{"id":"https://openalex.org/W2050778977","doi":"https://doi.org/10.1145/1517472.1517477","title":"Consistent phrase relevance measures","display_name":"Consistent phrase relevance measures","publication_year":2008,"publication_date":"2008-08-24","ids":{"openalex":"https://openalex.org/W2050778977","doi":"https://doi.org/10.1145/1517472.1517477","mag":"2050778977"},"language":"en","primary_location":{"id":"doi:10.1145/1517472.1517477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1517472.1517477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising","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/A5066873932","display_name":"Wen-tau Yih","orcid":null},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Wen-tau Yih","raw_affiliation_strings":["Microsoft Research, One Microsoft Way, Redmond, WA","Microsoft Research, One Microsoft Way, Redmond, WA,"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, One Microsoft Way, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft Research, One Microsoft Way, Redmond, WA,","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102772073","display_name":"Christopher Meek","orcid":"https://orcid.org/0000-0003-1696-6152"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christopher Meek","raw_affiliation_strings":["Microsoft Research, One Microsoft Way, Redmond, WA","Microsoft Research, One Microsoft Way, Redmond, WA,"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, One Microsoft Way, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]},{"raw_affiliation_string":"Microsoft Research, One Microsoft Way, Redmond, WA,","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066873932"],"corresponding_institution_ids":["https://openalex.org/I1290206253"],"apc_list":null,"apc_paid":null,"fwci":2.9329,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.91412344,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9952999949455261,"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"}},"topics":[{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9952999949455261,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9932000041007996,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9890999794006348,"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/phrase","display_name":"Phrase","score":0.8656447529792786},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.8410123586654663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7155424356460571},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6826766133308411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6068839430809021},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.583245038986206},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.46431729197502136},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4493749439716339},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.42329341173171997},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39344966411590576},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19573310017585754}],"concepts":[{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.8656447529792786},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.8410123586654663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7155424356460571},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6826766133308411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6068839430809021},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.583245038986206},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.46431729197502136},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4493749439716339},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.42329341173171997},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39344966411590576},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19573310017585754},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1517472.1517477","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1517472.1517477","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.186.8856","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.186.8856","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/pubs/73711/YihMeek%20-%20AdKDD-08.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W16630746","https://openalex.org/W164706946","https://openalex.org/W391985582","https://openalex.org/W637887103","https://openalex.org/W1506501075","https://openalex.org/W1541704740","https://openalex.org/W1556025486","https://openalex.org/W1560724230","https://openalex.org/W1573190978","https://openalex.org/W1598180361","https://openalex.org/W1646006088","https://openalex.org/W1648885110","https://openalex.org/W1694994217","https://openalex.org/W1746819321","https://openalex.org/W1837569165","https://openalex.org/W1843722864","https://openalex.org/W1877304445","https://openalex.org/W1901795779","https://openalex.org/W1907578970","https://openalex.org/W1922932798","https://openalex.org/W1947893135","https://openalex.org/W1948103060","https://openalex.org/W1962539974","https://openalex.org/W1967766192","https://openalex.org/W1979459060","https://openalex.org/W1987996059","https://openalex.org/W2014415866","https://openalex.org/W2073448073","https://openalex.org/W2085030399","https://openalex.org/W2090883204","https://openalex.org/W2098824882","https://openalex.org/W2099391294","https://openalex.org/W2128833328","https://openalex.org/W2135843591","https://openalex.org/W2136542423","https://openalex.org/W2149393279","https://openalex.org/W2153252192","https://openalex.org/W2156577800","https://openalex.org/W2160555926","https://openalex.org/W2161443453","https://openalex.org/W2162668326","https://openalex.org/W2165299010","https://openalex.org/W2169178495","https://openalex.org/W2169213601","https://openalex.org/W2169749653","https://openalex.org/W2170741935","https://openalex.org/W2198259498","https://openalex.org/W2201837189","https://openalex.org/W2208586609","https://openalex.org/W2244424692","https://openalex.org/W2265199312","https://openalex.org/W2297332610","https://openalex.org/W2334018742","https://openalex.org/W2397532978","https://openalex.org/W2408763461","https://openalex.org/W2548695521","https://openalex.org/W2595697910","https://openalex.org/W2950982165","https://openalex.org/W3142625335","https://openalex.org/W4211049957","https://openalex.org/W4231856373","https://openalex.org/W4240913316","https://openalex.org/W4246858749"],"related_works":["https://openalex.org/W2039546652","https://openalex.org/W2012262991","https://openalex.org/W2373794620","https://openalex.org/W2060629350","https://openalex.org/W2357294589","https://openalex.org/W2386861027","https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W1891216533","https://openalex.org/W2349302580"],"abstract_inverted_index":{"Measuring":[0],"the":[1,30,61,80,94,109,125],"relevance":[2,31,42,72,81],"between":[3,32],"a":[4,7,33,36,55,70,97,115,133],"document":[5,34,49,62],"and":[6,15,35,47,63,87,128],"phrase":[8,37,64],"is":[9,54,112,121],"fundamental":[10],"to":[11,39,68,92],"many":[12],"information":[13],"retrieval":[14],"matching":[16],"tasks":[17],"including":[18],"on-line":[19],"advertising.":[20],"In":[21],"this":[22],"paper,":[23],"we":[24],"explore":[25],"two":[26,105],"approaches":[27,106],"for":[28,44],"measuring":[29],"aiming":[38],"provide":[40],"consistent":[41],"scores":[43],"both":[45,60,102],"in":[46],"out-of":[48],"phrases.":[50],"The":[51,74],"first":[52],"approach":[53,76,127],"similarity-based":[56,126],"method":[57,136],"which":[58,120],"represents":[59],"as":[65,78],"term":[66],"vectors":[67],"derive":[69],"real-valued":[71],"score.":[73],"second":[75],"takes":[77],"input":[79],"estimates":[82],"of":[83,96,103],"some":[84],"in-document":[85],"phrases":[86],"uses":[88],"Gaussian":[89,116],"Process":[90,117],"Regression":[91,118],"predict":[93],"score":[95],"target":[98],"out-of-document":[99],"phrase.":[100],"While":[101],"these":[104],"work":[107],"well,":[108],"best":[110],"result":[111],"given":[113],"by":[114],"model,":[119],"significantly":[122],"better":[123,131],"than":[124,132],"10":[129],"%":[130],"baseline":[134],"similarity":[135],"using":[137],"bag-of-word":[138],"vectors.":[139]},"counts_by_year":[],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
