Martin Vesely

From Text to Knowledge: Document Processing and Visualization: a Text Mining Approach

Document processing and visualization was identified as one of the key topics in the domain of Text Mining. For this reason, the WG1 working group was created in the NEMIS project. In the areas it covers, this working group contributes to the production of a roadmap for follow-up research and technological development in text mining, which is the overall goal of the NEMIS project. Relevant research topics have been identified in the document processing and visualization domains. An analysis of the associated state-ofthe-art techniques and state-of-the-software tools have been carried out. The results of this analysis are presented to foster discussion and contribute to a collaborative improvement of the roadmap content.

CERN document server: Document management system for grey literature in a networked environment

ConclusionIn this paper we briefly described the current status of research in the field of digital libraries interoperability, mainly with respect to federated data processing such as permitted within the Open Archive Initiative framework. We then presented the CERN Document Server Software suite that is a free software package main-tained by CERN providing an online digital library solution for mid- to large-sized document repositories. The set of CDSware modules was described and the differ-ences with other existing tools briefly mentioned. Finally we have mentioned a typical usage statistics illustrating the scope of grey literature and networked con-ditions of the CERN Document Server.We pointed out that the current trend in grey literature management goes toward institutional repositories build upon the distributed and federated model. Further research is going on within the CDS collaboration in this area, focused particularly on (i) semantic interoperability using ontologies in distributed and federated data processing and (ii) ranking technologies when searching grey literature in OAI compliant repositories.

Citation graph based ranking in Invenio

Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods.

Combining Text Mining and Information Retrieval Techniques for Enhanced Access to Statistical Data on the Web: A Preliminary Report

In this contribution, we present the StatSearch prototype, a search engine that enables an enhanced access to domain specific data available on the Web. The StatSearch engine proposes a hybrid search interface combining query-based search with automated navigation through a tree-like hierarchical structure. The goal of such an interface is to allow a more natural and intuitive control over the information access process, thus improving the speed and quality of the access to information.