Exploiting multimedia in creating and analysing multimedia Web archives

The data contained on the web and the social web are inherently multimedia and consist of a mixture of textual, visual and audio modalities. Community memories embodied on the web and social web contain a rich mixture of data from these modalities. In many ways, the web is the greatest resource ever created by human-kind. However, due to the dynamic and distributed nature of the web, its content changes, appears and disappears on a daily basis. Web archiving provides a way of capturing snapshots of (parts of) the web for preservation and future analysis. This paper provides an overview of techniques we have developed within the context of the EU funded ARCOMEM (ARchiving COmmunity MEMories) project to allow multimedia web content to be leveraged during the archival process and for post-archival analysis. Through a set of use cases, we explore several practical applications of multimedia analytics within the realm of web archiving, web archive analysis and multimedia data on the web in general

Current Challenges and Visions in Music Recommender Systems Research

Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at the user's fingertip. While today's MRS considerably help users to find interesting music in these huge catalogs, MRS research is still facing substantial challenges. In particular when it comes to build, incorporate, and evaluate recommendation strategies that integrate information beyond simple user--item interactions or content-based descriptors, but dig deep into the very essence of listener needs, preferences, and intentions, MRS research becomes a big endeavor and related publications quite sparse. The purpose of this trends and survey article is twofold. We first identify and shed light on what we believe are the most pressing challenges MRS research is facing, from both academic and industry perspectives. We review the state of the art towards solving these challenges and discuss its limitations. Second, we detail possible future directions and visions we contemplate for the further evolution of the field. The article should therefore serve two purposes: giving the interested reader an overview of current challenges in MRS research and providing guidance for young researchers by identifying interesting, yet under-researched, directions in the field

Sand and Dust Storm Warning Advisory and Assessment System (SDS-WAS) Science and Implementation Plan: 2015-2020

World Weather Research Programme (WWRP 2015-5

Spatial Keypoint Representation for Visual Object Retrieval

Abstract. This paper presents a concept of an object pre-classification method based on image keypoints generated by the SURF algorithm. For this purpose, the method uses keypoints histograms for image serialization and next histograms tree representation to speed-up the comparison process. Presented method generates histograms for each image based on localization of generated keypoints. Each histogram contains 72 values computed from keypoints that correspond to sectors that slice the entire image. Sectors divide image in radial direction form center points of objects that are the subject of classification. Generated histograms allow to store information of the object shape and also allow to compare shapes efficiently by determining the deviation between histograms. Moreover, a tree structure generated from a set of image histograms allows to further speed up process of image comparison. In this approach each histogram is added to a tree as a branch. The sub tree is created in a reverse order. The last element of the lowest level stores the entire histogram. Each next upper element is a simplified version of its child. This approach allows to group histograms by their parent node and reduce the number of node comparisons. In case of not matched element, its entire subtree is omitted. The final result is a set of similar images that could be processed by more complex methods

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Survey on Challenges of Question Answering in the Semantic Web

Höffner K, Walter S, Marx E, Usbeck R, Lehmann J, Ngomo A-CN. Survey on Challenges of Question Answering in the Semantic Web. Semantic Web Journal. 2017;8(6):895-920

A document based traceability model for test management

Software testing has became more complicated in the emergence of distributed network, real-time environment, third party software enablers and the need to test system at multiple integration levels. These scenarios have created more concern over the quality of software testing. The quality of software has been deteriorating due to inefficient and ineffective testing activities. One of the main flaws is due to ineffective use of test management to manage software documentations. In documentations, it is difficult to detect and trace bugs in some related documents of which traceability is the major concern. Currently, various studies have been conducted on test management, however very few have focused on document traceability in particular to support the error propagation with respect to documentation. The objective of this thesis is to develop a new traceability model that integrates software engineering documents to support test management. The artefacts refer to requirements, design, source code, test description and test result. The proposed model managed to tackle software traceability in both forward and backward propagations by implementing multi-bidirectional pointer. This platform enabled the test manager to navigate and capture a set of related artefacts to support test management process. A new prototype was developed to facilitate observation of software traceability on all related artefacts across the entire documentation lifecycle. The proposed model was then applied to a case study of a finished software development project with a complete set of software documents called the On-Board Automobile (OBA). The proposed model was evaluated qualitatively and quantitatively using the feature analysis, precision and recall, and expert validation. The evaluation results proved that the proposed model and its prototype were justified and significant to support test management