{"id":{"repo_id":"byu","oai_identifier":"oai:scholarsarchive.byu.edu:etd-1098"},"canonical_url":"https://search.dev.ndltd.org/etd/byu/oai:scholarsarchive.byu.edu:etd-1098","repository":{"repo_id":"byu","name":"Brigham Young University","base_url":"https://scholarsarchive.byu.edu/do/oai/"},"display":{"title":"Schema Matching and Data Extraction over HTML Tables","abstract":"Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem for the case of mostly structured data in the form of HTML tables, based on document-independent extraction ontologies. The solution entails elements of table location and table understanding, data integration, and wrapper creation. Table location and understanding allows us to locate the table of interest, recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus \"directly\" query source data with unknown structure through a known target schema.","abstract_html":"Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem for the case of mostly structured data in the form of HTML tables, based on document-independent extraction ontologies. The solution entails elements of table location and table understanding, data integration, and wrapper creation. Table location and understanding allows us to locate the table of interest, recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus "directly" query source data with unknown structure through a known target schema.","abstract_has_math":false,"creators":["Tao, Cui"],"institution":"Brigham Young University - Provo","degree_name":"MS","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:27:25Z","subjects":["HTML table","ontology","data extraction","schema matching","document-independent extraction","data-integration techniques","Computer Sciences"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsarchive.byu.edu/etd/99","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Tao, Cui"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2003-09-16T07:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["Brigham Young University - Provo"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["HTML table","ontology","data extraction","schema matching","document-independent extraction","data-integration techniques","Computer Sciences"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsarchive.byu.edu/etd/99","https://scholarsarchive.byu.edu/context/etd/article/1098/viewcontent/ETD_CISOPTR_65.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Physical and Mathematical Sciences; Computer Science"]},{"key":"dc:description.abstract","label":"Abstract","values":["Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem for the case of mostly structured data in the form of HTML tables, based on document-independent extraction ontologies. The solution entails elements of table location and table understanding, data integration, and wrapper creation. Table location and understanding allows us to locate the table of interest, recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus \"directly\" query source data with unknown structure through a known target schema."]},{"key":"dc:format","label":"Dc Format","values":["application:pdf"]},{"key":"dc:source","label":"Dc Source","values":["Brigham Young University - Provo"]},{"key":"dc:title","label":"Title","values":["Schema Matching and Data Extraction over HTML Tables"]}]}],"canonical_facts":{"dc:creator":["Tao, Cui"],"dc:date":["2003-09-16T07:00:00Z"],"dc:description":["Physical and Mathematical Sciences; Computer Science"],"dc:description.abstract":["Data on the Web in HTML tables is mostly structured, but we usually do not know the structure in advance. Thus, we cannot directly query for data of interest. We propose a solution to this problem for the case of mostly structured data in the form of HTML tables, based on document-independent extraction ontologies. The solution entails elements of table location and table understanding, data integration, and wrapper creation. Table location and understanding allows us to locate the table of interest, recognize attributes and values, pair attributes with values, and form records. Data-integration techniques allow us to match source records with a target schema. Ontologically specified wrappers allow us to extract data from source records into a target schema. Experimental results show that we can successfully map data of interest from source HTML tables with unknown structure to a given target database schema. We can thus \"directly\" query source data with unknown structure through a known target schema."],"dc:format":["application:pdf"],"dc:identifier":["https://scholarsarchive.byu.edu/etd/99","https://scholarsarchive.byu.edu/context/etd/article/1098/viewcontent/ETD_CISOPTR_65.pdf"],"dc:language":["English"],"dc:publisher":["Brigham Young University - Provo"],"dc:source":["Brigham Young University - Provo"],"dc:subject":["HTML table","ontology","data extraction","schema matching","document-independent extraction","data-integration techniques","Computer Sciences"],"dc:title":["Schema Matching and Data Extraction over HTML Tables"],"dc:type":["Thesis"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T01:27:25Z"}