{"id":"https://openalex.org/W2250956838","doi":"https://doi.org/10.18653/v1/w15-4407","title":"Bilingual Keyword Extraction and its Educational Application","display_name":"Bilingual Keyword Extraction and its Educational Application","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2250956838","doi":"https://doi.org/10.18653/v1/w15-4407","mag":"2250956838"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w15-4407","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w15-4407","pdf_url":"https://www.aclweb.org/anthology/W15-4407.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W15-4407.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102837741","display_name":"Chung\u2010Chi Huang","orcid":"https://orcid.org/0009-0008-9246-9004"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chung-Chi Huang","raw_affiliation_strings":["LTI, CMU 5000 Forbes Ave. Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"LTI, CMU 5000 Forbes Ave. Pittsburgh, PA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101598024","display_name":"Mei-Hua Chen","orcid":"https://orcid.org/0000-0003-3990-0404"},"institutions":[{"id":"https://openalex.org/I169090423","display_name":"Tunghai University","ror":"https://ror.org/00zhvdn11","country_code":"TW","type":"education","lineage":["https://openalex.org/I169090423"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Mei-Hua Chen","raw_affiliation_strings":["FLL Tunghai University Taichung, Taiwan"],"affiliations":[{"raw_affiliation_string":"FLL Tunghai University Taichung, Taiwan","institution_ids":["https://openalex.org/I169090423"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111458344","display_name":"Ping-Che Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I3141939062","display_name":"Institute for Information Industry","ror":"https://ror.org/01d8kr740","country_code":"TW","type":"nonprofit","lineage":["https://openalex.org/I3141939062"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ping-Che Yang","raw_affiliation_strings":["Institute for Information Industry Taipei, Taiwan"],"affiliations":[{"raw_affiliation_string":"Institute for Information Industry Taipei, Taiwan","institution_ids":["https://openalex.org/I3141939062"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101598024"],"corresponding_institution_ids":["https://openalex.org/I169090423"],"apc_list":null,"apc_paid":null,"fwci":0.4314,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.77451821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"43","last_page":"48"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9914000034332275,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9800000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8718401789665222},{"id":"https://openalex.org/keywords/pagerank","display_name":"PageRank","score":0.7526019811630249},{"id":"https://openalex.org/keywords/keyword-extraction","display_name":"Keyword extraction","score":0.7315587401390076},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6995996236801147},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6355995535850525},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6264085173606873},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.5442010760307312},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5271582007408142},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.47053155303001404},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.43706756830215454},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.39611175656318665},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1604631245136261}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8718401789665222},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.7526019811630249},{"id":"https://openalex.org/C2780288562","wikidata":"https://www.wikidata.org/wiki/Q25053353","display_name":"Keyword extraction","level":2,"score":0.7315587401390076},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6995996236801147},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6355995535850525},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6264085173606873},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.5442010760307312},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5271582007408142},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.47053155303001404},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.43706756830215454},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.39611175656318665},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1604631245136261},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w15-4407","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w15-4407","pdf_url":"https://www.aclweb.org/anthology/W15-4407.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w15-4407","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w15-4407","pdf_url":"https://www.aclweb.org/anthology/W15-4407.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.8700000047683716,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320336958","display_name":"Institute for Information Industry, Ministry of Science and Technology, Taiwan","ror":"https://ror.org/01d8kr740"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2250956838.pdf","grobid_xml":"https://content.openalex.org/works/W2250956838.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W1574901103","https://openalex.org/W1973406306","https://openalex.org/W2010484471","https://openalex.org/W2019987199","https://openalex.org/W2043004216","https://openalex.org/W2069870183","https://openalex.org/W2074356021","https://openalex.org/W2099763641","https://openalex.org/W2102775690","https://openalex.org/W2108459929","https://openalex.org/W2111538853","https://openalex.org/W2112324543","https://openalex.org/W2116229791","https://openalex.org/W2127246734","https://openalex.org/W2145766604","https://openalex.org/W2146769536","https://openalex.org/W2147707543","https://openalex.org/W2153653739","https://openalex.org/W2156985047","https://openalex.org/W2163659824","https://openalex.org/W2168286119","https://openalex.org/W2175979272","https://openalex.org/W2179764914","https://openalex.org/W2950090310","https://openalex.org/W4241645538"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W2154222238","https://openalex.org/W4312814274","https://openalex.org/W2026353382","https://openalex.org/W2357647850","https://openalex.org/W2010484471","https://openalex.org/W1579690747","https://openalex.org/W1588516692"],"abstract_inverted_index":{"We":[0,55],"introduce":[1],"a":[2,8],"method":[3,17,58],"that":[4,67],"extracts":[5],"keywords":[6,23,80],"in":[7,81],"language":[9,63,75],"with":[10,48],"the":[11,14],"help":[12],"of":[13],"other.":[15],"The":[16],"involves":[18],"estimating":[19],"preferences":[20],"for":[21,41,52],"topical":[22],"and":[24,45,62,74],"fusing":[25],"language-specific":[26],"word":[27,36,42,49],"statistics.":[28],"At":[29],"run-time,":[30],"we":[31],"transform":[32],"parallel":[33],"articles":[34],"into":[35],"graphs,":[37],"build":[38],"crosslingual":[39],"edges":[40],"statistics":[43],"integration,":[44],"exploit":[46],"PageRank":[47],"keyness":[50],"information":[51,73],"keyword":[53,60,68],"extraction.":[54],"apply":[56],"our":[57,79],"to":[59],"analysis":[61],"learning.":[64],"Evaluation":[65],"shows":[66],"extraction":[69],"benefits":[70],"from":[71,78],"cross-language":[72],"learners":[76],"benefit":[77],"reading":[82],"comprehension":[83],"test.":[84]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}