{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/101370"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/101370","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Design and implementation of the search engine module in colds","abstract":"This thesis describes the design and implementation of the search engine module in a novel Cloud-based Open Lab for Data Science (COLDS) system. COLDS is a general infrastructure system to support data science programming assignments on the cloud that is currently being developed at the University of Illinois at Urbana-Champaign in collaboration with Microsoft and Intel with Azure grant support from Microsoft and a gift fund support from Intel. The annotation subsystem of COLDS is responsible for helping instructors design flexible annotation tasks and straightforward annotation of data sets using search engine results. The function of the search engine module in the annotation subsystem of COLDS includes allowing instructors to upload customized data sets, building inverted index for data sets to support fast query and selecting ranking functions with customized parameters to perform query and get a ranked list of results. The thesis describes the design and implementation of the search engine module, including specifically its data set uploading and configuration procedure, indexing of data set, storage of the data set and index, and ranking and querying with selected method, parameters and data set. This thesis also describes the background, related work, challenges and future work of COLDS and its annotation subsystem.","abstract_html":"This thesis describes the design and implementation of the search engine module in a novel Cloud-based Open Lab for Data Science (COLDS) system. COLDS is a general infrastructure system to support data science programming assignments on the cloud that is currently being developed at the University of Illinois at Urbana-Champaign in collaboration with Microsoft and Intel with Azure grant support from Microsoft and a gift fund support from Intel. The annotation subsystem of COLDS is responsible for helping instructors design flexible annotation tasks and straightforward annotation of data sets using search engine results. The function of the search engine module in the annotation subsystem of COLDS includes allowing instructors to upload customized data sets, building inverted index for data sets to support fast query and selecting ranking functions with customized parameters to perform query and get a ranked list of results. The thesis describes the design and implementation of the search engine module, including specifically its data set uploading and configuration procedure, indexing of data set, storage of the data set and index, and ranking and querying with selected method, parameters and data set. This thesis also describes the background, related work, challenges and future work of COLDS and its annotation subsystem.","abstract_has_math":false,"creators":["Yu, Xiaofo"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Zhai, ChengXiang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-09-04T20:47:29Z","date_published":"2018-09-04T20:47:29Z","updated_at":"2026-07-22T22:24:40Z","subjects":["Information Retrieval","Crowdsourcing","Online Education"],"languages":["en"],"rights":["Copyright 2018 Xiaofo Yu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/101370","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhai, ChengXiang"]},{"key":"dc:creator","label":"Author","values":["Yu, Xiaofo"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-09-04T20:47:29Z","2020-09-05T09:15:26Z","2018-04-23","2018-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Information Retrieval","Crowdsourcing","Online Education"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2018 Xiaofo Yu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/101370"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis describes the design and implementation of the search engine module in a novel Cloud-based Open Lab for Data Science (COLDS) system. 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The thesis describes the design and implementation of the search engine module, including specifically its data set uploading and configuration procedure, indexing of data set, storage of the data set and index, and ranking and querying with selected method, parameters and data set. This thesis also describes the background, related work, challenges and future work of COLDS and its annotation subsystem.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Xiaofo Yu, accepted the attached license on 2018-04-23 at 15:50.","The student, Xiaofo Yu, submitted this Thesis for approval on 2018-04-23 at 15:55.","This Thesis was approved for publication on 2018-04-23 at 16:38.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12430 on 2018-08-31 at 17:30:20","Made available in DSpace on 2018-09-04T20:47:29Z (GMT). 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COLDS is a general infrastructure system to support data science programming assignments on the cloud that is currently being developed at the University of Illinois at Urbana-Champaign in collaboration with Microsoft and Intel with Azure grant support from Microsoft and a gift fund support from Intel. The annotation subsystem of COLDS is responsible for helping instructors design flexible annotation tasks and straightforward annotation of data sets using search engine results. The function of the search engine module in the annotation subsystem of COLDS includes allowing instructors to upload customized data sets, building inverted index for data sets to support fast query and selecting ranking functions with customized parameters to perform query and get a ranked list of results. The thesis describes the design and implementation of the search engine module, including specifically its data set uploading and configuration procedure, indexing of data set, storage of the data set and index, and ranking and querying with selected method, parameters and data set. This thesis also describes the background, related work, challenges and future work of COLDS and its annotation subsystem.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2020-05-01","The student, Xiaofo Yu, accepted the attached license on 2018-04-23 at 15:50.","The student, Xiaofo Yu, submitted this Thesis for approval on 2018-04-23 at 15:55.","This Thesis was approved for publication on 2018-04-23 at 16:38.","DSpace SAF Submission Ingestion Package generated from Vireo submission #12430 on 2018-08-31 at 17:30:20","Made available in DSpace on 2018-09-04T20:47:29Z (GMT). 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