{"id":"https://openalex.org/W2089840379","doi":"https://doi.org/10.1145/1007568.1007710","title":"A TeXQuery-based XML full-text search engine","display_name":"A TeXQuery-based XML full-text search engine","publication_year":2004,"publication_date":"2004-06-13","ids":{"openalex":"https://openalex.org/W2089840379","doi":"https://doi.org/10.1145/1007568.1007710","mag":"2089840379"},"language":"en","primary_location":{"id":"doi:10.1145/1007568.1007710","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1007568.1007710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2004 ACM SIGMOD international conference on Management of data","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/A5077339008","display_name":"Chavdar Botev","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chavdar Botev","raw_affiliation_strings":["Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081664259","display_name":"Sihem Amer-Yahia","orcid":"https://orcid.org/0000-0002-6194-4502"},"institutions":[{"id":"https://openalex.org/I1283103587","display_name":"AT&T (United States)","ror":"https://ror.org/02bbd5539","country_code":"US","type":"company","lineage":["https://openalex.org/I1283103587"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sihem Amer-Yahia","raw_affiliation_strings":["AT&T Labs-Research"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AT&T Labs-Research","institution_ids":["https://openalex.org/I1283103587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075946653","display_name":"Jayavel Shanmugasundaram","orcid":"https://orcid.org/0009-0000-3176-1556"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayavel Shanmugasundaram","raw_affiliation_strings":["Cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.7467,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.87548904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"943","last_page":"944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10317","display_name":"Advanced Database Systems and Queries","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9955000281333923,"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/T11106","display_name":"Data Management and Algorithms","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/xquery","display_name":"XQuery","score":0.9582617878913879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8705494403839111},{"id":"https://openalex.org/keywords/xpath","display_name":"XPath","score":0.7652223110198975},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6482245922088623},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.6175943613052368},{"id":"https://openalex.org/keywords/xml","display_name":"XML","score":0.6057077050209045},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.48055556416511536},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.45851895213127136},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.453438401222229},{"id":"https://openalex.org/keywords/xml-database","display_name":"XML database","score":0.43911588191986084},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.4220418930053711},{"id":"https://openalex.org/keywords/query-language","display_name":"Query language","score":0.4108578562736511},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.234978586435318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23197847604751587}],"concepts":[{"id":"https://openalex.org/C2780512708","wikidata":"https://www.wikidata.org/wiki/Q850661","display_name":"XQuery","level":4,"score":0.9582617878913879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8705494403839111},{"id":"https://openalex.org/C2780213375","wikidata":"https://www.wikidata.org/wiki/Q16340","display_name":"XPath","level":4,"score":0.7652223110198975},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6482245922088623},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.6175943613052368},{"id":"https://openalex.org/C8797682","wikidata":"https://www.wikidata.org/wiki/Q2115","display_name":"XML","level":2,"score":0.6057077050209045},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.48055556416511536},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.45851895213127136},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.453438401222229},{"id":"https://openalex.org/C183068750","wikidata":"https://www.wikidata.org/wiki/Q357393","display_name":"XML database","level":3,"score":0.43911588191986084},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.4220418930053711},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.4108578562736511},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.234978586435318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23197847604751587}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1007568.1007710","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1007568.1007710","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2004 ACM SIGMOD international conference on Management of data","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.546.4792","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.546.4792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.uiuc.edu/class/fa05/cs591han/sigmodpods04/sigmod/pdf/D-140.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2125630417"],"related_works":["https://openalex.org/W106453523","https://openalex.org/W4256405642","https://openalex.org/W4231075805","https://openalex.org/W2020042858","https://openalex.org/W4233448385","https://openalex.org/W158654455","https://openalex.org/W2169421069","https://openalex.org/W169802313","https://openalex.org/W4205604934","https://openalex.org/W2154079961"],"abstract_inverted_index":{"We":[0],"demonstrate":[1],"an":[2],"XML":[3],"full-text":[4,16,29,54,74,86],"search":[5,17],"engine":[6],"that":[7,21,68],"implements":[8],"the":[9,82,85],"TeXQuery":[10,12,40,61,80],"language.":[11],"is":[13,81],"a":[14,23,64],"powerful":[15],"extension":[18,88],"to":[19,43,89],"XQuery":[20,57,93],"provides":[22],"rich":[24],"set":[25],"of":[26,84],"fully":[27],"composable":[28],"primitives,":[30],"such":[31],"as":[32],"phrase":[33],"matching,":[34],"proximity":[35],"distance,":[36],"stemming":[37],"and":[38,50,58,76,92],"thesauri.":[39],"enables":[41],"users":[42],"seamlessly":[44],"query":[45,70],"over":[46],"both":[47],"structure":[48],"data":[49],"text,":[51],"by":[52,98],"embedding":[53],"primitives":[55],"in":[56],"vice":[59],"versa.":[60],"also":[62],"supports":[63],"flexible":[65],"scoring":[66],"construct":[67],"scores":[69],"results":[71],"based":[72],"on":[73],"predicates":[75],"permits":[77],"top-k":[78],"queries.":[79],"precursor":[83],"language":[87],"XPath":[90],"2.0":[91],"1.0":[94],"currently":[95],"being":[96],"developed":[97],"W3C.":[99]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}