{"id":"https://openalex.org/W2157912840","doi":"https://doi.org/10.1145/1273496.1273588","title":"Learning for efficient retrieval of structured data with noisy queries","display_name":"Learning for efficient retrieval of structured data with noisy queries","publication_year":2007,"publication_date":"2007-06-20","ids":{"openalex":"https://openalex.org/W2157912840","doi":"https://doi.org/10.1145/1273496.1273588","mag":"2157912840"},"language":"en","primary_location":{"id":"doi:10.1145/1273496.1273588","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1273496.1273588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th international conference on Machine learning","raw_type":"proceedings-article"},"type":"article","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/A5080521049","display_name":"Charles Parker","orcid":null},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Charles Parker","raw_affiliation_strings":["Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030052689","display_name":"Alan Fern","orcid":"https://orcid.org/0000-0001-5851-8935"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan Fern","raw_affiliation_strings":["Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014260664","display_name":"Prasad Tadepalli","orcid":"https://orcid.org/0000-0003-2736-3912"},"institutions":[{"id":"https://openalex.org/I131249849","display_name":"Oregon State University","ror":"https://ror.org/00ysfqy60","country_code":"US","type":"education","lineage":["https://openalex.org/I131249849"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Prasad Tadepalli","raw_affiliation_strings":["Oregon State University, Corvallis, OR"],"affiliations":[{"raw_affiliation_string":"Oregon State University, Corvallis, OR","institution_ids":["https://openalex.org/I131249849"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080521049"],"corresponding_institution_ids":["https://openalex.org/I131249849"],"apc_list":null,"apc_paid":null,"fwci":0.9715,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.778827,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"729","last_page":"736"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":1.0,"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/T11309","display_name":"Music and Audio Processing","score":1.0,"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/T11269","display_name":"Algorithms and Data Compression","score":0.991599977016449,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.8264118432998657},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.7489427328109741},{"id":"https://openalex.org/keywords/data-retrieval","display_name":"Data retrieval","score":0.6103969812393188},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5679618716239929},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5373441576957703},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.42882031202316284},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41361871361732483},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4122583866119385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36604273319244385},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.343513548374176}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8264118432998657},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.7489427328109741},{"id":"https://openalex.org/C551230270","wikidata":"https://www.wikidata.org/wiki/Q4368942","display_name":"Data retrieval","level":2,"score":0.6103969812393188},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5679618716239929},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5373441576957703},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.42882031202316284},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41361871361732483},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4122583866119385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36604273319244385},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.343513548374176},{"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1273496.1273588","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1273496.1273588","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th international conference on Machine learning","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.75.718","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.75.718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cs.oregonstate.edu/~tadepall/research/papers/fast-icml07.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.550000011920929}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332180","display_name":"Defense Advanced Research Projects Agency","ror":"https://ror.org/02caytj08"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W3773308","https://openalex.org/W38597621","https://openalex.org/W155081921","https://openalex.org/W1541459201","https://openalex.org/W1559819186","https://openalex.org/W1792924715","https://openalex.org/W1975830550","https://openalex.org/W2014706029","https://openalex.org/W2024046085","https://openalex.org/W2027518030","https://openalex.org/W2065528935","https://openalex.org/W2087064593","https://openalex.org/W2102122585","https://openalex.org/W2133296809","https://openalex.org/W2164312060","https://openalex.org/W2176165178","https://openalex.org/W2429914308","https://openalex.org/W6601524540","https://openalex.org/W6638084862","https://openalex.org/W6683645735"],"related_works":["https://openalex.org/W2125652721","https://openalex.org/W1540371141","https://openalex.org/W4231274751","https://openalex.org/W1549363203","https://openalex.org/W2154063878","https://openalex.org/W2556012038","https://openalex.org/W1489772951","https://openalex.org/W1538046993","https://openalex.org/W3082059448","https://openalex.org/W4313640622"],"abstract_inverted_index":{"Increasingly":[0],"large":[1],"collections":[2],"of":[3,9,41,63,71,83],"structured":[4],"data":[5,43],"necessitate":[6],"the":[7,39,60,69],"development":[8],"efficient,":[10],"noise-tolerant":[11],"retrieval":[12,42,57,61],"tools.":[13],"In":[14],"this":[15,19],"work,":[16],"we":[17],"consider":[18],"issue":[20],"and":[21,59],"describe":[22],"an":[23,47],"approach":[24,73],"to":[25,54],"learn":[26],"a":[27,78],"similarity":[28],"function":[29],"that":[30,36,49],"is":[31],"not":[32],"only":[33],"accurate,":[34],"but":[35],"also":[37],"increases":[38],"effectiveness":[40,70],"structures.":[44],"We":[45,67],"present":[46],"algorithm":[48],"uses":[50],"functional":[51],"gradient":[52],"boosting":[53],"maximize":[55],"both":[56],"accuracy":[58],"efficiency":[62],"vantage":[64],"point":[65],"trees.":[66],"demonstrate":[68],"our":[72],"on":[74],"two":[75],"datasets,":[76],"including":[77],"moderately":[79],"sized":[80],"real-world":[81],"dataset":[82],"folk":[84],"music.":[85]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}