Usability Guidelines for Desktop Search Engines

In this article we describe a usability evaluation of eight desktop search engines (DSEs). We used the heuristic walkthrough method to gather usability problems as well as individual strengths and weaknesses of the tested search engines. The results of the evaluation are integrated into a set of 30 design guidelines for user-friendly DSEs

Developing a Process Model for the Forensic Extraction of Information from Desktop Search

Desktop search applications can contain cached copies of files that were deleted from the file system. Forensic investigators see this as a potential source of evidence, as documents deleted by suspects may still exist in the cache. Whilst there have been attempts at recovering data collected by desktop search applications, there is no methodology governing the process, nor discussion on the most appropriate means to do so. This article seeks to address this issue by developing a process model that can be applied when developing an information extraction application for desktop search applications, discussing preferred methods and the limitations of each. This work represents a more structured approach than other forms of current research

Desktop Search Engine for Linux

Desktop Search Engine become more popular for personal and enterprise after some difficulties occurs when dealing with the huge amount of files and in a multi-user environment. Desktop Search Engine for Linux is a desktop search tool, integrated between Namazu with web-based interface that can search text format files inthe hard drive ofpersonal computer. As increasingly demand for aneffective and efficient desktop search tools especially for the Linux environment where there were just a few tools have been developed for Linux compared for Windows although the usage of Linux operating system are increased from days to days. This system is just for Linux (Debian platform) operating system and just search for a text format files. This system index the entire words of files in the hard drive and create one index files that contains all details about the files in the disk. The system just refers to this index files when processing the searching process for a fast and effective results. From the studies and analysis that has been done during the development of this system, there have a benchmark criterion for desktop search tools that can be use as a reference and also a lot of indexer that can be used to index the files. Only the best indexer was be taken to integrate with this system. This system still can be improved with the support, effort and deep knowledge about desktop searchtools and technical skills

Integrando motores de indexação de dados para a construção de sistemas de recuperação de informação em ambientes heterogêneos

The different proposals for information recovery put forward a set of limitations about the environments which they recover information from, they usually restrict the information recovery to a very specific data source or knowledge area. In this context, this paper proposes a model and a framework in order to integrate different index engines to enable the development of Information Retrieval Systems capable of retrieving information in heterogeneous data sources, and, therefore, showing up as a solution to fulfill the demand to access information in corporate environments.As diversas propostas existentes para a recuperação de informação apresentam limitações referentes ao ambiente em que atuam, restringindo a recuperação de informações a fontes de dados ou a áreas do conhecimento especificas. Neste contexto, este artigo propõe um modelo e um arcabouço para a integração de motores de indexação a fim de possibilitar o desenvolvimento de Sistemas de Recuperação de Informação (SRIs) capacitados a recuperar informações em ambientes de fontes de dados heterogêneas, apresentando-se assim, como uma abordagem para atender a demanda de acesso às informações em ambientes corporativos

Ein Vergleich ausgewählter Desktop-Suchmaschinen

Ilmenauer Beiträge zur Wirtschaftsinformatik Nr. 2011-02 / Technische Universität Ilmenau, Fakultät für Wirtschaftswissenschaften, Institut für Wirtschaftsinformatik ISSN 1861-9223 ISBN 978-3-938940-33-

Search in glintt HS solutions

Documento confidencial. Não pode ser disponibilizado para consultaTese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 201

Técnicas de mineração incrementais em recuperação de informação

[EN] A desirable property of learning algorithms is the ability of incorporating new data in an incremental way. Incremental algorithms have received attention on the last few years. Particulary Bayesian networks, this is due to the hardness of the task. In Bayesian networks one example can change the whole structure of the Bayesian network. In this theses we focus on incremental induction of Tree Augmented Naive Bayes (TAN) algorithm. A incremental version of TAN saves computing time, is more suite to data mining and concept drift. But, as usual in Bayesian learning TAN is restricted to discrete attributes. Complementary to the incremental TAN, we propose an incremental discretization algorithm, necessary to evaluate TAN in domains with continuous attribute. Discretization is a fundamental pre-processing step for some well- known algorithms, the topic of incremental discretization has received few attention from the community. This theses has two major contributions, the benefict of both proposals is incremental learning, one for TAN and the other for discretization.We present and test a algorithm that rebuilds the network structure of tree augmented naive Bayes (TAN) based on the weighted sum of vectors containing the mutual information. We also present a new discretization method, this works in two layers. This two-stage architecture is very fexible. It can be used as supervised or unsupervised. For the second layer any base discretization method can be used: equal width, equal frequency, recursive entropy discretization, chi-merge, etc. The most relevant aspect is that the boundaries of the intervals of the second layer can change when new data is available. We tested experimentally the incremental approach to discretization with batch and incremental learners. The experimental evaluation of incremental TAN shows a perfor mance similar to the batch version. Similar remarks apply to incremental discretization. This is a relevant aspect, because few works in machine learning address the fundamental aspect of incremental discretization. We believe that with Incremental discretization, the evaluation of the incremental algorithms can become more realistic and accurate. We evaluated two versions of incremental discretization: supervised and unsupervised. We have seen that this feature can improve accuracy for the incremental learners and that the preview of future algorithm performance can be more precise. This method of discretization has another advantages, like, can be used with large data set's or can be used in dynamic environments with concept drift, areas where a batch discretization can be difficult or is not adequate.[ES] Esta tesis tenía como objetivo el estudio de una red Bayesiana (TAN) incremental. Durante el transcurso de esta se verificó la laguna en el área de una discretización incremental para la evaluación de un algoritmo incremental. Así se procuró dar como contribución para el área no solo un clasificador Bayesiano incremental sino también un modo de evaluación correcto del clasificador. Los Sistemas de Recuperación de Información tienen como objetivo la realización de las tareas de indexación, búsqueda y clasificación de documentos (expresos en la forma textual), con el fin de satisfacer la necesidad de información del individuo, generalmente expresa a través de consultas. La necesidad de información puede ser entendida como la búsqueda de respuestas para determinadas cuestiones que tienen que ser resueltas, la recuperación de documentos que tratan sobre un determinado asunto o incluso la relación entre asuntos