FundingNAApproved for public release; distribution is unlimited

A multilayered Bayesian network model for structured document retrieval

Abstract. New standards in document representation, like for example SGML, XML, and MPEG-7, compel Information Retrieval to design and implement models and tools to index, retrieve and present documents according to the given document structure. The paper presents the design of an Information Retrieval system for multimedia structured documents, like for example journal articles, e-books, and MPEG-7 videos. The system is based on Bayesian Networks, since this class of mathematical models enable to represent and quantify the relations between the structural components of the document. Some preliminary results on the system implementation are also presented.

A Graphical User Interface for structured document retrieval

Structured document retrieval requires different user graphical interfaces from standard Information Retrieval. An Information Retrieval system dealing with structured documents has to enable a user to query, browse retrieved documents, provide query refinement and relevance feedback based not only on full documents, but also on specific document structural parts. In this paper, we present a new graphical user interface for structured document retrieval that provides the user with an intuitive and powerful set of tools for structured document searching, retrieved list navigation, and search refinement. We also present the results of a preliminary evaluation of the interface which highlights strengths and weaknesses of the current implementation and suggests directions of future work