{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T01:55:12Z","timestamp":1775181312742,"version":"3.50.1"},"reference-count":34,"publisher":"Association for Computing Machinery (ACM)","issue":"4","license":[{"start":{"date-parts":[[2017,12,31]],"date-time":"2017-12-31T00:00:00Z","timestamp":1514678400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Google faculty research award"},{"name":"Australian Research Council's Discovery Projects Scheme","award":["DP140101587"],"award-info":[{"award-number":["DP140101587"]}]},{"name":"Australian Research Council DECRA Research Fellowship","award":["DE140100275"],"award-info":[{"award-number":["DE140100275"]}]},{"DOI":"10.13039\/100008242","name":"National ICT Australia","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100008242","id-type":"DOI","asserted-by":"crossref"}]},{"name":"ARC","award":["DP170102726 and DP170102231"],"award-info":[{"award-number":["DP170102726 and DP170102231"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["91646204"],"award-info":[{"award-number":["91646204"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Spatial Algorithms Syst."],"published-print":{"date-parts":[[2017,12,31]]},"abstract":"<jats:p>\n            Since the mid-2000s, everal indexing techniques have been proposed to efficiently answer top-\n            <jats:italic>k<\/jats:italic>\n            spatial-textual queries. However, all of these approaches focus on answering one query at a time. In contrast, how to design efficient algorithms that can exploit similarities between incoming queries to improve performance has received little attention. In this article, we study a series of efficient approaches to\n            <jats:italic>batch process<\/jats:italic>\n            multiple top-\n            <jats:italic>k<\/jats:italic>\n            spatial-textual queries concurrently. We carefully design a variety of indexing structures for the problem space by exploring the effect of prioritizing spatial and textual properties on system performance. Specifically, we present an efficient traversal method, SF-S\n            <jats:sc>ep<\/jats:sc>\n            , over an existing space-prioritized index structure. Then, we propose a new space-prioritized index structure, the MIR-Tree to support a filter-and-refine based technique, SF-G\n            <jats:sc>rp<\/jats:sc>\n            . To support the processing of text-intensive data, we propose an augmented, inverted indexing structure that can easily be added into existing text search engine architectures and a novel traversal method for batch processing of the queries. In all of these approaches, the goal is to improve the overall performance by sharing the I\/O costs of similar queries. Finally, we demonstrate significant I\/O savings in our algorithms over traditional approaches by extensive experiments on three real datasets and compare how properties of different datasets affect the performance. Many applications in streaming, micro-batching of continuous queries, and privacy-aware search can benefit from this line of work.\n          <\/jats:p>","DOI":"10.1145\/3196155","type":"journal-article","created":{"date-parts":[[2018,5,4]],"date-time":"2018-05-04T12:31:01Z","timestamp":1525437061000},"page":"1-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":17,"title":["Batch Processing of Top-\n            <i>k<\/i>\n            Spatial-Textual Queries"],"prefix":"10.1145","volume":"3","author":[{"given":"Farhana M.","family":"Choudhury","sequence":"first","affiliation":[{"name":"School of Science, RMIT University, Victoria, Australia"}]},{"given":"J. Shane","family":"Culpepper","sequence":"additional","affiliation":[{"name":"School of Science, RMIT University, Victoria, Australia"}]},{"given":"Zhifeng","family":"Bao","sequence":"additional","affiliation":[{"name":"School of Science, RMIT University, Victoria, Australia"}]},{"given":"Timos","family":"Sellis","sequence":"additional","affiliation":[{"name":"Data Science Research Institute, Swinburne University of Technology, Hawthorn, Victoria, Australia"}]}],"member":"320","published-online":{"date-parts":[[2018,5,3]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/956863.956944"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2011.5767855"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.14778\/2535569.2448955"},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Yun Chen and J. M. Patel. 2007. Efficient evaluation of all-nearest-neighbor queries. In ICDE. 1056--1065.  Yun Chen and J. M. Patel. 2007. Efficient evaluation of all-nearest-neighbor queries. In ICDE. 1056--1065.","DOI":"10.1109\/ICDE.2007.368964"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/2786006.2786008"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.14778\/2904121.2904122"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2063576.2063641"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687627.1687666"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/2433396.2433412"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1935826.1935858"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2009916.2010048"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/971697.602266"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1516360.1516376"},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","unstructured":"H. Kido Y. Yanagisawa and T. Satoh. 2005. An anonymous communication technique using dummies for location-based services. In ICPS. 88--97.  H. Kido Y. Yanagisawa and T. Satoh. 2005. An anonymous communication technique using dummies for location-based services. In ICPS. 88--97.","DOI":"10.1109\/ICDE.2005.269"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2010.149"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1626536.1626540"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2838931.2838933"},{"key":"e_1_2_1_18_1","volume-title":"Introduction to Information Retrieval","author":"Manning Christopher D.","unstructured":"Christopher D. Manning , Prabhakar Raghavan , and Hinrich Sch\u00fatze . 2008. Introduction to Information Retrieval . Cambridge University Press . Christopher D. Manning, Prabhakar Raghavan, and Hinrich Sch\u00fatze. 2008. Introduction to Information Retrieval. 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Papadopoulos and Yannis Manolopoulos . 1998 . Multiple range query optimization in spatial databases. In ADBIS. 71--82. Apostolos N. Papadopoulos and Yannis Manolopoulos. 1998. Multiple range query optimization in spatial databases. In ADBIS. 71--82."},{"key":"e_1_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Jo\u00e3o B. Rocha-Junior Orestis Gkorgkas Simon Jonassen and Kjetil N\u00f8rv\u00e5g. 2011. Efficient processing of top-k spatial keyword queries. In SSTD. 205--222.   Jo\u00e3o B. Rocha-Junior Orestis Gkorgkas Simon Jonassen and Kjetil N\u00f8rv\u00e5g. 2011. Efficient processing of top-k spatial keyword queries. In SSTD. 205--222.","DOI":"10.1007\/978-3-642-22922-0_13"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/0306-4573(88)90021-0"},{"key":"e_1_2_1_24_1","volume-title":"Retrieved","year":"2010","unstructured":"SearchEngineLand. 2010 . Microsoft: 53 Percent Of Mobile Searches Have Local Intent . 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