{"id":"https://openalex.org/W2295329165","doi":"https://doi.org/10.1007/978-3-319-28430-9_20","title":"Cross-Correlation as Tool to Determine the Similarity of Series of Measurements for Big-Data Analysis Tasks","display_name":"Cross-Correlation as Tool to Determine the Similarity of Series of Measurements for Big-Data Analysis Tasks","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2295329165","doi":"https://doi.org/10.1007/978-3-319-28430-9_20","mag":"2295329165"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-319-28430-9_20","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-28430-9_20","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089924780","display_name":"Marcus Hilbrich","orcid":"https://orcid.org/0000-0003-3717-9449"},"institutions":[{"id":"https://openalex.org/I206945453","display_name":"Paderborn University","ror":"https://ror.org/058kzsd48","country_code":"DE","type":"education","lineage":["https://openalex.org/I206945453"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Marcus Hilbrich","raw_affiliation_strings":["Software Quality Lab (s-lab), Universit\u00e4t Paderborn, Paderborn, Germany"],"affiliations":[{"raw_affiliation_string":"Software Quality Lab (s-lab), Universit\u00e4t Paderborn, Paderborn, Germany","institution_ids":["https://openalex.org/I206945453"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047894471","display_name":"R. M\u00fcller-Pfefferkorn","orcid":"https://orcid.org/0000-0001-8719-5741"},"institutions":[{"id":"https://openalex.org/I78650965","display_name":"TU Dresden","ror":"https://ror.org/042aqky30","country_code":"DE","type":"education","lineage":["https://openalex.org/I78650965"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ralph M\u00fcller-Pfefferkorn","raw_affiliation_strings":["Center for Information Services and High Performance Computing (ZIH), Technische Universit\u00e4t Dresden, Dresden, Germany"],"affiliations":[{"raw_affiliation_string":"Center for Information Services and High Performance Computing (ZIH), Technische Universit\u00e4t Dresden, Dresden, Germany","institution_ids":["https://openalex.org/I78650965"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089924780"],"corresponding_institution_ids":["https://openalex.org/I206945453"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":null,"fwci":0.863,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.7128821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"263","last_page":"282"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8103427886962891},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6521393060684204},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6132564544677734},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5020904541015625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4923316240310669},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.48960381746292114},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.45886892080307007},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36138612031936646},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23335453867912292},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10531914234161377}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8103427886962891},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6521393060684204},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6132564544677734},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5020904541015625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4923316240310669},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.48960381746292114},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.45886892080307007},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36138612031936646},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23335453867912292},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10531914234161377},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-3-319-28430-9_20","is_oa":false,"landing_page_url":"https://doi.org/10.1007/978-3-319-28430-9_20","pdf_url":null,"source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W161049316","https://openalex.org/W202059055","https://openalex.org/W221263235","https://openalex.org/W938539187","https://openalex.org/W1480411462","https://openalex.org/W1516506771","https://openalex.org/W1538118628","https://openalex.org/W1565377632","https://openalex.org/W1583975142","https://openalex.org/W1673310716","https://openalex.org/W1674877186","https://openalex.org/W1687244664","https://openalex.org/W1884606608","https://openalex.org/W1913306154","https://openalex.org/W1938740620","https://openalex.org/W1971399824","https://openalex.org/W1977556410","https://openalex.org/W1987971958","https://openalex.org/W1990061958","https://openalex.org/W2006263683","https://openalex.org/W2007210316","https://openalex.org/W2011430131","https://openalex.org/W2028569720","https://openalex.org/W2028641616","https://openalex.org/W2074231493","https://openalex.org/W2087554554","https://openalex.org/W2090506829","https://openalex.org/W2101005720","https://openalex.org/W2102129129","https://openalex.org/W2127218421","https://openalex.org/W2128061541","https://openalex.org/W2130200371","https://openalex.org/W2131960077","https://openalex.org/W2150847526","https://openalex.org/W2165654401","https://openalex.org/W2169542477","https://openalex.org/W2477818891","https://openalex.org/W2482589566","https://openalex.org/W2492292585","https://openalex.org/W2535964966","https://openalex.org/W2795859997","https://openalex.org/W2904250082","https://openalex.org/W3152455277","https://openalex.org/W4250503569","https://openalex.org/W6600005074","https://openalex.org/W6634236767"],"related_works":["https://openalex.org/W4390608645","https://openalex.org/W4247566972","https://openalex.org/W4394895745","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2622688551","https://openalex.org/W1550175370","https://openalex.org/W1990205660"],"abstract_inverted_index":null,"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}