{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,8]],"date-time":"2024-06-08T06:39:56Z","timestamp":1717828796232},"reference-count":13,"publisher":"Association for Computing Machinery (ACM)","issue":"13","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:p>\n            We demonstrate our SPIRE technology for supporting interactive mining of both positive and negative rules at the speed of thought. It is often misleading to learn only about positive rules, yet extremely revealing to find strongly supported negative rules. Key technical contributions of SPIRE including\n            <jats:italic>region-wise abstractions of rules, positive-negative rule relationship analysis, rule redundancy management<\/jats:italic>\n            and\n            <jats:italic>rule visualization<\/jats:italic>\n            supporting novel\n            <jats:italic>exploratory queries<\/jats:italic>\n            will be showcased. The audience can interactively explore complex rule relationships in a visual manner, such as comparing negative rules with their positive counterparts, that would otherwise take prohibitive time. Overall, our SPIRE system provides data analysts with rich insights into rules and rule relationships while significantly reducing manual effort and time investment required.\n          <\/jats:p>","DOI":"10.14778\/2733004.2733053","type":"journal-article","created":{"date-parts":[[2015,5,12]],"date-time":"2015-05-12T15:37:52Z","timestamp":1431445072000},"page":"1653-1656","source":"Crossref","is-referenced-by-count":3,"title":["SPIRE"],"prefix":"10.14778","volume":"7","author":[{"given":"Xika","family":"Lin","sequence":"first","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA"}]},{"given":"Abhishek","family":"Mukherji","sequence":"additional","affiliation":[{"name":"Samsung Research America - Silicon Valley, San Jose CA"}]},{"given":"Elke A.","family":"Rundensteiner","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA"}]},{"given":"Matthew O.","family":"Ward","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute, Worcester, MA"}]}],"member":"320","published-online":{"date-parts":[[2014,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/69.940730"},{"key":"e_1_2_1_2_1","first-page":"487","volume-title":"VLDB'94","author":"Agrawal R.","year":"1994","unstructured":"R. Agrawal and R. Srikant . Fast algorithms for mining association rules in large databases . In VLDB'94 , pages 487 -- 499 , 1994 . R. Agrawal and R. Srikant. Fast algorithms for mining association rules in large databases. In VLDB'94, pages 487--499, 1994."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.5555\/1053072.1053078"},{"key":"e_1_2_1_4_1","unstructured":"A. Asuncion and D. Newman. UCI machine learning repository. http:\/\/www.ics.uci.edu\/ mlearn\/MLRepository.html November 2007.  A. Asuncion and D. Newman. UCI machine learning repository. http:\/\/www.ics.uci.edu\/ mlearn\/MLRepository.html November 2007."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335372"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.14778\/2535569.2448953"},{"key":"e_1_2_1_7_1","volume-title":"FIMI'04","author":"Lucchese C.","year":"2004","unstructured":"C. Lucchese , S. Orlando , R. Perego , and F. Silvestri . Webdocs: a real-life huge transactional dataset . In FIMI'04 , 2004 . C. Lucchese, S. Orlando, R. Perego, and F. Silvestri. Webdocs: a real-life huge transactional dataset. In FIMI'04, 2004."},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465245"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2505515.2505631"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1057\/palgrave.ivs.9500025"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2012.86"},{"key":"e_1_2_1_12_1","volume-title":"March","year":"2014","unstructured":"Xmdvtool home page. http:\/\/davis.wpi.edu\/ xmdv\/ , March 2014 . Xmdvtool home page. http:\/\/davis.wpi.edu\/ xmdv\/, March 2014."},{"key":"e_1_2_1_13_1","first-page":"283","volume-title":"SIG KDD","author":"Zaki M. J.","year":"1997","unstructured":"M. J. Zaki , S. Parthasarathy , M. Ogihara , and W. Li . New algorithms for fast discovery of association rules . In SIG KDD , pages 283 -- 286 , Aug 1997 . M. J. Zaki, S. Parthasarathy, M. Ogihara, and W. Li. New algorithms for fast discovery of association rules. In SIG KDD, pages 283--286, Aug 1997."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2733004.2733053","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T09:37:16Z","timestamp":1672220236000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2733004.2733053"}},"subtitle":["supporting parameter-driven interactive rule mining and exploration"],"short-title":[],"issued":{"date-parts":[[2014,8]]},"references-count":13,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2014,8]]}},"alternative-id":["10.14778\/2733004.2733053"],"URL":"https:\/\/doi.org\/10.14778\/2733004.2733053","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2014,8]]}}}