On exploiting static and dynamically mined metadata for exploratory web searching

Most Web Search Engines (WSEs) are appropriate for focalized search, i.e., they make the assumption that users can accurately describe their information need using a small sequence of terms. However, as several user studies have shown, a high percentage of search tasks are exploratory, and focalized search very commonly leads to inadequate interactions and poor results. This paper proposes exploiting static and dynamically mined metadata for enriching web searching with exploration services. Online results clustering, which is a mining task of dynamic nature since it is based on query-dependent snippets, is useful for providing users with overviews of the top results and thus allowing them to restrict their focus to the desired parts. On the other hand, the various static metadata that are available to a search engine (e.g., domain, language, date, and filetype) are commonly exploited only through the advanced (form-based) search facilities that some WSEs offer (and users rarely use). We propose an approach that combines both kinds of metadata by adopting the interaction paradigm of dynamic taxonomies and faceted exploration, which allows the users to restrict their focus gradually using both static and dynamically derived metadata. Special focus is given on the design and analysis of incremental algorithms for speeding up the exploration process. The experimental evaluation over a real WSE shows that this combination results to an effective, flexible, and efficient exploration experience. Finally, we report the results of a user study indicating that this direction is promising in terms of user preference, satisfaction, and effort.     

The ramification problem in temporal databases: an approach with conflicting constraints

In this paper we study the ramification problem in the setting of temporal databases. Standard solutions from the literature on reasoning about action are inadequate because they rely on the assumption that fluents persist, and because actions have effects on the next situation only. In this paper we provide a solution to the ramification problem based on an extension of the situation calculus and the work of McCain and Turner. More specifically, we study the case where there are conflicting effects of an action, a particularly complex problem. Also we present a tool which implements the proposed solution.     

Text binarization in color documents

This article presents a new method for the binarization of color document images. Initially, the colors of the document image are reduced to a small number using a new color reduction technique. Specifically, this technique estimates the dominant colors and then assigns the original image colors to them in order that the background and text components to become uniform. Each dominant color defines a color plane in which the connected components (CCs) are extracted. Next, in each color plane a CC filtering procedure is applied which is followed by a grouping procedure. At the end of this stage, blocks of CCs are constructed which are next redefined by obtaining the direction of connection (DOC) property for each CC. Using the DOC property, the blocks of CCs are classified as text or nontext. The identified text blocks are binarized properly using suitable binarization techniques, considering the rest of the pixels as background. The final result is a binary image which contains always black characters in white background independently of the original colors of each text block. The proposed document binarization approach can also be used for binarization of noisy color (or gray‐scale) document images. Several experiments that confirm the effectiveness of the proposed technique are presented. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 262–274, 2006     

The global k-means clustering algorithm

We present the global k-means algorithm which is an incremental approach to clustering that dynamically adds one cluster center at a time through a deterministic global search procedure consisting of N (with N being the size of the data set) executions of the k-means algorithm from suitable initial positions. We also propose modifications of the method to reduce the computational load without significantly affecting solution quality. The proposed clustering methods are tested on well-known data sets and they compare favorably to the k-means algorithm with random restarts.     

An integrated architecture for the provision of health telematic services based on digital library technologies

monolithic information system to effectively serve the needs of an entire healthcare organizational structure. Thus, information and telecommunications systems must primarily provide the infrastructure to support the effective integration of distributed and heterogeneous components, ensuring overall integrity in terms of functional and information interworking. This approach i.e., the integration of heterogeneous autonomous distributed systems, to developing and managing regional healthcare networks ensures the transfer and integration of consistent information between healthcare facilities, without imposing constraints on the operation of individual clinical units. This paper presents the results of an ongoing effort for the design and implementation of an architecture based on digital library technologies, for the provision of user-oriented telematic services in a regional healthcare network. Specifically, it addresses issues related to the provision of user-oriented services, transparent to the needs of different user groups and the requirements of specific tasks, based on: a) meta-information for the creation of an information infrastructure for the regional healthcare network which is, effectively, a multimedia distributed digital library, b) intelligent informationretrieval strategies to selectively retrieve information from multimedia data, c) agent-based technologies for effective service delivery adapted to the current user needs and the task at hand, and d) middleware services that explicitly reveal not only the characteristics of the information sources, but also address the context of specific telematic services, through appropriate mediation mechanisms. Received: 10 April 1997 / Revised: 6 July 1997 / Accepted: 5 August 1997     

Mapping average equivalized income using robust small area methods

Measures of economic well‐being are often needed for geographically small areas, as economic indicators may be distributed unevenly among the subsets of relatively small regions. We consider small area estimation of average equivalized income. Disposable household income data are usually available only for a sample of households, typically too small to provide reliable estimates for small regions. We consider a small area estimation technique that is robust to outliers, produces results consistent with design weighted estimates obtained for larger areas and yield maps with approximately no shrinkage. The proposed methodology is applied to the Local Labour Systems in Tuscany (Italy).     

Cooperative schemes for path establishment in mobile ad-hoc networks under shadow-fading

The performance of routing protocols for multi-hop path-establishment in Mobile Ad-hoc NETworks (MANET) is examined when the individual radio links undergo shadow fading of parameterized severity. Such propagation modeling is typical of ground-level networking along with node mobility. The metrics of main interest are the probability of having a reliable multi-hop path plus the temporal statistics of such availability under a Markovian model. Such availability is an indicator for the suitability of the network to carry delay-sensitive applications (push-to-talk voice, streaming video) in uninterrupted manner. It is shown that high levels of diversity are necessary in such adverse environments, as obtained either by multiple independent paths or via concurrent cooperative transmission. Analytical and simulation comparisons of typical routing options are presented on the above metrics, plus on the required nodal engagement for supporting such diversity.     

Subclass discriminant Nonnegative Matrix Factorization for facial image analysis

Nonnegative Matrix Factorization (NMF) is among the most popular subspace methods, widely used in a variety of image processing problems. Recently, a discriminant NMF method that incorporates Linear Discriminant Analysis inspired criteria has been proposed, which achieves an efficient decomposition of the provided data to its discriminant parts, thus enhancing classification performance. However, this approach possesses certain limitations, since it assumes that the underlying data distribution is unimodal, which is often unrealistic. To remedy this limitation, we regard that data inside each class have a multimodal distribution, thus forming clusters and use criteria inspired by Clustering based Discriminant Analysis. The proposed method incorporates appropriate discriminant constraints in the NMF decomposition cost function in order to address the problem of finding discriminant projections that enhance class separability in the reduced dimensional projection space, while taking into account subclass information. The developed algorithm has been applied for both facial expression and face recognition on three popular databases. Experimental results verified that it successfully identified discriminant facial parts, thus enhancing recognition performance.     

A comparative organic geochemical study of oils seeps in Western Greece

Samples from three oil shows in Western Greece were studied following a suite of analytical geochemical procedures, aiming to reveal the origin of the organic matter and characterize its depositional environment. The authors’ findings were compared, and confirmed to a great extent, to geochemical results from previously published studies. Certain compositional differences exist between the three oil shows, reflecting different source rock and/or different facies. The influence of different analytical methodologies commonly used to separate compound groups (saturates, aromatics, resins, asphaltenes) on the obtained geochemical indices was also examined. The results demonstrate that bulk composition of maltenes, as well as most biomarker indices, are not affected significantly by the employed group-type separation procedures.