{"id":"https://openalex.org/W2547901313","doi":"https://doi.org/10.1109/icacci.2016.7732034","title":"Entropy based informative content density approach for efficient web content extraction","display_name":"Entropy based informative content density approach for efficient web content extraction","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2547901313","doi":"https://doi.org/10.1109/icacci.2016.7732034","mag":"2547901313"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2016.7732034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5084480545","display_name":"Manjusha Annam","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Manjusha Annam","raw_affiliation_strings":["Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, IN"],"affiliations":[{"raw_affiliation_string":"Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, IN","institution_ids":["https://openalex.org/I81556334"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073768586","display_name":"G P Sajeev","orcid":null},"institutions":[{"id":"https://openalex.org/I81556334","display_name":"Amrita Vishwa Vidyapeetham","ror":"https://ror.org/03am10p12","country_code":"IN","type":"education","lineage":["https://openalex.org/I81556334"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G P Sajeev","raw_affiliation_strings":["Dept of Computer Science and Engineering, Amrita University, India"],"affiliations":[{"raw_affiliation_string":"Dept of Computer Science and Engineering, Amrita University, India","institution_ids":["https://openalex.org/I81556334"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5084480545"],"corresponding_institution_ids":["https://openalex.org/I81556334"],"apc_list":null,"apc_paid":null,"fwci":3.3175,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.93474535,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"8","issue":null,"first_page":"118","last_page":"124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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/T11269","display_name":"Algorithms and Data Compression","score":0.954800009727478,"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/T11478","display_name":"Caching and Content Delivery","score":0.9510999917984009,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7835478782653809},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.6588195562362671},{"id":"https://openalex.org/keywords/web-content","display_name":"Web content","score":0.627880334854126},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6210533380508423},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.5559769868850708},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4644510746002197},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3241952955722809},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.20840081572532654},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14180636405944824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7835478782653809},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.6588195562362671},{"id":"https://openalex.org/C2776324614","wikidata":"https://www.wikidata.org/wiki/Q3948731","display_name":"Web content","level":3,"score":0.627880334854126},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6210533380508423},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.5559769868850708},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4644510746002197},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3241952955722809},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20840081572532654},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14180636405944824},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2016.7732034","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2016.7732034","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W100562005","https://openalex.org/W1890508656","https://openalex.org/W1989338554","https://openalex.org/W1997838466","https://openalex.org/W2012575882","https://openalex.org/W2019264297","https://openalex.org/W2019577381","https://openalex.org/W2107467543","https://openalex.org/W2121640842","https://openalex.org/W2129595335","https://openalex.org/W2139481238","https://openalex.org/W2146990843","https://openalex.org/W2147220393","https://openalex.org/W2167167851","https://openalex.org/W2167859982","https://openalex.org/W2314353303","https://openalex.org/W4240344917","https://openalex.org/W4244354591","https://openalex.org/W4255475599","https://openalex.org/W6604096230","https://openalex.org/W6639554339"],"related_works":["https://openalex.org/W4249299808","https://openalex.org/W2483353929","https://openalex.org/W2464413305","https://openalex.org/W2163230867","https://openalex.org/W4255475599","https://openalex.org/W4307079979","https://openalex.org/W2544674189","https://openalex.org/W2897171874","https://openalex.org/W1987716395","https://openalex.org/W2550808318"],"abstract_inverted_index":{"Web":[0],"content":[1,11,24,52,57,85,138],"extraction":[2,53,58,86],"is":[3,25,31,41,46,59,111,121,145],"a":[4,26,83,140],"popular":[5,61],"technique":[6,87],"for":[7,113,127],"extracting":[8],"the":[9,17,22,38,49,73,108,124,129,134,150],"main":[10],"from":[12,68],"web":[13,39,51,84],"pages":[14,74],"and":[15,43,78,149],"discards":[16],"irrelevant":[18],"content.":[19,106],"Extracting":[20],"only":[21],"relevant":[23,42],"challenging":[27],"task":[28],"since":[29],"it":[30],"difficult":[32],"to":[33,122,133],"determine":[34],"which":[35,44],"part":[36,45],"of":[37,119,136],"page":[40],"not.":[47],"Among":[48],"existing":[50],"methods,":[54,66],"density":[55,64,105],"based":[56,65,91],"one":[60],"method.":[62],"However":[63],"suffer":[67],"poor":[69],"efficiency,":[70],"especially":[71],"when":[72],"containing":[75],"less":[76],"information":[77,125],"long":[79],"noise.":[80],"We":[81],"propose":[82],"build":[88],"on":[89],"Entropy":[90],"Informative":[92],"Content":[93],"Density":[94],"algorithm":[95,100],"(EICD).":[96],"The":[97,116,142],"proposed":[98,143],"EICD":[99,120],"initially":[101],"analyses":[102],"higher":[103],"text":[104],"Further,":[107],"entropy-based":[109],"analysis":[110],"performed":[112],"selected":[114],"features.":[115],"key":[117],"idea":[118],"utilize":[123],"entropy":[126],"representing":[128],"knowledge":[130],"that":[131],"correlates":[132],"amount":[135],"informative":[137],"in":[139],"page.":[141],"method":[144],"validated":[146],"through":[147],"simulation":[148],"results":[151],"are":[152],"promising.":[153]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
