Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Centering: a framework for modeling the local coherence of discourse
Computational Linguistics
Automatic text decomposition using text segments and text themes
Proceedings of the the seventh ACM conference on Hypertext
Internet browsing and searching: user evaluations of category map and concept space techniques
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Generic topic segmentation of document texts
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Visualizing the non-visual: spatial analysis and interaction with information from text documents
INFOVIS '95 Proceedings of the 1995 IEEE Symposium on Information Visualization
TextTiling: segmenting text into multi-paragraph subtopic passages
Computational Linguistics
Robust pronoun resolution with limited knowledge
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Concept identification and presentation in the context of technical text summarization
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLPWorkshop on Automatic summarization - Volume 4
Finding an answer to a question
Proceedings of the 2006 international workshop on Research issues in digital libraries
A document browsing tool: using lexical classes to convey information
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
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Most work in text retrieval aims at presenting the information held by several texts in order to give entry clues towards these texts and to allow a navigation between them. Besides, a lesser interest is dedicated to the definition of principles for accessing content of single documents. As most information retrieval systems return documents from an initial request made of words, a usual solution consists of presenting document titles and highlighting words of the request inside a passage or in the whole document. Such a presentation does not allow a rapid reading and systems cannot satisfy themselves with it. Our studies lead us to provide indicative and informative view of texts as in summarization systems. We offer the user different levels of abstraction of a text: the first is a global overview, where global topics are indicated and positioned in the text. The second level of abstraction goes deeper in the topic description by adding local topics and information about the argumentative role of the segments. In this paper, we will detail the extraction of thematic descriptors and meta-descriptors that relies on recurrence -respectively in a text or in the corpus- and how their characterization provides the segment structuring.