This paper describes a novel approach for discovering web services. The approach combines two logic-based formalisms and two reasoning engines and is illustrated in using a set of web services dedicated to web information extraction. The approach exhibits more or less complex relationships between services: (1) a service may have one or many variants, these are services that perform the same ta...

Currently, the main drawback for the development of the Semantic Web stems from the manual tagging of web pages according to a given ontology that conceptualizes its domain. This tasks is usually hard, even for experts, and it is prone to errors due to the different interpretations users can have about the same documents. In this paper we address the problem of automatically generating ontology...

This paper shows how Semantic Web technologies enable the design and implementation of advanced, personalized information systems. We demonstrate by means of an example application how personalized content syndication can be realized in the Semantic Web. Our approach consists of two main parts: The web data extraction part, providing the information system with real-time, dynamic data, and the ...

Personal information extraction is an important component of advanced information retrieval. There are two problems needed to be solved in this practical task: personal name ambiguity and extraction of personal information for a specific person. For personal name ambiguity, which is a very common phenomenon in the fast growing Web resource, we propose a robust system which extracts features wit...

In this paper we propose a methodology to learn to extract domain-specific information from large repositories (e.g. the Web) with minimum user intervention. Learning is seeded by integrating information from structured sources (e.g. databases and digital libraries). Retrieved information is then used to bootstrap learning for simple Information Extraction (IE) methodologies, which in turn will...

The process of document annotation for the Semantic Web is complex and time consuming, as it requires a great deal of manual annotation. Information extraction from texts (IE) is a technology used by some very recent systems for reducing the burden of annotation. The integration of IE systems in annotation tools is quite a new development and there is still the necessity of thinking the impact ...

Selecting discriminating terms in order to represent the contents of texts is a critical problem for many applications in Information Retrieval. Most of the Information Retrieval systems index documents based on individual words that are not specific enough to evidence the contents of texts. As a consequence, there has been a growing interest in developing techniques for automatic term extracti...

The goal of information extraction (IE) is to find desired pieces of information in natural language texts and store them in a form that is suitable for automatic querying and processing; the Semantic Web provides formats and standards for storing and processing such data. Hence IE-based automatic or semi-automatic approaches are a promising approach for building the Semantic Web. My Ph.D. thes...

This paper presents a search system for information on scientists which was implemented prototypically for the area of information science, employing Web Content Mining techniques. The sources that are used in the implemented approach are online publication services and personal homepages of scientists. The system contains wrappers for querying the publication services and information extractio...

We present a simple method to extract information from search engine snippets. Although the techniques presented are domain independent, this work focuses on extracting biographical information of historical persons from multiple unstructured sources on the Web. We first similarly find a list of persons and their periods of life by querying the periods and scanning the retrieved snippets for pe...