{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,2,19]],"date-time":"2023-02-19T02:27:06Z","timestamp":1676773626013},"reference-count":9,"publisher":"Association for Computing Machinery (ACM)","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2009,8]]},"abstract":"<jats:p>\n            We propose to demonstrate a practical alternative approach to the current state-of-the-art query processing techniques, called the \"\n            <jats:italic>Query Mesh<\/jats:italic>\n            \" (or\n            <jats:italic>QM<\/jats:italic>\n            , for short). The main idea of\n            <jats:italic>QM<\/jats:italic>\n            is to compute multiple routes (i.e., query plans), each designed for a particular subset of data with distinct statistical properties. Based on the execution routes and the data characteristics, a\n            <jats:italic>classifier<\/jats:italic>\n            model is induced and is used to partition new data tuples to assign the best routes for their processing. We propose to demonstrate the\n            <jats:italic>QM<\/jats:italic>\n            framework in the streaming context using our demo application, called the \"\n            <jats:italic>Ubi-City<\/jats:italic>\n            \". We will illustrate the innovative features of\n            <jats:italic>QM<\/jats:italic>\n            , including: the\n            <jats:italic>QM<\/jats:italic>\n            optimization with the integrated machine learning component, the\n            <jats:italic>QM<\/jats:italic>\n            execution using the efficient \"\n            <jats:italic>Self-Routing Fabric<\/jats:italic>\n            \" infrastructure, and finally, the\n            <jats:italic>QM<\/jats:italic>\n            adaptive component that performs the online adaptation of\n            <jats:italic>QM<\/jats:italic>\n            with near-zero runtime overhead.\n          <\/jats:p>","DOI":"10.14778\/1687553.1687583","type":"journal-article","created":{"date-parts":[[2014,6,24]],"date-time":"2014-06-24T12:17:57Z","timestamp":1403612277000},"page":"1530-1533","source":"Crossref","is-referenced-by-count":3,"title":["Query mesh"],"prefix":"10.14778","volume":"2","author":[{"given":"Rimma V.","family":"Nehme","sequence":"first","affiliation":[{"name":"Purdue University"}]},{"given":"Karen E.","family":"Works","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute"}]},{"given":"Elke A.","family":"Rundensteiner","sequence":"additional","affiliation":[{"name":"Worcester Polytechnic Institute"}]},{"given":"Elisa","family":"Bertino","sequence":"additional","affiliation":[{"name":"Purdue University"}]}],"member":"320","published-online":{"date-parts":[[2009,8]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1561\/1900000001"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1015231126594"},{"key":"e_1_2_1_3_1","volume-title":"VLDB","author":"Cape E. R.","year":"2004"},{"key":"e_1_2_1_4_1","unstructured":"T. M. Mitchell. Machine Learning. McGraw-Hill NY 1997.   T. M. Mitchell. Machine Learning . McGraw-Hill NY 1997."},{"key":"e_1_2_1_5_1","volume-title":"McGraw-Hill Higher Education","author":"Ramakrishnan R.","year":"2000"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2008.4497449"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1516360.1516452"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCIT.2007.382"},{"key":"e_1_2_1_9_1","unstructured":"The Carbon Project. http:\/\/www.thecarbonproject.com\/.  The Carbon Project. http:\/\/www.thecarbonproject.com\/."}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/1687553.1687583","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:59:26Z","timestamp":1672225166000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/1687553.1687583"}},"subtitle":["multi-route query processing technology"],"short-title":[],"issued":{"date-parts":[[2009,8]]},"references-count":9,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2009,8]]}},"alternative-id":["10.14778\/1687553.1687583"],"URL":"https:\/\/doi.org\/10.14778\/1687553.1687583","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2009,8]]}}}