Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Accelerating sequential programs using FastFlow and self-offloading

FastFlow is a programming environment specifically targeting cache-coherent shared-memory multi-cores. FastFlow is implemented as a stack of C++ template libraries built on top of lock-free (fence-free) synchronization mechanisms. In this paper we present a further evolution of FastFlow enabling programmers to offload part of their workload on a dynamically created software accelerator running on unused CPUs. The offloaded function can be easily derived from pre-existing sequential code. We emphasize in particular the effective trade-off between human productivity and execution efficiency of the approach.Comment: 17 pages + cove

Creation, Enrichment and Application of Knowledge Graphs

The world is in constant change, and so is the knowledge about it. Knowledge-based systems - for example, online encyclopedias, search engines and virtual assistants - are thus faced with the constant challenge of collecting this knowledge and beyond that, to understand it and make it accessible to their users. Only if a knowledge-based system is capable of this understanding - that is, it is capable of more than just reading a collection of words and numbers without grasping their semantics - it can recognise relevant information and make it understandable to its users. The dynamics of the world play a unique role in this context: Events of various kinds which are relevant to different communities are shaping the world, with examples ranging from the coronavirus pandemic to the matches of a local football team. Vital questions arise when dealing with such events: How to decide which events are relevant, and for whom? How to model these events, to make them understood by knowledge-based systems? How is the acquired knowledge returned to the users of these systems? A well-established concept for making knowledge understandable by knowledge-based systems are knowledge graphs, which contain facts about entities (persons, objects, locations, ...) in the form of graphs, represent relationships between these entities and make the facts understandable by means of ontologies. This thesis considers knowledge graphs from three different perspectives: (i) Creation of knowledge graphs: Even though the Web offers a multitude of sources that provide knowledge about the events in the world, the creation of an event-centric knowledge graph requires recognition of such knowledge, its integration across sources and its representation. (ii) Knowledge graph enrichment: Knowledge of the world seems to be infinite, and it seems impossible to grasp it entirely at any time. Therefore, methods that autonomously infer new knowledge and enrich the knowledge graphs are of particular interest. (iii) Knowledge graph interaction: Even having all knowledge of the world available does not have any value in itself; in fact, there is a need to make it accessible to humans. Based on knowledge graphs, systems can provide their knowledge with their users, even without demanding any conceptual understanding of knowledge graphs from them. For this to succeed, means for interaction with the knowledge are required, hiding the knowledge graph below the surface. In concrete terms, I present EventKG - a knowledge graph that represents the happenings in the world in 15 languages - as well as Tab2KG - a method for understanding tabular data and transforming it into a knowledge graph. For the enrichment of knowledge graphs without any background knowledge, I propose HapPenIng, which infers missing events from the descriptions of related events. I demonstrate means for interaction with knowledge graphs at the example of two web-based systems (EventKG+TL and EventKG+BT) that enable users to explore the happenings in the world as well as the most relevant events in the lives of well-known personalities.Die Welt befindet sich im steten Wandel, und mit ihr das Wissen über die Welt. Wissensbasierte Systeme - seien es Online-Enzyklopädien, Suchmaschinen oder Sprachassistenten - stehen somit vor der konstanten Herausforderung, dieses Wissen zu sammeln und darüber hinaus zu verstehen, um es so Menschen verfügbar zu machen. Nur wenn ein wissensbasiertes System in der Lage ist, dieses Verständnis aufzubringen - also zu mehr in der Lage ist, als auf eine unsortierte Ansammlung von Wörtern und Zahlen zurückzugreifen, ohne deren Bedeutung zu erkennen -, kann es relevante Informationen erkennen