{"id":"https://openalex.org/W2053084120","doi":"https://doi.org/10.1109/fskd.2012.6233970","title":"Combining N-gram retrieval with weights propagation on massive RDF graphs","display_name":"Combining N-gram retrieval with weights propagation on massive RDF graphs","publication_year":2012,"publication_date":"2012-05-01","ids":{"openalex":"https://openalex.org/W2053084120","doi":"https://doi.org/10.1109/fskd.2012.6233970","mag":"2053084120"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2012.6233970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2012.6233970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 9th International Conference on Fuzzy Systems and Knowledge Discovery","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/A5101182785","display_name":"Hu He","orcid":"https://orcid.org/0000-0002-1556-6715"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]},{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"funder","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"He Hu","raw_affiliation_strings":["Key Laboratories of Data Engineering and Knowledge Engineering, Ministry of Education, China","School of Information, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratories of Data Engineering and Knowledge Engineering, Ministry of Education, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"School of Information, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008721449","display_name":"Xiaoyong Du","orcid":"https://orcid.org/0000-0002-5757-9135"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"funder","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyong Du","raw_affiliation_strings":["Key Laboratories of Data Engineering and Knowledge Engineering, Ministry of Education, China","School of Information, Renmin University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratories of Data Engineering and Knowledge Engineering, Ministry of Education, China","institution_ids":["https://openalex.org/I1327237609"]},{"raw_affiliation_string":"School of Information, Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101182785"],"corresponding_institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":0.4281,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.71837686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1181","last_page":"1185"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9991999864578247,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.9991999864578247,"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":0.9990000128746033,"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":0.9965999722480774,"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":0.8070016503334045},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.754033088684082},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6939225792884827},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.6533498764038086},{"id":"https://openalex.org/keywords/linked-data","display_name":"Linked data","score":0.6420996189117432},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.6283550262451172},{"id":"https://openalex.org/keywords/gram","display_name":"Gram","score":0.6238583326339722},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5464675426483154},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.4707128405570984},{"id":"https://openalex.org/keywords/sparql","display_name":"SPARQL","score":0.4216327667236328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3340877294540405},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.229361891746521},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.07789957523345947}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8070016503334045},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.754033088684082},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6939225792884827},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.6533498764038086},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.6420996189117432},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6283550262451172},{"id":"https://openalex.org/C161369605","wikidata":"https://www.wikidata.org/wiki/Q41803","display_name":"Gram","level":3,"score":0.6238583326339722},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5464675426483154},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.4707128405570984},{"id":"https://openalex.org/C41009113","wikidata":"https://www.wikidata.org/wiki/Q54871","display_name":"SPARQL","level":4,"score":0.4216327667236328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3340877294540405},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.229361891746521},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.07789957523345947},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C523546767","wikidata":"https://www.wikidata.org/wiki/Q10876","display_name":"Bacteria","level":2,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2012.6233970","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2012.6233970","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 9th International Conference on Fuzzy Systems and Knowledge Discovery","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1606325279","https://openalex.org/W2122465391","https://openalex.org/W2338146244","https://openalex.org/W2553798302","https://openalex.org/W2741384016"],"related_works":["https://openalex.org/W199330785","https://openalex.org/W2615202182","https://openalex.org/W98016204","https://openalex.org/W2904139343","https://openalex.org/W2101525042","https://openalex.org/W2767591199","https://openalex.org/W1591429950","https://openalex.org/W2563388676","https://openalex.org/W4388184885","https://openalex.org/W4322622679"],"abstract_inverted_index":{"N-gram":[0],"approach":[1],"takes":[2],"the":[3,40,70,86,100,104,110,131],"position":[4],"information":[5],"into":[6,57],"account":[7],"additionally":[8],"and":[9,22,28,42,52,108],"thus":[10],"can":[11],"offer":[12],"higher":[13],"accuracy":[14],"in":[15,26,31,73,103,138],"query":[16],"answering":[17],"than":[18,50],"keyword":[19],"based":[20,92],"approaches":[21],"is":[23,65,97],"widely":[24],"used":[25],"IR":[27],"NLP.":[29],"However,":[30],"large-scale":[32],"RDF":[33,71,105],"graphs,":[34],"URIs":[35,45,54],"instead":[36],"of":[37],"documents":[38],"are":[39,46,55],"ranking":[41],"querying":[43,64],"units;":[44],"usually":[47,66],"much":[48],"shorter":[49],"documents,":[51],"different":[53],"interlinked":[56],"a":[58,81],"massive":[59],"network.":[60],"One":[61],"shot":[62,112],"n-gram":[63,87,113,143],"not":[67],"good":[68],"for":[69],"data":[72,106],"many":[74],"cases.":[75],"In":[76],"this":[77],"paper,":[78],"we":[79],"present":[80],"hybrid":[82,132],"framework":[83,133],"which":[84],"combines":[85],"retrieval":[88],"with":[89,117],"link":[90,101],"analysis":[91],"weight":[93],"propagation.":[94],"The":[95],"idea":[96],"to":[98],"exploit":[99],"structures":[102],"graphs":[107],"propagate":[109],"one":[111],"score":[114],"weights":[115],"along":[116],"these":[118],"links.":[119],"Large":[120],"scale":[121],"experiments":[122],"using":[123],"MapReduce":[124],"on":[125],"Billion":[126],"Triples":[127],"Challenge":[128],"dataset":[129],"show":[130],"achieves":[134],"an":[135],"80.3%":[136],"improvement":[137],"relevance":[139],"scores":[140],"over":[141],"mere":[142],"retrieval.":[144]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}