We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the "aboutness" of a corpus of scientific and technical publications by bridging the gap between pure statistical approaches and symbolic techniques. In the present paper, an experiment on unsupervised textmining is performed on a corpus of scientific titles and abstracts from 16 prominent IR journals. The preliminary results showed that TermWatch was able to capture low occurring phenomena which the usual clustering methods based on co-occurrence may not highlight. The results also reflect the expressive power of terminological variations as a means to capture the structure of research topics contained in a corpus
Term extraction is an essential tool for content-based publication analysis, and has a long history ...
The extraction of relevant information in texts constitutes a fundamental process of text mining. We...
Topic models are a well known clustering approach for textual data, which provides promising applica...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
International audienceWe present a system for mapping the structure of research topics in a corpus. ...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
International audienceThis paper examines further a research hypothesis that syntactic variations ar...
We present the TermWatch system which combines linguistic engineering with clustering and visualisat...
A multi-disciplinary approach integrating computational linguistic techniques is necessary to elabor...
Matière NucléaireWe present the TermWatch system which combines linguistic engineering with clusteri...
In earlier studies (e.g. Glänzel and Thijs in Scientometrics, 2017) we have used components of text ...
This paper describes how methods and techniques developed in corpus linguistics can be used to compa...
The introduction of textual analysis and the use of lexical similarities already proved an important...
Term extraction is an essential tool for content-based publication analysis, and has a long history ...
The extraction of relevant information in texts constitutes a fundamental process of text mining. We...
Topic models are a well known clustering approach for textual data, which provides promising applica...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
International audienceWe present a system for mapping the structure of research topics in a corpus. ...
We present a system for mapping the structure of research topics in a corpus. TermWatch portrays the...
International audienceThis paper examines further a research hypothesis that syntactic variations ar...
We present the TermWatch system which combines linguistic engineering with clustering and visualisat...
A multi-disciplinary approach integrating computational linguistic techniques is necessary to elabor...
Matière NucléaireWe present the TermWatch system which combines linguistic engineering with clusteri...
In earlier studies (e.g. Glänzel and Thijs in Scientometrics, 2017) we have used components of text ...
This paper describes how methods and techniques developed in corpus linguistics can be used to compa...
The introduction of textual analysis and the use of lexical similarities already proved an important...
Term extraction is an essential tool for content-based publication analysis, and has a long history ...
The extraction of relevant information in texts constitutes a fundamental process of text mining. We...
Topic models are a well known clustering approach for textual data, which provides promising applica...