The availability of relatively inexpensive computing power as well as the ability to obtain, store, and retrieve huge amounts of data has spurred interest in data mining. In a majority of data mining applications, most of the effort is spent in cleaning the data and extracting useful patterns in the data. However, a critical step in refining the extracted knowledge especially in dynamic environ...

*London School of Economics and Political Science ([email protected]; [email protected]) University of Oslo ([email protected] ) Abstract The strategic use of knowledge and its management depend upon the relevant organizational context. The model of the “learning ladder” is a compact way of describing the unfolding of multiple organizational knowledge creation, transformation and transfer ...

Several arti cial intelligence architectures and systems based on \deep" models of a domain have been proposed, in particular for the diagnostic task. These systems have several advantages over traditional knowledge based systems, but they have a main limitation in their computational complexity. One of the ways to face this problem is to rely on a knowledge compilation phase, which produces kn...

In this paper, we propose a novel deep learning architecture for multi-label zero-shot learning (ML-ZSL), which is able to predict multiple unseen class labels for each input instance. Inspired by the way humans utilize semantic knowledge between objects of interests, we propose a framework that incorporates knowledge graphs for describing the relationships between multiple labels. Our model le...

When deployed in practical applications, Ontologies and KBs often suffer various kinds of inconsistency, which limit the applications performances significantly. In this paper, we propose a framework to reason inconsistency between Ontology and KB and refine the inconsistency accordingly. To make our framework efficient, we only focus on reasoning a part responsible for the inconsistency, rathe...

Automated question answering has been a topic of research and development since the earliest AI applications. Computing power has increased since the first such systems were developed, and the general methodology has changed from the use of hand-encoded knowledge bases about simple domains to the use of text collections as the main knowledge source over more complex domains. Still, many researc...

The project described in this paper deals with the design of a software product aimed to help users during the tuning process. It gives suggestions about a few crucial points, such as suitable hardware, database parameters and object distribution on the disks. Two scenarios have prevailed : if the database already exists, statistics automatically collected by Oracle will be extensively used. In...

Many organizations have recognized that knowledge is the most important resource in today’s economy. With regards to knowledge-based views of the firm, organizations are actively embracing knowledge management with the expectation of acquiring and maintaining high levels of organizational performance. The relationship between knowledge management (KM) and organizational performance has been the...

OBJECTIVE A significant impact of limited schooling and illiteracy has been found on numerous neuropsychological tests, which may partly be due to the ecological relevance of the tests in the context of illiteracy. The aims of this study were to compare the performance of illiterate and literate immigrants on two semantic criteria for the verbal fluency test, and examine the influence of accult...

This paper investigates the process of knowledge exchange in inter-firm Research and Development (R&D) alliances by means of an agent-based model. Extant research has pointed out that firms select alliance partners considering both network-related and network-unrelated features (e.g., social capital versus complementary knowledge stocks). In our agent-based model, firms are located in a metric ...