{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00241729","sets":["1164:1165:11462:11815"]},"path":["11815"],"owner":"44499","recid":"241729","title":["2次元ポリゴンデータを対象としたIntersectionクエリに対する学習型カーディナリティ推定器"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-12-19"},"_buckets":{"deposit":"6857ed0e-b12e-4ee3-8b81-28ef8b4c6268"},"_deposit":{"id":"241729","pid":{"type":"depid","value":"241729","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"2次元ポリゴンデータを対象としたIntersectionクエリに対する学習型カーディナリティ推定器","author_link":["665974","665971","665973","665968","665975","665970","665969","665972"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"2次元ポリゴンデータを対象としたIntersectionクエリに対する学習型カーディナリティ推定器"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"データアルゴリズム","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-12-19","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"大阪大学大学院情報科学研究科"},{"subitem_text_value":"大阪大学大学院情報科学研究科"},{"subitem_text_value":"大阪大学大学院情報科学研究科"},{"subitem_text_value":"大阪大学大学院情報科学研究科"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/241729/files/IPSJ-DBS24180008.pdf","label":"IPSJ-DBS24180008.pdf"},"date":[{"dateType":"Available","dateValue":"2026-12-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DBS24180008.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"13"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"9d7629a0-b3d3-4bcf-aee7-ead8e6b85d77","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ji, Yuchen"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"天方, 大地"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐々木, 勇和"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"原, 隆浩"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuchen, Ji","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Daichi, Amagata","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yuya, Sasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takahiro, Hara","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10112482","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-871X","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ポリゴンのような複雑な形状のデータに対するクエリ処理において，その結果のサイズを推定するカーディナリティ推定問題は挑戦的であるが，クエリスケジューリングや最適化において重要な役割を示している．例えば，高速かつ性格な推定は，クエリ処理全体の効率性に大きく貢献する．既存のカーディナリティ推定技術はヒストグラムを用いているものが多く，ポリゴンを最小外接矩形に近似すれば適用可能であるが，正確性に欠けてしまう．この問題を解決するため，本稿では 2 次元ポリゴンデータを対象とした intersection クエリに対する学習型カーディナリティ推定器である PolyCard を提案する．数百万ポリゴンによって構成される実データを用いた実験により，PolyCard の効率性と正確性を確認したところ，PolyCard は以下の特長がある．（1）正確性：既存技術に対して 30% 精度を向上している．（2）高速性：一度の推定に 4 マイクロ秒しか要しない．（3）安定性：PolyCard は異なるカーディナリティとなるクエリに対して頑健である．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告データベースシステム（DBS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-12-19","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2024-DBS-180"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:46:30.418559+00:00","updated":"2025-01-19T07:33:57.826567+00:00","id":241729}