{"id":"https://openalex.org/W2023420943","doi":"https://doi.org/10.4304/jnw.9.4.993-999","title":"Heterogeneous Web Data Extraction Algorithm Based On Modified Hidden Conditional Random Fields","display_name":"Heterogeneous Web Data Extraction Algorithm Based On Modified Hidden Conditional Random Fields","publication_year":2014,"publication_date":"2014-04-01","ids":{"openalex":"https://openalex.org/W2023420943","doi":"https://doi.org/10.4304/jnw.9.4.993-999","mag":"2023420943"},"language":"en","primary_location":{"id":"doi:10.4304/jnw.9.4.993-999","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.9.4.993-999","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-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/A5101128703","display_name":"Cui Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Cui Cheng","raw_affiliation_strings":["Department of Information Engineering Jilin Police College, Changchun"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering Jilin Police College, Changchun","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5101128703"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16607055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":"4","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":1.0,"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/T12016","display_name":"Web Data Mining and Analysis","score":1.0,"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/T11478","display_name":"Caching and Content Delivery","score":0.9710999727249146,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T13976","display_name":"Web visibility and informetrics","score":0.9307000041007996,"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":0.8980517387390137},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.7110821008682251},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4301125407218933},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4271141290664673},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3094509243965149}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8980517387390137},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.7110821008682251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4301125407218933},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4271141290664673},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3094509243965149}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.4304/jnw.9.4.993-999","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jnw.9.4.993-999","pdf_url":null,"source":{"id":"https://openalex.org/S189188848","display_name":"Journal of Networks","issn_l":"1796-2056","issn":["1796-2056"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Networks","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1973625941","https://openalex.org/W1980818185","https://openalex.org/W1981791873","https://openalex.org/W1998654057","https://openalex.org/W2005646337","https://openalex.org/W2008723124","https://openalex.org/W2031404913","https://openalex.org/W2040757233","https://openalex.org/W2045986835","https://openalex.org/W2060645041","https://openalex.org/W2088600132","https://openalex.org/W2089078841","https://openalex.org/W2101534792","https://openalex.org/W2114541504","https://openalex.org/W2130041528","https://openalex.org/W2135186040","https://openalex.org/W2160189941","https://openalex.org/W2165887717","https://openalex.org/W2166983036","https://openalex.org/W2168196213","https://openalex.org/W2168358004","https://openalex.org/W2271908734","https://openalex.org/W2911997683","https://openalex.org/W3093414588"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2356597680","https://openalex.org/W2114846443","https://openalex.org/W2093471820","https://openalex.org/W3102147106","https://openalex.org/W2347460059","https://openalex.org/W50079190","https://openalex.org/W3136048405","https://openalex.org/W182104056"],"abstract_inverted_index":{"As":[0],"it":[1,179],"is":[2,99],"of":[3,49,128,147],"great":[4],"importance":[5],"to":[6,75,158],"extract":[7,188],"useful":[8,189],"information":[9,190],"from":[10,191],"heterogeneous":[11,21,52,137,192],"Web":[12,22,53,138,175,193],"data,":[13],"in":[14,64],"this":[15],"paper,":[16],"we":[17,56],"propose":[18],"a":[19,27,121],"novel":[20],"data":[23,54,97,139,176,194],"extraction":[24,177],"algorithm":[25,186],"using":[26,101],"modified":[28,149],"hidden":[29,60,72,78,84,102,129,150],"conditional":[30,40,61,85,130,151],"random":[31,41,62,86,131,152],"fields":[32,42,63,87,132],"model.":[33],"Considering":[34],"the":[35,47,58,71,77,82,92,113,136,144,148,173,184],"traditional":[36],"linear":[37],"chain":[38],"based":[39],"can":[43,109,117,180,187],"not":[44],"effectively":[45,195],"solve":[46],"problem":[48],"complex":[50],"and":[51,105,135,167,196],"extraction,":[55],"modify":[57],"standard":[59,83,164],"three":[65],"aspects,":[66],"which":[67],"are":[68,133,140,156],"1)":[69],"Using":[70],"Markov":[73,103],"model":[74],"calculate":[76],"variables,":[79],"2)":[80],"Modifying":[81],"through":[88],"two":[89,163],"stages.":[90],"In":[91,112],"first":[93],"stage,":[94,115],"each":[95],"training":[96],"sequence":[98],"learned":[100,119],"model,":[104],"then":[106],"implicit":[107],"variables":[108],"be":[110,118,181],"visible.":[111],"second":[114],"parameters":[116],"for":[120],"given":[122],"sequence.":[123],"(3)":[124],"The":[125],"objective":[126],"functions":[127],"revised,":[134],"extracted":[141],"by":[142],"maximizing":[143],"posterior":[145],"probability":[146],"fields.":[153],"Finally,":[154],"experiments":[155],"conducted":[157],"make":[159],"performance":[160],"evaluation":[161],"on":[162],"datasets-EData":[165],"dataset":[166],"Research":[168],"Papers":[169],"dataset.":[170],"Compared":[171],"with":[172],"existing":[174],"methods,":[178],"seen":[182],"that":[183],"proposed":[185],"efficiently.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}