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Internet Technol."],"published-print":{"date-parts":[[2018,8,31]]},"abstract":"<jats:p>Knowledge Bases (KBs) are widely used as one of the fundamental components in Semantic Web applications as they provide facts and relationships that can be automatically understood by machines. Curated knowledge bases usually use Resource Description Framework (RDF) as the data representation model. To query the RDF-presented knowledge in curated KBs, Web interfaces are built via SPARQL Endpoints. Currently, querying SPARQL Endpoints has problems like network instability and latency, which affect the query efficiency. To address these issues, we propose a client-side caching framework, SPARQL Endpoint Caching Framework (SECF), aiming at accelerating the overall querying speed over SPARQL Endpoints. SECF identifies the potential issued queries by leveraging the querying patterns learned from clients\u2019 historical queries and prefecthes\/caches these queries. In particular, we develop a distance function based on graph edit distance to measure the similarity of SPARQL queries. We propose a feature modelling method to transform SPARQL queries to vector representation that are fed into machine-learning algorithms. A time-aware smoothing-based method, Modified Simple Exponential Smoothing (MSES), is developed for cache replacement. Extensive experiments performed on real-world queries showcase the effectiveness of our approach, which outperforms the state-of-the-art work in terms of the overall querying speed.<\/jats:p>","DOI":"10.1145\/3155806","type":"journal-article","created":{"date-parts":[[2018,2,6]],"date-time":"2018-02-06T18:13:28Z","timestamp":1517940808000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["A Learning-Based Framework for Improving Querying on Web Interfaces of Curated Knowledge Bases"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0406-5974","authenticated-orcid":false,"given":"Wei Emma","family":"Zhang","sequence":"first","affiliation":[{"name":"Macquarie University, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quan Z.","family":"Sheng","sequence":"additional","affiliation":[{"name":"Macquarie University, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4149-839X","authenticated-orcid":false,"given":"Lina","family":"Yao","sequence":"additional","affiliation":[{"name":"The University of New South Wales, Sydney, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kerry","family":"Taylor","sequence":"additional","affiliation":[{"name":"Australian National University, Canberra, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ali","family":"Shemshadi","sequence":"additional","affiliation":[{"name":"Complexica, Adelaide, SA, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yongrui","family":"Qin","sequence":"additional","affiliation":[{"name":"University of Huddersfield, Huddersfield, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,2,5]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1080\/00031305.1992.10475879","article-title":"An introduction to kernel and nearest-neighbor nonparametric regression","volume":"46","author":"Altman Naomi S.","year":"1992","unstructured":"Naomi S. Altman . 1992 . An introduction to kernel and nearest-neighbor nonparametric regression . Amer. Stat. 46 , 3 (1992), 175 -- 185 . Naomi S. Altman. 1992. An introduction to kernel and nearest-neighbor nonparametric regression. Amer. Stat. 46, 3 (1992), 175--185.","journal-title":"Amer. Stat."},{"volume-title":"Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911)","author":"Elbassuoni Shady","key":"e_1_2_1_2_1","unstructured":"Shady Elbassuoni , Maya Ramanath , and Gerhard Weikum . Query relaxation for entity-relationship search . In Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911) . 62--76. Shady Elbassuoni, Maya Ramanath, and Gerhard Weikum. Query relaxation for entity-relationship search. In Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911). 62--76."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623677"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-18818-8_15"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijforecast.2006.03.005"},{"key":"e_1_2_1_6_1","volume-title":"Data Mining: Concepts and Techniques","author":"Han Jiawei","year":"2011","unstructured":"Jiawei Han , Jian Pei , and Micheline Kamber . 2011 . Data Mining: Concepts and Techniques . Elsevier . Jiawei Han, Jian Pei, and Micheline Kamber. 2011. Data Mining: Concepts and Techniques. Elsevier."},{"volume-title":"Proceedings of the 11th Extended Semantic Web Conference (ESWC\u201914)","author":"Hasan Rakebul","key":"e_1_2_1_7_1","unstructured":"Rakebul Hasan . Predicting SPARQL query performance and explaining linked data . In Proceedings of the 11th Extended Semantic Web Conference (ESWC\u201914) . 795--805. Rakebul Hasan. Predicting SPARQL query performance and explaining linked data. In Proceedings of the 11th Extended Semantic Web Conference (ESWC\u201914). 795--805."},{"key":"e_1_2_1_8_1","volume-title":"Relations between two sets of variates. Biometrika","author":"Hotelling Harold","year":"1936","unstructured":"Harold Hotelling . 1936. Relations between two sets of variates. Biometrika ( 1936 ), 321--377. Harold Hotelling. 1936. Relations between two sets of variates. Biometrika (1936), 321--377."},{"volume-title":"Principal Component Analysis","author":"Jolliffe Ian","key":"e_1_2_1_9_1","unstructured":"Ian Jolliffe . 2002. Principal Component Analysis . Wiley Online Library . Ian Jolliffe. 2002. Principal Component Analysis. 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Nature 401, 6755 (1999), 788--791."},{"volume-title":"Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911)","author":"Lehmann Jens","key":"e_1_2_1_14_1","unstructured":"Jens Lehmann and Lorenz B\u00fchmann . AutoSPARQL : Let users query your knowledge base . In Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911) . 63--79. Jens Lehmann and Lorenz B\u00fchmann. AutoSPARQL: Let users query your knowledge base. In Proceedings of the 8th Extended Semantic Web Conference (ESWC\u201911). 63--79."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2013.6544811"},{"volume-title":"Proceedings of the 10th Extended Semantic Web Conference (ESWC\u201913)","author":"Lorey Johannes","key":"e_1_2_1_16_1","unstructured":"Johannes Lorey and Felix Naumann . Detecting SPARQL query templates for data prefetching . In Proceedings of the 10th Extended Semantic Web Conference (ESWC\u201913) . 124--139. Johannes Lorey and Felix Naumann. 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