{"id":"https://openalex.org/W2769050050","doi":"https://doi.org/10.1109/indin.2017.8104916","title":"Incorporating word embeddings in the hierarchical dirichlet process for query-oriented text summarization","display_name":"Incorporating word embeddings in the hierarchical dirichlet process for query-oriented text summarization","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2769050050","doi":"https://doi.org/10.1109/indin.2017.8104916","mag":"2769050050"},"language":"en","primary_location":{"id":"doi:10.1109/indin.2017.8104916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2017.8104916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","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/A5090407851","display_name":"Hadrien Van Lierde","orcid":"https://orcid.org/0000-0002-3633-5764"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Hadrien Van Lierde","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050716572","display_name":"Tommy W. S. Chow","orcid":"https://orcid.org/0000-0001-7051-0434"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Tommy W. S. Chow","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6196,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.78094654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"1050","issue":null,"first_page":"1037","last_page":"1042"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9997000098228455,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9889000058174133,"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/automatic-summarization","display_name":"Automatic summarization","score":0.8867018222808838},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8802264928817749},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6909335255622864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6225113272666931},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5997132062911987},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5889198184013367},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.576111376285553},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.5524743795394897},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5422424077987671},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5346208214759827},{"id":"https://openalex.org/keywords/hierarchical-dirichlet-process","display_name":"Hierarchical Dirichlet process","score":0.5326820015907288},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.531791627407074},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.3946508467197418},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.07244247198104858}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8867018222808838},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8802264928817749},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6909335255622864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6225113272666931},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5997132062911987},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5889198184013367},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.576111376285553},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.5524743795394897},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5422424077987671},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5346208214759827},{"id":"https://openalex.org/C141318989","wikidata":"https://www.wikidata.org/wiki/Q5753066","display_name":"Hierarchical Dirichlet process","level":4,"score":0.5326820015907288},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.531791627407074},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.3946508467197418},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.07244247198104858},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin.2017.8104916","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin.2017.8104916","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE 15th International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1480633635","https://openalex.org/W1573514622","https://openalex.org/W2100163972","https://openalex.org/W2102160377","https://openalex.org/W2110693578","https://openalex.org/W2144245630","https://openalex.org/W2147406357","https://openalex.org/W2151343603","https://openalex.org/W2153579005","https://openalex.org/W2154652894","https://openalex.org/W2250753706","https://openalex.org/W2276623712","https://openalex.org/W3087975536","https://openalex.org/W3101913037","https://openalex.org/W4294170691","https://openalex.org/W6628595286","https://openalex.org/W6634065907","https://openalex.org/W6674922813","https://openalex.org/W6675495717","https://openalex.org/W6682631176","https://openalex.org/W6682691769"],"related_works":["https://openalex.org/W2914864478","https://openalex.org/W2097627380","https://openalex.org/W2008338582","https://openalex.org/W4291700620","https://openalex.org/W1999586157","https://openalex.org/W22044811","https://openalex.org/W2625329765","https://openalex.org/W2810994508","https://openalex.org/W2255612897","https://openalex.org/W2766840109"],"abstract_inverted_index":{"The":[0,95],"ever-growing":[1],"amount":[2],"of":[3,32],"textual":[4],"data":[5],"available":[6],"online":[7],"creates":[8],"the":[9,48,70,85,106],"need":[10],"for":[11,87,92],"automatic":[12],"text":[13],"summarization":[14,34],"tools.":[15],"Probabilistic":[16],"topic":[17,72],"models":[18],"are":[19],"able":[20],"to":[21,46,76,113],"infer":[22],"semantic":[23,50,78],"relationships":[24,51],"between":[25,52,80],"sentences":[26,104],"which":[27,64],"is":[28,97,111],"a":[29,61,88,118],"key":[30],"step":[31],"extractive":[33],"methods.":[35],"However,":[36],"they":[37],"strongly":[38],"rely":[39],"on":[40,117],"word":[41,67],"co-occurrence":[42],"patterns":[43],"and":[44],"fail":[45],"capture":[47,77],"actual":[49],"words":[53],"such":[54],"as":[55],"synonymy,":[56],"antonymy,":[57],"etc.":[58],"We":[59],"propose":[60],"novel":[62],"algorithm":[63,91],"incorporates":[65],"pre-trained":[66],"embeddings":[68],"in":[69,74],"probabilistic":[71],"model":[73],"order":[75],"similarities":[79,83],"sentences.":[81],"These":[82],"provide":[84],"basis":[86],"sentence":[89],"ranking":[90],"query-oriented":[93],"summarization.":[94],"summary":[96],"then":[98],"produced":[99],"by":[100],"extracting":[101],"highly":[102],"ranked":[103],"from":[105],"original":[107],"corpus.":[108],"Our":[109],"method":[110],"shown":[112],"outperform":[114],"state-of-the-art":[115],"algorithms":[116],"benchmark":[119],"dataset.":[120]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}