{"id":"https://openalex.org/W2739992143","doi":"https://doi.org/10.1145/3077136.3080822","title":"Neural Rating Regression with Abstractive Tips Generation for Recommendation","display_name":"Neural Rating Regression with Abstractive Tips Generation for Recommendation","publication_year":2017,"publication_date":"2017-07-28","ids":{"openalex":"https://openalex.org/W2739992143","doi":"https://doi.org/10.1145/3077136.3080822","mag":"2739992143"},"language":"en","primary_location":{"id":"doi:10.1145/3077136.3080822","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1708.00154","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061435467","display_name":"Piji Li","orcid":"https://orcid.org/0000-0003-1474-3692"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Piji Li","raw_affiliation_strings":["Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100413085","display_name":"Zihao Wang","orcid":"https://orcid.org/0000-0002-3919-0396"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zihao Wang","raw_affiliation_strings":["Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100384130","display_name":"Zhaochun Ren","orcid":"https://orcid.org/0000-0002-9076-6565"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaochun Ren","raw_affiliation_strings":["Data Science Lab, JD.com, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Data Science Lab, JD.com, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086674741","display_name":"Lidong Bing","orcid":"https://orcid.org/0000-0003-4565-6313"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lidong Bing","raw_affiliation_strings":["AI Lab, Tencent Inc., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, Tencent Inc., Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018582154","display_name":"Wai Lam","orcid":"https://orcid.org/0000-0001-5479-377X"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wai Lam","raw_affiliation_strings":["Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":305,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"345","last_page":"354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9771000146865845,"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":0.832158625125885},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7201347947120667},{"id":"https://openalex.org/keywords/feeling","display_name":"Feeling","score":0.6455370187759399},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5775228142738342},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5745770931243896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5463387370109558},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.541972815990448},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.46801790595054626},{"id":"https://openalex.org/keywords/product","display_name":"Product (mathematics)","score":0.46662676334381104},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4635877311229706},{"id":"https://openalex.org/keywords/user-experience-design","display_name":"User experience design","score":0.4452027976512909},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.40184253454208374},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3348296582698822},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09665378928184509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.832158625125885},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7201347947120667},{"id":"https://openalex.org/C122980154","wikidata":"https://www.wikidata.org/wiki/Q205555","display_name":"Feeling","level":2,"score":0.6455370187759399},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5775228142738342},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5745770931243896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5463387370109558},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.541972815990448},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.46801790595054626},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.46662676334381104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4635877311229706},{"id":"https://openalex.org/C201025465","wikidata":"https://www.wikidata.org/wiki/Q11248500","display_name":"User experience design","level":2,"score":0.4452027976512909},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40184253454208374},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3348296582698822},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09665378928184509},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3077136.3080822","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3077136.3080822","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1708.00154","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.00154","pdf_url":"https://arxiv.org/pdf/1708.00154","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1708.00154","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1708.00154","pdf_url":"https://arxiv.org/pdf/1708.00154","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1486317198","https://openalex.org