Clustering and identifying temporal trends in document databases

by: A Popescul, GW Flake, S Lawrence, LH Ungar, CL Giles

Advances in Digital Libraries, 2000. ADL 2000. Proceedings. IEEE (2000), pp. 173-182.

View FullText article

IEEE Explore

Reviews [Write a review of this article]

There are no reviews of this article

Find related articles from these CiteULike users

weiwu, ehohman, pim (group)

Find related articles with these CiteULike tags

citation, no-tag, similarity

Abstract

We introduce a simple and efficient method for clustering and identifying temporal trends in hyper-linked document databases. Our method can scale to large datasets because it exploits the underlying regularity often found in hyper-linked document databases. Because of this scalability, we can use our method to study the temporal trends of individual clusters in a statistically meaningful manner. As an example of our approach, we give a summary of the temporal trends found in a scientific literature database with thousands of documents

@inproceedings{citeulike:776816, abstract = {We introduce a simple and efficient method for clustering and identifying temporal trends in hyper-linked document databases. Our method can scale to large datasets because it exploits the underlying regularity often found in hyper-linked document databases. Because of this scalability, we can use our method to study the temporal trends of individual clusters in a statistically meaningful manner. As an example of our approach, we give a summary of the temporal trends found in a scientific literature database with thousands of documents}, author = {Popescul, A. and Flake, G. W. and Lawrence, S. and Ungar, L. H. and Giles, C. L. }, citeulike-article-id = {776816}, journal = {Advances in Digital Libraries, 2000. ADL 2000. Proceedings. IEEE}, keywords = {citation, similarity}, pages = {173--182}, posted-at = {2006-07-28 00:35:32}, priority = {2}, title = {Clustering and identifying temporal trends in document databases}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=848380}, year = {2000} }

RIS record

TY - CONF ID - citeulike:776816 L3 - citeulike-article-id:776816 TI - Clustering and identifying temporal trends in document databases JF - Advances in Digital Libraries, 2000. ADL 2000. Proceedings. IEEE SP - 173 EP - 182 N2 - We introduce a simple and efficient method for clustering and identifying temporal trends in hyper-linked document databases. Our method can scale to large datasets because it exploits the underlying regularity often found in hyper-linked document databases. Because of this scalability, we can use our method to study the temporal trends of individual clusters in a statistically meaningful manner. As an example of our approach, we give a summary of the temporal trends found in a scientific literature database with thousands of documents KW - citation KW - similarity AU - Popescul, A AU - Flake, GW AU - Lawrence, S AU - Ungar, LH AU - Giles, CL PY - 2000/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=848380 ER -

RIS BibTeX