{"id":"https://openalex.org/W2913608552","doi":"https://doi.org/10.1109/bigdata.2018.8622526","title":"Identifying Pros and Cons of Product Aspects Based on Customer Reviews","display_name":"Identifying Pros and Cons of Product Aspects Based on Customer Reviews","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2913608552","doi":"https://doi.org/10.1109/bigdata.2018.8622526","mag":"2913608552"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big 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/A5051906335","display_name":"Ebad Ahmadzadeh","orcid":null},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ebad Ahmadzadeh","raw_affiliation_strings":["Dept. of Computer Sciences, Florida Institute of Technology, Melbourne, Florida, 32901"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Sciences, Florida Institute of Technology, Melbourne, Florida, 32901","institution_ids":["https://openalex.org/I106959904"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072267835","display_name":"Philip K. Chan","orcid":"https://orcid.org/0000-0002-3878-4205"},"institutions":[{"id":"https://openalex.org/I106959904","display_name":"Florida Institute of Technology","ror":"https://ror.org/04atsbb87","country_code":"US","type":"education","lineage":["https://openalex.org/I106959904"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip K. Chan","raw_affiliation_strings":["Dept. of Computer Sciences, Florida Institute of Technology, Melbourne, Florida, 32901"],"affiliations":[{"raw_affiliation_string":"Dept. of Computer Sciences, Florida Institute of Technology, Melbourne, Florida, 32901","institution_ids":["https://openalex.org/I106959904"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051906335"],"corresponding_institution_ids":["https://openalex.org/I106959904"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1775733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"3","issue":null,"first_page":"931","last_page":"936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cons","display_name":"cons","score":0.9093099236488342},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7247178554534912},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.6975254416465759},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6314513683319092},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.47283607721328735},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.47001221776008606},{"id":"https://openalex.org/keywords/new-product-development","display_name":"New product development","score":0.4373292326927185},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.40014466643333435},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15364351868629456},{"id":"https://openalex.org/keywords/systems-engineering","display_name":"Systems engineering","score":0.1402571201324463},{"id":"https://openalex.org/keywords/marketing","display_name":"Marketing","score":0.10518646240234375},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08370822668075562},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06852632761001587},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.067808598279953}],"concepts":[{"id":"https://openalex.org/C37091826","wikidata":"https://www.wikidata.org/wiki/Q3687178","display_name":"cons","level":2,"score":0.9093099236488342},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7247178554534912},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.6975254416465759},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6314513683319092},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.47283607721328735},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.47001221776008606},{"id":"https://openalex.org/C19351080","wikidata":"https://www.wikidata.org/wiki/Q1395034","display_name":"New product development","level":2,"score":0.4373292326927185},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.40014466643333435},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15364351868629456},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.1402571201324463},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.10518646240234375},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08370822668075562},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06852632761001587},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.067808598279953},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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:10.1109/bigdata.2018.8622526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622526","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W147952312","https://openalex.org/W1517771839","https://openalex.org/W1581485226","https://openalex.org/W1880262756","https://openalex.org/W2088622183","https://openalex.org/W2099813784","https://openalex.org/W2141631351","https://openalex.org/W2145071407","https://openalex.org/W2146894761","https://openalex.org/W2148506018","https://openalex.org/W2150098611","https://openalex.org/W2160714905","https://openalex.org/W2161058795","https://openalex.org/W2166706824","https://openalex.org/W2243869100","https://openalex.org/W2250539671","https://openalex.org/W2251939518","https://openalex.org/W2404032054","https://openalex.org/W2783442281","https://openalex.org/W2963662719","https://openalex.org/W3146306708","https://openalex.org/W6634901647","https://openalex.org/W6639619044","https://openalex.org/W6683812798"],"related_works":["https://openalex.org/W4241391178","https://openalex.org/W4281781887","https://openalex.org/W769482574","https://openalex.org/W1551026882","https://openalex.org/W3178425452","https://openalex.org/W2992833102","https://openalex.org/W4230644486","https://openalex.org/W2482050438","https://openalex.org/W2091920932","https://openalex.org/W2799298689"],"abstract_inverted_index":{"The":[0],"task":[1],"of":[2,40,43,53,131],"identifying":[3],"pros":[4,24,69,132],"and":[5,25,38,70,75,94,133],"cons":[6,26,71,134],"from":[7],"product":[8,30,45,54,60],"reviews":[9],"has":[10],"applications":[11],"in":[12],"decision":[13],"support":[14],"for":[15,29,72,79],"consumers.":[16],"It":[17],"becomes":[18],"even":[19],"more":[20,123,135],"useful":[21],"when":[22],"the":[23,44,63,99],"are":[27,89,95,104],"identified":[28],"aspects":[31],"so":[32],"consumers":[33],"can":[34,121],"quickly":[35],"see":[36],"strengths":[37],"weaknesses":[39],"each":[41,73,80,139],"aspect":[42,100],"without":[46],"reading":[47],"all":[48],"reviews.":[49],"Given":[50],"a":[51,77,129],"collection":[52],"reviews,":[55],"we":[56],"automatically":[57],"extract":[58],"relevant":[59],"aspects,":[61,126],"find":[62],"most":[64],"significant":[65],"sentences":[66,87],"that":[67,88,113],"represent":[68,92],"aspect,":[74],"provide":[76],"summary":[78],"aspect.":[81,140],"We":[82],"introduce":[83],"SS2":[84],"to":[85,91,98,101,115,138],"select":[86],"likely":[90],"pros/cons":[93],"semantically":[96],"related":[97,137],"which":[102],"they":[103],"associated.":[105],"Our":[106],"results":[107],"on":[108],"three":[109],"data":[110],"sets":[111],"indicate":[112],"compared":[114],"an":[116],"existing":[117],"algorithm,":[118],"our":[119],"algorithm":[120],"generate":[122],"meaningful":[124],"summarized":[125],"along":[127],"with":[128],"list":[130],"closely":[136]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}