{"id":"https://openalex.org/W4392447035","doi":"https://doi.org/10.1145/3639233.3639346","title":"Enhancing a User Matchmaking Algorithm using Personalized PageRank","display_name":"Enhancing a User Matchmaking Algorithm using Personalized PageRank","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4392447035","doi":"https://doi.org/10.1145/3639233.3639346"},"language":"en","primary_location":{"id":"doi:10.1145/3639233.3639346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639346","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 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639346","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008213060","display_name":"Santipong Thaiprayoon","orcid":"https://orcid.org/0000-0003-3021-474X"},"institutions":[{"id":"https://openalex.org/I120691247","display_name":"FernUniversit\u00e4t in Hagen","ror":"https://ror.org/04tkkr536","country_code":"DE","type":"education","lineage":["https://openalex.org/I120691247"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Santipong Thaiprayoon","raw_affiliation_strings":["Chair of Communication Networks, FernUniversitat in Hagen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Communication Networks, FernUniversitat in Hagen, Germany","institution_ids":["https://openalex.org/I120691247"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003105685","display_name":"Herwig Unger","orcid":"https://orcid.org/0000-0002-8818-3600"},"institutions":[{"id":"https://openalex.org/I120691247","display_name":"FernUniversit\u00e4t in Hagen","ror":"https://ror.org/04tkkr536","country_code":"DE","type":"education","lineage":["https://openalex.org/I120691247"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Herwig Unger","raw_affiliation_strings":["Chair of Communication Networks, FernUniversitat in Hagen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Communication Networks, FernUniversitat in Hagen, Germany","institution_ids":["https://openalex.org/I120691247"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008213060"],"corresponding_institution_ids":["https://openalex.org/I120691247"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.36650652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"319","last_page":"327"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.9950000047683716,"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8515479564666748},{"id":"https://openalex.org/keywords/pagerank","display_name":"PageRank","score":0.7065743207931519},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.5951842069625854},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5604755878448486},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4847092628479004},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.4780595600605011},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4684125781059265},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4385111629962921},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4237779676914215},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.41951999068260193},{"id":"https://openalex.org/keywords/personalized-search","display_name":"Personalized search","score":0.41757622361183167},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38009944558143616},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36835089325904846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21895498037338257},{"id":"https://openalex.org/keywords/search-engine","display_name":"Search engine","score":0.17027395963668823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8515479564666748},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.7065743207931519},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.5951842069625854},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5604755878448486},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4847092628479004},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.4780595600605011},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4684125781059265},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4385111629962921},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4237779676914215},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.41951999068260193},{"id":"https://openalex.org/C2776945383","wikidata":"https://www.wikidata.org/wiki/Q7170667","display_name":"Personalized search","level":3,"score":0.41757622361183167},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38009944558143616},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36835089325904846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21895498037338257},{"id":"https://openalex.org/C97854310","wikidata":"https://www.wikidata.org/wiki/Q19541","display_name":"Search engine","level":2,"score":0.17027395963668823},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3639233.3639346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639346","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 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3639233.3639346","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3639233.3639346","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3639233.3639346","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 2023 7th International Conference on Natural Language Processing and Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392447035.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W866925903","https://openalex.org/W2117878949","https://openalex.org/W2286310738","https://openalex.org/W2754493004","https://openalex.org/W2887360225","https://openalex.org/W2908054697","https://openalex.org/W2911407631","https://openalex.org/W2933316466","https://openalex.org/W3010338999","https://openalex.org/W3011596381","https://openalex.org/W3014234739","https://openalex.org/W3035063214","https://openalex.org/W3098417430","https://openalex.org/W3110690473","https://openalex.org/W3141794196","https://openalex.org/W4301112302","https://openalex.org/W4380787770","https://openalex.org/W4385414053","https://openalex.org/W4402793838","https://openalex.org/W7038341846"],"related_works":["https://openalex.org/W1555177483","https://openalex.org/W4286432911","https://openalex.org/W2137682642","https://openalex.org/W1866209616","https://openalex.org/W4240778985","https://openalex.org/W2760343045","https://openalex.org/W4205700582","https://openalex.org/W2067314954","https://openalex.org/W2109819452","https://openalex.org/W1550457191"],"abstract_inverted_index":{"With":[0],"the":[1,93,106,121,132],"increasing":[2],"number":[3],"of":[4,52,131],"users":[5,19],"in":[6,129],"online":[7],"communities":[8],"and":[9,22,66,81,89,101,135],"social":[10],"networking":[11],"platforms,":[12],"it":[13],"is":[14,55,76],"becoming":[15],"more":[16,109],"difficult":[17],"for":[18,61],"to":[20,43,47],"meet":[21],"connect":[23],"with":[24],"individuals":[25],"who":[26],"share":[27],"similar":[28],"opinions":[29],"or":[30],"interests.":[31],"The":[32,69],"paper":[33],"proposes":[34],"a":[35,58,114],"user":[36,53,74,103,116],"matchmaking":[37,107],"algorithm":[38,95,123],"based":[39],"on":[40,113],"personalized":[41,90],"PageRank":[42],"provide":[44],"potential":[45],"friends":[46],"individual":[48],"users.":[49,68],"A":[50],"set":[51],"profiles":[54,75],"transformed":[56],"into":[57],"graph":[59,91],"model":[60],"efficiently":[62],"discovering":[63],"meaningful":[64],"connections":[65],"influential":[67],"semantic":[70,99],"relationship":[71],"between":[72],"two":[73],"then":[77],"estimated":[78],"using":[79],"word":[80],"sentence":[82],"embeddings.":[83],"By":[84],"incorporating":[85],"both":[86],"embedding":[87],"models":[88],"analytics,":[92],"proposed":[94,122],"can":[96],"capture":[97],"complex":[98],"information":[100],"high-order":[102],"relationships,":[104],"making":[105],"process":[108],"accurate.":[110],"Experiments":[111],"conducted":[112],"simulated":[115],"profile":[117],"dataset":[118],"show":[119],"that":[120],"consistently":[124],"outperforms":[125],"existing":[126],"state-of-the-art":[127],"methods":[128],"terms":[130],"F1":[133],"score":[134],"mean":[136],"average":[137],"precision":[138],"metrics.":[139]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