und diese seinen Nutzern verständlich machen. Eine besondere Rolle spielt hierbei die Dynamik der Welt, die von Ereignissen unterschiedlichster Art geformt wird, die für unterschiedlichste Bevölkerungsgruppe relevant sind; Beispiele hierfür erstrecken sich von der Corona-Pandemie bis hin zu den Spielen lokaler Fußballvereine. Doch stellen sich hierbei bedeutende Fragen: Wie wird die Entscheidung getroffen, ob und für wen derlei Ereignisse relevant sind? Wie sind diese Ereignisse zu modellieren, um von wissensbasierten Systemen verstanden zu werden? Wie wird das angeeignete Wissen an die Nutzer dieser Systeme zurückgegeben? Ein bewährtes Konzept, um wissensbasierten Systemen das Wissen verständlich zu machen, sind Wissensgraphen, die Fakten über Entitäten (Personen, Objekte, Orte, ...) in der Form von Graphen sammeln, Zusammenhänge zwischen diesen Entitäten darstellen, und darüber hinaus anhand von Ontologien verständlich machen. Diese Arbeit widmet sich der Betrachtung von Wissensgraphen aus drei aufeinander aufbauenden Blickwinkeln: (i) Erstellung von Wissensgraphen: Auch wenn das Internet eine Vielzahl an Quellen anbietet, die Wissen über Ereignisse in der Welt bereithalten, so erfordert die Erstellung eines ereigniszentrierten Wissensgraphen, dieses Wissen zu erkennen, miteinander zu verbinden und zu repräsentieren. (ii) Anreicherung von Wissensgraphen: Das Wissen über die Welt scheint schier unendlich und so scheint es unmöglich, dieses je vollständig (be)greifen zu können. Von Interesse sind also Methoden, die selbstständig das vorhandene Wissen erweitern. (iii) Interaktion mit Wissensgraphen: Selbst alles Wissen der Welt bereitzuhalten, hat noch keinen Wert in sich selbst, vielmehr muss dieses Wissen Menschen verfügbar gemacht werden. Basierend auf Wissensgraphen, können wissensbasierte Systeme Nutzern ihr Wissen darlegen, auch ohne von diesen ein konzeptuelles Verständis von Wissensgraphen abzuverlangen. Damit dies gelingt, sind Möglichkeiten der Interaktion mit dem gebotenen Wissen vonnöten, die den genutzten Wissensgraphen unter der Oberfläche verstecken. Konkret präsentiere ich EventKG - einen Wissensgraphen, der Ereignisse in der Welt repräsentiert und in 15 Sprachen verfügbar macht, sowie Tab2KG - eine Methode, um in Tabellen enthaltene Daten anhand von Hintergrundwissen zu verstehen und in Wissensgraphen zu wandeln. Zur Anreicherung von Wissensgraphen ohne weiteres Hintergrundwissen stelle ich HapPenIng vor, das fehlende Ereignisse aus den vorliegenden Beschreibungen ähnlicher Ereignisse inferiert. Interaktionsmöglichkeiten mit Wissensgraphen demonstriere ich anhand zweier web-basierter Systeme (EventKG+TL und EventKG+BT), die Nutzern auf einfache Weise die Exploration von Geschehnissen in der Welt sowie der wichtigsten Ereignisse in den Leben bekannter Persönlichkeiten ermöglichen

Multi-perspective requirements engineering for networked business systems: a framework for pattern composition

How business and software analysts explore, document, and negotiate requirements for enterprise systems is critical to the benefits their organizations will eventually derive. In this paper, we present a framework for analysis and redesign of networked business systems. It is based on libraries of patterns which are derived from existing Internet businesses. The framework includes three perspectives: Economic value, Business processes, and Application communication, each of which applies a goal-oriented method to compose patterns. By means of consistency relationships between perspectives, we demonstrate the usefulness of the patterns as a light-weight approach to exploration of business ideas

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System

A dataflow platform for applications based on Linked Data

Modern software applications increasingly benefit from accessing the multifarious and heterogeneous Web of Data, thanks to the use of web APIs and Linked Data principles. In previous work, the authors proposed a platform to develop applications consuming Linked Data in a declarative and modular way. This paper describes in detail the functional language the platform gives access to, which is based on SPARQL (the standard query language for Linked Data) and on the dataflow paradigm. The language features interactive and meta-programming capabilities so that complex modules/applications can be developed. By adopting a declarative style, it favours the development of modules that can be reused in various specific execution context