Dual retrieval in conceptual information systems

Conceptual Information Systems provide a multi-dimensional conceptually structured view on data stored in relational databases. On restricting the expressiveness of the retrieval language, they allow the visualization of sets of realted queries in conceptual hierarchies, hence supporting the search of something one does not have a precise description, but only a vague idea of. Information Retrieval is considered as the process of finding specific objects (documents etc.) out of a large set of objects which fit to some description. In some data analysis and knowledge discovery applications, the dual task is of interest: The analyst needs to determine, for a subset of objects, a description for this subset. In this paper we discuss how Conceptual Information Systems can be extended to support also the second task.

Semantic-driven context-aware visual information indexing and retrieval: applied in the film post-production domain

A large volume of visual content is inaccessible until effective and efficient indexing and retrieval of such data is achieved. In this paper, we introduce the DREAM system, which is a knowledge-assisted semantic-driven context-aware visual information retrieval system applied in the film post production domain. We mainly focus on the automatic labelling and topic map related aspects of the framework. The use of the context- related collateral knowledge, represented by a novel probabilistic based visual keyword co-occurrence matrix, had been proven effective via the experiments conducted during system evaluation. The automatically generated semantic labels were fed into the Topic Map Engine which can automatically construct ontological networks using Topic Maps technology, which dramatically enhances the indexing and retrieval performance of the system towards an even higher semantic level.

New perspectives on the processing and release of public information

This article discusses issues related to the organization and reception of information in the context of services and public information systems driven by technology. It stems from the assumption that in a ""technologized"" society, the distance between users and information is almost always of cognitive and socio-cultural nature, a product of our effort to design communication. In this context, we favor the approach of the information sign, seeking to answer how a documentary message turns into information, i.e. a structure recognized as socially useful. Observing the structural, cognitive and communicative aspects of the documentary message, based on Documentary Linguistics, Terminology, as well as on Textual Linguistics, the policy of knowledge management and innovation of the Government of the State of Sao Paulo is analyzed, which authorizes the use of Web 2.0, also questioning to what extent this initiative represents innovation in the environment of libraries.

Decision support system with incomplete and domain incoherent information management

Many of the most common human functions such as temporal and non-monotonic reasoning have not yet been fully mapped in developed systems, even though some theoretical breakthroughs have already been accomplished. This is mainly due to the inherent computational complexity of the theoretical approaches. In the particular area of fault diagnosis in power systems however, some systems which tried to solve the problem, have been deployed using methodologies such as production rule based expert systems, neural networks, recognition of chronicles, fuzzy expert systems, etc. SPARSE (from the Portuguese acronym, which means expert system for incident analysis and restoration support) was one of the developed systems and, in the sequence of its development, came the need to cope with incomplete and/or incorrect information as well as the traditional problems for power systems fault diagnosis based on SCADA (supervisory control and data acquisition) information retrieval, namely real-time operation, huge amounts of information, etc. This paper presents an architecture for a decision support system, which can solve the presented problems, using a symbiosis of the event calculus and the default reasoning rule based system paradigms, insuring soft real-time operation with incomplete, incorrect or domain incoherent information handling ability. A prototype implementation of this system is already at work in the control centre of the Portuguese Transmission Network.

Discovery and retrieval of Geographic data using Google

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Formulierung von Nutzerpräferenzen in Multimedia-Retrieval-Systemen

Multimedia, retrieval, multimedia-retrieval-system, multimedia query languages, weighting, preferences

Le journaliste dans le processus de recherche d'information sur le Web

Le présent mémoire cherche à comprendre et à cerner le lien entre la stratégie de recherche d’information par le journaliste sur le web et les exigences de sa profession. Il vise à appréhender les précautions que prend le journaliste lors de sa recherche d’information sur le web en rapport avec les contraintes que lui imposent les règles de sa profession pour assurer la qualité des sources d’informations qu’il exploite. Nous avons examiné cette problématique en choisissant comme cadre d’étude Radio-Canada où nous avons rencontré quelques journalistes. Ceux-ci ont été suivis en situation de recherche d’information puis questionnés sur leurs expériences de recherche. L’arrivée d’internet et la révolution technologique qui en a découlé ont profondément bouleversé les pratiques journalistiques. La recherche d’information représente ainsi une zone importante de cette mutation des pratiques. Cette transformation amène surtout à s’interroger sur la façon dont la nouvelle façon de rechercher les sources d’information influence le travail du journaliste, et surtout les balises que se donne celui-ci pour résister aux pièges découlant de sa nouvelle méthode de travail.

Information Discovery in Distributed Systems-A Novel Concept Based on Modelling of Information Elements

