At present, adapting an Information Extraction system to new topics is an expensive and slow process, requiring some knowledge engineering for each new topic. We propose a new par...
Most information extraction systems either use hand written extraction patterns or use a machine learning algorithm that is trained on a manually annotated corpus. Both of these a...
Information Extraction methods can be used to automatically "fill-in" database forms from unstructured data such as Web documents or email. State-of-the-art methods have...
Trausti T. Kristjansson, Aron Culotta, Paul A. Vio...
The task of identifying synonymous relations and objects, or Synonym Resolution (SR), is critical for high-quality information extraction. The bulk of previous SR work assumed str...
Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, pre-specified requests from small homogeneous corpora (e.g., extract the location and time o...
Michele Banko, Michael J. Cafarella, Stephen Soder...
Information extraction is concerned with the location of specific items in (unstructured) textual documents, e.g., being applied for the acquisition of structured data. Then, the ...
In this paper, we discuss methods of measuring the performance of ontology-based information extraction systems. We focus particularly on the Balanced Distance Metric (BDM), a new...
In this paper, we describe an approach that aims to model heterogeneous resources for information extraction. Document is modeled in graph representation that enables better under...
In this paper we propose to integrate Information Extraction and Adaptive Personalization in order to empower information access and Web search experience. We describe the PIE (Per...
Nirmala Pudota, Paolo Casoto, Antonina Dattolo, Pa...
Regular expressions have served as the dominant workhorse of practical information extraction for several years. However, there has been little work on reducing the manual effort ...