%0 Conference Paper %1 1348558 %A Zaiane, Osmar R. %A Chen, Jiyang %A Goebel, Randy %B WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis %C New York, NY, USA %D 2007 %I ACM %K 2007 analysis collaboration community database detection mining relation %P 74--81 %R http://doi.acm.org/10.1145/1348549.1348558 %T DBconnect: mining research community on DBLP data %U http://portal.acm.org/citation.cfm?id=1348558&coll=GUIDE&dl=GUIDE&CFID=17695029&CFTOKEN=22803053&ret=1#Fulltext %X Extracting information from large collections of structured, semi-structured or even unstructured data can be a considerable challenge when much of the hidden information is implicit within relationships among entities within the data. Social networks are such data collections in which relationships play a vital role in the knowledge these networks can convey. A bibliographic database is an essential tool for the research community, yet finding and making use of relationships comprised within such a social network is difficult. In this paper we introduce DBconnect, a prototype that exploits the social network coded within the DBLP database by drawing on a new random walk approach to reveal interesting knowledge about the research community and even recommend collaborations. %@ 978-1-59593-848-0

@inproceedings{1348558, abstract = {Extracting information from large collections of structured, semi-structured or even unstructured data can be a considerable challenge when much of the hidden information is implicit within relationships among entities within the data. Social networks are such data collections in which relationships play a vital role in the knowledge these networks can convey. A bibliographic database is an essential tool for the research community, yet finding and making use of relationships comprised within such a social network is difficult. In this paper we introduce DBconnect, a prototype that exploits the social network coded within the DBLP database by drawing on a new random walk approach to reveal interesting knowledge about the research community and even recommend collaborations.}, added-at = {2009-01-14T10:52:18.000+0100}, address = {New York, NY, USA}, author = {Zaiane, Osmar R. and Chen, Jiyang and Goebel, Randy}, biburl = {https://www.bibsonomy.org/bibtex/2913842df65b7827774a8041c9bdce9b6/anneba}, booktitle = {WebKDD/SNA-KDD '07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis}, description = {DBconnect}, doi = {http://doi.acm.org/10.1145/1348549.1348558}, interhash = {baec3eb11b9ac359c0466d3c17520ca5}, intrahash = {913842df65b7827774a8041c9bdce9b6}, isbn = {978-1-59593-848-0}, keywords = {2007 analysis collaboration community database detection mining relation}, location = {San Jose, California}, pages = {74--81}, publisher = {ACM}, timestamp = {2009-01-14T10:52:47.000+0100}, title = {DBconnect: mining research community on DBLP data}, url = {http://portal.acm.org/citation.cfm?id=1348558&coll=GUIDE&dl=GUIDE&CFID=17695029&CFTOKEN=22803053&ret=1#Fulltext}, year = 2007 }