NAVDEX, a helpful tool for the classification of environmental legislation

Since its launch in 1998 the thematic indexation of the Flemish Environmental Navigator is carried out manually by legal experts of the University of Ghent, Belgium. However, due to the exponential growth of legal documents a physical indexation process eventually was no longer tenable, nor desirable. Hence, a semi-automatic indexing tool for environmental legislation, called NAVDEX, was developed. A specific algorithm was determined, based On the presence of similar terms in law objects. A parameter was defined, reflecting the strength of the relation between law objects in order to computerise the return on a user's query. 1/7 view, of managing the relations between law objects, a visualisation tool was created in order to provide the legal experts with a detailed overview of all associated law Objects. The testing corpus was decided to be VLAREA, a Flemish order concerning waste prevention and management. The evaluation of the test results was carried out by experts in environmental legislation, who computed the relative recall of several search terms. With an average score of 0.63 NAVDEX is able to retrieve nearly two third of the associated law objects. Consequently the evaluators' conclusions were unanimous so as to define NAVDEX as a useful tool to determine and visualise associated LawObjects

The Most Influential Paper Gerard Salton Never Wrote

Gerard Salton is often credited with developing the vector space model (VSM) for information retrieval (IR). Citations to Salton give the impression that the VSM must have been articulated as an IR model sometime between 1970 and 1975. However, the VSM as it is understood today evolved over a longer time period than is usually acknowledged, and an articulation of the model and its assumptions did not appear in print until several years after those assumptions had been criticized and alternative models proposed. An often cited overview paper titled ???A Vector Space Model for Information Retrieval??? (alleged to have been published in 1975) does not exist, and citations to it represent a confusion of two 1975 articles, neither of which were overviews of the VSM as a model of information retrieval. Until the late 1970s, Salton did not present vector spaces as models of IR generally but rather as models of specifi c computations. Citations to the phantom paper refl ect an apparently widely held misconception that the operational features and explanatory devices now associated with the VSM must have been introduced at the same time it was fi rst proposed as an IR model.published or submitted for publicatio

Does Criticism Overcome the Praises of Journal Impact Factor?

Journal impact factor (IF) as a gauge of influence and impact of a particular journal comparing with other journals in the same area of research, reports the mean number of citations to the published articles in particular journal. Although, IF attracts more attention and being used more frequently than other measures, it has been subjected to criticisms, which overcome the advantages of IF. Critically, extensive use of IF may result in destroying editorial and researchers’ behaviour, which could compromise the quality of scientific articles. Therefore, it is the time of the timeliness and importance of a new invention of journal ranking techniques beyond the journal impact factor

Measuring inter-indexer consistency using a thesaurus

When professional indexers independently assign terms to a given document, the term sets generally differ between indexers. Studies of inter-indexer consistency measure the percentage of matching index terms, but none of them consider the semantic relationships that exist amongst these terms. We propose to represent multiple-indexers data in a vector space and use the cosine metric as a new consistency measure that can be extended by semantic relations between index terms. We believe that this new measure is more accurate and realistic than existing ones and therefore more suitable for evaluation of automatically extracted index terms

Adaptive content mapping for internet navigation

The Internet as the biggest human library ever assembled keeps on growing. Although all kinds of information carriers (e.g. audio/video/hybrid file formats) are available, text based documents dominate. It is estimated that about 80% of all information worldwide stored electronically exists in (or can be converted into) text form. More and more, all kinds of documents are generated by means of a text processing system and are therefore available electronically. Nowadays, many printed journals are also published online and may even discontinue to appear in print form tomorrow. This development has many convincing advantages: the documents are both available faster (cf. prepress services) and cheaper, they can be searched more easily, the physical storage only needs a fraction of the space previously necessary and the medium will not age. For most people, fast and easy access is the most interesting feature of the new age; computer-aided search for specific documents or Web pages becomes the basic tool for information-oriented work. But this tool has problems. The current keyword based search machines available on the Internet are not really appropriate for such a task; either there are (way) too many documents matching the specified keywords are presented or none at all. The problem lies in the fact that it is often very difficult to choose appropriate terms describing the desired topic in the first place. This contribution discusses the current state-of-the-art techniques in content-based searching (along with common visualization/browsing approaches) and proposes a particular adaptive solution for intuitive Internet document navigation, which not only enables the user to provide full texts instead of manually selected keywords (if available), but also allows him/her to explore the whole database

Semantic-driven matchmaking of web services using case-based reasoning

With the rapid proliferation of Web services as the medium of choice to securely publish application services beyond the firewall, the importance of accurate, yet flexible matchmaking of similar services gains importance both for the human user and for dynamic composition engines. In this paper, we present a novel approach that utilizes the case based reasoning methodology for modelling dynamic Web service discovery and matchmaking. Our framework considers Web services execution experiences in the decision making process and is highly adaptable to the service requester constraints. The framework also utilises OWL semantic descriptions extensively for implementing both the components of the CBR engine and the matchmaking profile of the Web services