Sharing of information with those in need of it has always been an idealistic goal of networked environments. With the proliferation of computer networks, information is so widely distributed among systems, that it is imperative to have well-organized schemes for retrieval and also discovery. This thesis attempts to investigate the problems associated with such schemes and suggests a software architecture, which is aimed towards achieving a meaningful discovery. Usage of information elements as a modelling base for efficient information discovery in distributed systems is demonstrated with the aid of a novel conceptual entity called infotron.The investigations are focused on distributed systems and their associated problems. The study was directed towards identifying suitable software architecture and incorporating the same in an environment where information growth is phenomenal and a proper mechanism for carrying out information discovery becomes feasible. An empirical study undertaken with the aid of an election database of constituencies distributed geographically, provided the insights required. This is manifested in the Election Counting and Reporting Software (ECRS) System. ECRS system is a software system, which is essentially distributed in nature designed to prepare reports to district administrators about the election counting process and to generate other miscellaneous statutory reports.Most of the distributed systems of the nature of ECRS normally will possess a "fragile architecture" which would make them amenable to collapse, with the occurrence of minor faults. This is resolved with the help of the penta-tier architecture proposed, that contained five different technologies at different tiers of the architecture.The results of experiment conducted and its analysis show that such an architecture would help to maintain different components of the software intact in an impermeable manner from any internal or external faults. The architecture thus evolved needed a mechanism to support information processing and discovery. This necessitated the introduction of the noveI concept of infotrons. Further, when a computing machine has to perform any meaningful extraction of information, it is guided by what is termed an infotron dictionary.The other empirical study was to find out which of the two prominent markup languages namely HTML and XML, is best suited for the incorporation of infotrons. A comparative study of 200 documents in HTML and XML was undertaken. The result was in favor ofXML.The concept of infotron and that of infotron dictionary, which were developed, was applied to implement an Information Discovery System (IDS). IDS is essentially, a system, that starts with the infotron(s) supplied as clue(s), and results in brewing the information required to satisfy the need of the information discoverer by utilizing the documents available at its disposal (as information space). The various components of the system and their interaction follows the penta-tier architectural model and therefore can be considered fault-tolerant. IDS is generic in nature and therefore the characteristics and the specifications were drawn up accordingly. Many subsystems interacted with multiple infotron dictionaries that were maintained in the system.In order to demonstrate the working of the IDS and to discover the information without modification of a typical Library Information System (LIS), an Information Discovery in Library Information System (lDLIS) application was developed. IDLIS is essentially a wrapper for the LIS, which maintains all the databases of the library. The purpose was to demonstrate that the functionality of a legacy system could be enhanced with the augmentation of IDS leading to information discovery service. IDLIS demonstrates IDS in action. IDLIS proves that any legacy system could be augmented with IDS effectively to provide the additional functionality of information discovery service.Possible applications of IDS and scope for further research in the field are covered.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Case-based system: Indexing and retrieval with fuzzy hypercube

In some applications with case-based system, the attributes available for indexing are better described as linguistic variables instead of receiving numerical treatment. In these applications, the concept of fuzzy hypercube can be applied to give a geometrical interpretation of similarities among cases. This paper presents an approach that uses geometrical properties of fuzzy hypercube space to make indexing and retrieval processes of cases.

Automatic Indexing and Information Visualization: A Study Based on Paraconsistent Logic

This paper reports a research to evaluate the potential and the effects of use of annotated Paraconsistent logic in automatic indexing. This logic attempts to deal with contradictions, concerned with studying and developing inconsistency-tolerant systems of logic. This logic, being flexible and containing logical states that go beyond the dichotomies yes and no, permits to advance the hypothesis that the results of indexing could be better than those obtained by traditional methods. Interactions between different disciplines, as information retrieval, automatic indexing, information visualization, and nonclassical logics were considered in this research. From the methodological point of view, an algorithm for treatment of uncertainty and imprecision, developed under the Paraconsistent logic, was used to modify the values of the weights assigned to indexing terms of the text collections. The tests were performed on an information visualization system named Projection Explorer (PEx), created at Institute of Mathematics and Computer Science (ICMC - USP Sao Carlos), with available source code. PEx uses traditional vector space model to represent documents of a collection. The results were evaluated by criteria built in the information visualization system itself, and demonstrated measurable gains in the quality of the displays, confirming the hypothesis that the use of the para-analyser under the conditions of the experiment has the ability to generate more effective clusters of similar documents. This is a point that draws attention, since the constitution of more significant clusters can be used to enhance information indexing and retrieval. It can be argued that the adoption of non-dichotomous (non-exclusive) parameters provides new possibilities to relate similar information.

A distributed, semiotic-inductive and human-Oriented approach to web-scale knowledge retrieval

Web-scale knowledge retrieval can be enabled by distributed information retrieval, clustering Web clients to a large-scale computing infrastructure for knowledge discovery from Web documents. Based on this infrastructure, we propose to apply semiotic (i.e., sub-syntactical) and inductive (i.e., probabilistic) methods for inferring concept associations in human knowledge. These associations can be combined to form a fuzzy (i.e.,gradual) semantic net representing a map of the knowledge in the Web. Thus, we propose to provide interactive visualizations of these cognitive concept maps to end users, who can browse and search the Web in a human-oriented, visual, and associative interface.

Using citation data to improve retrieval from MEDLINE.

OBJECTIVE: To determine whether algorithms developed for the World Wide Web can be applied to the biomedical literature in order to identify articles that are important as well as relevant. DESIGN AND MEASUREMENTS A direct comparison of eight algorithms: simple PubMed queries, clinical queries (sensitive and specific versions), vector cosine comparison, citation count, journal impact factor, PageRank, and machine learning based on polynomial support vector machines. The objective was to prioritize important articles, defined as being included in a pre-existing bibliography of important literature in surgical oncology. RESULTS Citation-based algorithms were more effective than noncitation-based algorithms at identifying important articles. The most effective strategies were simple citation count and PageRank, which on average identified over six important articles in the first 100 results compared to 0.85 for the best noncitation-based algorithm (p < 0.001). The authors saw similar differences between citation-based and noncitation-based algorithms at 10, 20, 50, 200, 500, and 1,000 results (p < 0.001). Citation lag affects performance of PageRank more than simple citation count. However, in spite of citation lag, citation-based algorithms remain more effective than noncitation-based algorithms. CONCLUSION Algorithms that have proved successful on the World Wide Web can be applied to biomedical information retrieval. Citation-based algorithms can help identify important articles within large sets of relevant results. Further studies are needed to determine whether citation-based algorithms can effectively meet actual user information needs.