/W1498238796","https://openalex.org/W1498436455","https://openalex.org/W1690919088","https://openalex.org/W1720514416","https://openalex.org/W1843891098","https://openalex.org/W1880262756","https://openalex.org/W1969245231","https://openalex.org/W1994156358","https://openalex.org/W1994389483","https://openalex.org/W2008353316","https://openalex.org/W2028988057","https://openalex.org/W2037351199","https://openalex.org/W2042281163","https://openalex.org/W2050096199","https://openalex.org/W2054141820","https://openalex.org/W2061873838","https://openalex.org/W2064675550","https://openalex.org/W2071111773","https://openalex.org/W2099471712","https://openalex.org/W2099866409","https://openalex.org/W2100235918","https://openalex.org/W2127426251","https://openalex.org/W2131744502","https://openalex.org/W2133564696","https://openalex.org/W2135029798","https://openalex.org/W2135790056","https://openalex.org/W2137245235","https://openalex.org/W2145094598","https://openalex.org/W2151052953","https://openalex.org/W2153579005","https://openalex.org/W2154652894","https://openalex.org/W2157331557","https://openalex.org/W2157881433","https://openalex.org/W2161611336","https://openalex.org/W2163605009","https://openalex.org/W2173089013","https://openalex.org/W2253995343","https://openalex.org/W2384495648","https://openalex.org/W2483418458","https://openalex.org/W2525778437","https://openalex.org/W2548339725","https://openalex.org/W2557283755","https://openalex.org/W2575006718","https://openalex.org/W2583674722","https://openalex.org/W2583875861","https://openalex.org/W2604777655","https://openalex.org/W2605350416","https://openalex.org/W2950133940","https://openalex.org/W2950947809","https://openalex.org/W2951707557","https://openalex.org/W2962965405","https://openalex.org/W2963241389","https://openalex.org/W2964308564","https://openalex.org/W2997574889","https://openalex.org/W3101913037","https://openalex.org/W3102701984","https://openalex.org/W3143596294","https://openalex.org/W4233045210","https://openalex.org/W4294170691","https://openalex.org/W4320013936"],"related_works":["https://openalex.org/W2291261743","https://openalex.org/W1540119434","https://openalex.org/W4229598134","https://openalex.org/W2335262298","https://openalex.org/W2378211422","https://openalex.org/W2765982327","https://openalex.org/W2071657884","https://openalex.org/W213396585","https://openalex.org/W4237671428","https://openalex.org/W2068152137"],"abstract_inverted_index":{"Recently,":[0],"some":[1,37,73],"E-commerce":[2],"sites":[3],"launch":[4],"a":[5,41,48,68,108,152],"new":[6],"interaction":[7],"box":[8],"called":[9],"Tips":[10],"on":[11,157],"their":[12,18],"mobile":[13],"apps.":[14],"Users":[15],"can":[16,116,177],"express":[17],"experience":[19,56,131,182],"and":[20,39,57,88,121,132,147,183],"feelings":[21],"or":[22,31,83],"provide":[23],"suggestions":[24],"using":[25],"short":[26],"texts":[27],"typically":[28],"several":[29],"words":[30],"one":[32],"sentence.":[33,154],"In":[34],"essence,":[35],"writing":[36],"tips":[38,101,124,136,176],"giving":[40],"numerical":[42],"rating":[43,95],"are":[44,142],"two":[45,62],"facets":[46,63],"of":[47],"user's":[49],"product":[50],"assessment":[51],"action,":[52],"expressing":[53],"the":[54,94,170,174,180],"user":[55,84,87,130,146,181],"feelings.":[58,133,184],"Jointly":[59],"modeling":[60],"these":[61],"is":[64],"helpful":[65],"for":[66,92,102],"designing":[67],"better":[69],"recommendation":[70,104],"system.":[71],"While":[72],"existing":[74,98],"models":[75],"integrate":[76],"text":[77],"information":[78],"such":[79],"as":[80],"item":[81,89,148],"specifications":[82],"reviews":[85],"into":[86,151],"latent":[90,149],"factors":[91],"improving":[93,103],"prediction,":[96],"no":[97],"works":[99],"consider":[100],"quality.":[105],"We":[106],"propose":[107],"deep":[109],"learning":[110],"based":[111],"framework":[112],"named":[113],"NRT":[114,165],"which":[115],"simultaneously":[117],"predict":[118,179],"precise":[119],"ratings":[120],"generate":[122],"abstractive":[123,135],"with":[125],"good":[126],"linguistic":[127],"quality":[128],"simulating":[129],"For":[134],"generation,":[137],"gated":[138],"recurrent":[139],"neural":[140],"networks":[141],"employed":[143],"to":[144],"\"translate''":[145],"representations":[150],"concise":[153],"Extensive":[155],"experiments":[156],"benchmark":[158],"datasets":[159],"from":[160],"different":[161],"domains":[162],"show":[163],"that":[164],"achieves":[166],"significant":[167],"improvements":[168],"over":[169],"state-of-the-art":[171],"methods.":[172],"Moreover,":[173],"generated":[175],"vividly":[178]},"counts_by_year":[{"year":2026,"cited_by_count":12},{"year":2025,"cited_by_count":29},{"year":2024,"cited_by_count":25},{"year":2023,"cited_by_count":43},{"year":2022,"cited_by_count":42},{"year":2021,"cited_by_count":41},{"year":2020,"cited_by_count":50},{"year":2019,"cited_by_count":38},{"year":2018,"cited_by_count":20},{"year":2017,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}