http://www.bibsonomy.org/burst/user/renew/evolutionBibSonomy BuRST Feed for /user/renew/evolution2008-09-05T07:59:38+02:00http://www.bibsonomy.org/bibtex/2f81bc9315be5c3fb426ee22b2508c4d6/renewrenew2008-04-21T12:58:08+02:00evolution tdt topic visualization <span style="color:#555555;">Ata <a href="http://www.bibsonomy.org/author/Kaban">Kaban</a> und Mark <a href="http://www.bibsonomy.org/author/Girolami">Girolami</a> </span><em>Journal of Intelligent Information Systems</em><em>18(2/3):107--125</em>(<em>2002</em>)Mon Apr 21 12:58:08 CEST 2008Journal of Intelligent Information Systems2/3107--125A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams182002evolution tdt topic visualization We propose a novel probabilistic method, based on latent variable models, for unsupervised topographic visualisation of dynamically evolving, coherent textual information. This can be seen as a complementary tool for topic detection and tracking applications. This is achieved by the exploitation of the a priori domain knowledge available, that there are relatively homogeneous temporal segments in the data stream. In a different manner from topographical techniques previously utilized for static text collections, the topography is an outcome of the coherence in time of the data stream in the proposed model. Simulation results on both toy-data settings and an actual application on Internet chat line discussion analysis is presented by way of demonstration.http://www.bibsonomy.org/bibtex/2c46d19a954b854e23d9ce9bd859fb8e2/renewrenew2008-03-26T12:43:53+01:00evolution traceability software <span style="color:#555555;">Hsin-Yi <a href="http://www.bibsonomy.org/author/Jiang">Jiang</a> und Tien <a href="http://www.bibsonomy.org/author/Nguyen">Nguyen</a> und Ing-Xiang <a href="http://www.bibsonomy.org/author/Chen">Chen</a> </span><em>Intl Conf. on Software Engineering, </em><em>Leipzig, Germany, </em><em>May2008. </em>Wed Mar 26 12:43:53 CET 2008Leipzig, GermanyIntl Conf. on Software EngineeringMayIncremental Latent Semantic Indexing for Effective, Automatic Traceability Link Evolution Management2008evolution traceability software Maintaining traceability links among software artifacts is particularly important for many software engineering tasks. Even though automatic traceability link recovery tools are successful in identifying the semantic connections among software artifacts produced during software development, no existing traceability link management approach can e®ec- tively and automatically deal with software evolution. We propose a technique to automatically manage traceability link evolution and update the links in evolving software. Our novel technique, called incremental Latent Semantic Index- ing (iLSI), allows the fast and low-cost LSI computation for the update of traceability links by analyzing the changes to software artifacts and by re-using the results from previous LSI computation before the changes. We present our iLSI technique, and describe a complete automatic traceability link evolution management tool, TLEM, that is capable of interactively and quickly updating traceability links in the presence of evolving software artifacts. We report on our empirical evaluation with various experimental studies to assess the performance and usefulness of our approach.