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The main search operation on interval data is the retrieval of data intervals that intersect (i.e., overlap with) a query interval (e.g., find records which were valid in September 2020, find temperature readings with non-zero probability to be within [24, 26] degrees). As query results could be many, we need mechanisms that filter or order them based on how relevant they are to the query interval. We define alternative relevance scores between a data and a query interval based on their (relative) overlap. We define relevance queries, which compute only a subset of the most relevant intervals that intersect a query. Then, we propose a framework for evaluating relevance queries that can be applied on popular domain-partitioning interval indices (interval tree and HINT). We present experiments on real datasets that demonstrate the efficiency of our framework over baseline approaches.<\/jats:p>","DOI":"10.1145\/3725343","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T21:23:29Z","timestamp":1750281809000},"page":"1-26","source":"Crossref","is-referenced-by-count":0,"title":["Relevance Queries for Interval Data"],"prefix":"10.1145","volume":"3","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8846-4330","authenticated-orcid":false,"given":"Panagiotis","family":"Bouros","sequence":"first","affiliation":[{"name":"Institute of Computer Science, Johannes Gutenberg University Mainz, Mainz, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3423-4895","authenticated-orcid":false,"given":"Nikos","family":"Mamoulis","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, University of Ioannina, Ioannina, Greece and Archimedes, Athena Research Center, Athens, Greece"}]}],"member":"320","published-online":{"date-parts":[[2025,6,18]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2452376.2452443"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE60146.2024.00041"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/978--3-031--68309--1_12"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/J.IS.2020.101679"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/S007780050028"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340964.3340965"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978--3--319--96655--7_3"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137628.3137644"},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/S00778-020-00639-0"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2619088"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3603719.3603732"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/872757.872823"},{"key":"e_1_2_1_13_1","first-page":"1271","volume-title":"Proceedings of the 31st International Conference on Very Large Data Bases","author":"Cheng Reynold","year":"2005","unstructured":"Reynold Cheng, Sarvjeet Singh, and Sunil Prabhakar. 2005. 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