Information extraction is the process of recognizing the particular fragments of a document that constitute its core semantic content. However, most previous information extraction systems were not effective for real-world information sources due to difficulties in acquiring and representing useful domain knowledge and in dealing with structural heterogeneity inherent in different sources. In o...

As our reliance on computers increases, so does the need for robust software. Previous studies have shown that many C libraries exhibit robustness problems due to exceptional inputs. This paper describes the HEALERS system that uses an automated approach to increasing the robustness of C libraries without source code access. The system extracts the C type information for a shared library using ...

We investigate an important issue of a meta-algorithm for selecting variables in the framework of microarray data. This wrapper method starts from any classification algorithm and weights each variable (i.e. gene) relative to its efficiency for classification. An optimization procedure is then inferred which exhibits important genes for the studied biological process. Theory and application wit...

The htmlButler project aims at enhancing the usability of visual wrapper technology while preserving versatility. htmlButler will allow, for an untrained user who has only the most basic web knowledge, to visually specify simple but useful wrappers and, for a more tech-savvy user, to visually or otherwise specify more complex wrappers. htmlButler was started 2005/2 and is based on visual wrappi...

Connection of internal scan chains in core wrapper design (CWD) is necessary to handle the width match of TAM and internal scan chains. However, conventional serial connection of internal scan chains incurs power and time penalty. Study shows that the distribution and high density of don’t care bits (X-bits) in test patterns make scan slices overlapping and partial overlapping possible. A novel...

Data extraction from the Web represents an important issue. Several approaches have been developed to bring the wrapper generation process at the web scale. Although they rely on different techniques and formalisms, they all learn a wrapper given a set of sample pages. Unsupervised approaches require just a set of sample pages, supervised ones also need training data. Unfortunately, the accurac...

This work explores the usage of Linked Data for Web scale Information Extraction, with focus on the task of Wrapper Induction. We show how to effectively use Linked Data to automatically generate training material and build a self-trained Wrapper Induction method. Experiments on a publicly available dataset demonstrate that for covered domains, our method can achieve F measure of 0.85, which is...

The ongoing aim behind the work described here is to investigate support for a data centre type environment where an application can be implemented as a composition of components, or workflow. For instance, an application might reuse established components. As is typical in data centre operation, hosting of an application is governed by a Service Level Agreement (SLA) between provider and appli...

This work presents a global geometric similarity scheme (GGSS) for feature selection in fault diagnosis, which is composed of global geometric model and similarity metric. The global geometric model is formed to construct connections between disjoint clusters in fault diagnosis. The similarity metric of the global geometric model is applied to filter feature subsets. To evaluate the performance...