%0 Conference Paper %1 nurminen05extminer %A Nurminen, Miika %A Honkaranta, Anne %A Kärkkäinen, Tommi %B International workshop on Integrating Data Mining, Databases and Information Retrieval (IDDI'05), Proceedings of the 16th International Workshop on Database and Expert Systems Applications %D 2005 %I IEEE Computer Society %K cites.dss.r cites.procm myown research.clustering research.ir research.ir.ranking research.mining research.papers research.xml %P 1036-1040 %T ExtMiner: Combining Multiple Ranking and Clustering Algorithms for Structured Document Retrieval %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1508411 %X This paper introduces ExtMiner, a platform and potential tool for information management in SMEs (small & medium-size enterprise), or for organizational workgroups. ExtMiner supports interactive and iterative clustering of documents. It provides users with a visual cluster and list views at the same time, supporting iterative search process. ExtMiner may also be applied as a platform for research on retrieval fusion, since it combines search, clustering and visualization algorithms. ExtMiner was evaluated with three document collections. Although the findings were encouraging the user interface and performance with large document repositories need further development.

@inproceedings{nurminen05extminer, abstract = { This paper introduces ExtMiner, a platform and potential tool for information management in SMEs (small & medium-size enterprise), or for organizational workgroups. ExtMiner supports interactive and iterative clustering of documents. It provides users with a visual cluster and list views at the same time, supporting iterative search process. ExtMiner may also be applied as a platform for research on retrieval fusion, since it combines search, clustering and visualization algorithms. ExtMiner was evaluated with three document collections. Although the findings were encouraging the user interface and performance with large document repositories need further development.}, added-at = {2009-06-25T16:49:34.000+0200}, author = {Nurminen, Miika and Honkaranta, Anne and K\"arkk\"ainen, Tommi}, biburl = {https://www.bibsonomy.org/bibtex/23ec379c314de9661680ae26e06d59d88/msn}, booktitle = {International workshop on Integrating Data Mining, Databases and Information Retrieval (IDDI'05), Proceedings of the 16th International Workshop on Database and Expert Systems Applications}, file = {nurminen05extminer.pdf:papers\\dexa\\nurminen05extminer.pdf:PDF}, interhash = {1749549b40064a2fca84c248f00050d8}, intrahash = {3ec379c314de9661680ae26e06d59d88}, keywords = {cites.dss.r cites.procm myown research.clustering research.ir research.ir.ranking research.mining research.papers research.xml}, location = {Copenhagen, Denmark}, pages = {1036-1040}, publisher = {IEEE Computer Society}, timestamp = {2012-04-12T21:20:00.000+0200}, title = {Ext{M}iner: Combining Multiple Ranking and Clustering Algorithms for Structured Document Retrieval}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1508411}, year = 2005 }