@ARTICLE{Juola2006a,
  author = {Juola, Patrick},
  title = {{Authorship attribution}},
  journal = {Foundations and Trends in Information Retrieval},
  year = {2006},
  volume = {1},
  pages = {233--334},
  number = {3},
  abstract = {Authorship attribution, the science of inferring characteristics of
	the author from the characteristics of documents written by that
	author, is a problem with a long history and a wide range of application.
	Recent work in "non-traditional" authorship attribution demonstrates
	the practicality of automatically analyzing documents based on authorial
	style, but the state of the art is confusing. Analyses are difficult
	to apply, little is known about type or rate of errors, and few "best
	practices" are available. In part because of this confusion, the
	field has perhaps had less uptake and general acceptance than is
	its due. This review surveys the history and present state of the
	discipline, presenting some comparative results when available. It
	shows, first, that the discipline is quite successful, even in difficult
	cases involving small documents in unfamiliar and less studied languages;
	it further analyzes the types of analysis and features used and tries
	to determine characteristics of well-performing systems, finally
	formulating these in a set of recommendations for best practices.},
  issn = {1554-0669},
  keywords = {\#News\_Aggregator,\#attribution,\#authorship,\#content},
  mendeley-tags = {\#News\_Aggregator,\#attribution,\#authorship,\#content},
  url = {http://portal.acm.org/citation.cfm?id=1373451}
}

{"_id":{"_str":"51fcd7fec5b22c3876001569"},"__v":31,"authorIDs":["546ca000ec3c47a5180006f3"],"author_short":["Juola, P."],"bibbaseid":"juola-authorshipattribution-2006","bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Juola"],"firstnames":["Patrick"],"suffixes":[]}],"title":"Authorship attribution","journal":"Foundations and Trends in Information Retrieval","year":"2006","volume":"1","pages":"233--334","number":"3","abstract":"Authorship attribution, the science of inferring characteristics of the author from the characteristics of documents written by that author, is a problem with a long history and a wide range of application. Recent work in \"non-traditional\" authorship attribution demonstrates the practicality of automatically analyzing documents based on authorial style, but the state of the art is confusing. Analyses are difficult to apply, little is known about type or rate of errors, and few \"best practices\" are available. In part because of this confusion, the field has perhaps had less uptake and general acceptance than is its due. This review surveys the history and present state of the discipline, presenting some comparative results when available. It shows, first, that the discipline is quite successful, even in difficult cases involving small documents in unfamiliar and less studied languages; it further analyzes the types of analysis and features used and tries to determine characteristics of well-performing systems, finally formulating these in a set of recommendations for best practices.","issn":"1554-0669","keywords":"#News_Aggregator,#attribution,#authorship,#content","mendeley-tags":"#News_Aggregator,#attribution,#authorship,#content","url":"http://portal.acm.org/citation.cfm?id=1373451","bibtex":"@ARTICLE{Juola2006a,\r\n author = {Juola, Patrick},\r\n title = {{Authorship attribution}},\r\n journal = {Foundations and Trends in Information Retrieval},\r\n year = {2006},\r\n volume = {1},\r\n pages = {233--334},\r\n number = {3},\r\n abstract = {Authorship attribution, the science of inferring characteristics of\r\n\tthe author from the characteristics of documents written by that\r\n\tauthor, is a problem with a long history and a wide range of application.\r\n\tRecent work in \"non-traditional\" authorship attribution demonstrates\r\n\tthe practicality of automatically analyzing documents based on authorial\r\n\tstyle, but the state of the art is confusing. Analyses are difficult\r\n\tto apply, little is known about type or rate of errors, and few \"best\r\n\tpractices\" are available. In part because of this confusion, the\r\n\tfield has perhaps had less uptake and general acceptance than is\r\n\tits due. This review surveys the history and present state of the\r\n\tdiscipline, presenting some comparative results when available. It\r\n\tshows, first, that the discipline is quite successful, even in difficult\r\n\tcases involving small documents in unfamiliar and less studied languages;\r\n\tit further analyzes the types of analysis and features used and tries\r\n\tto determine characteristics of well-performing systems, finally\r\n\tformulating these in a set of recommendations for best practices.},\r\n issn = {1554-0669},\r\n keywords = {\\#News\\_Aggregator,\\#attribution,\\#authorship,\\#content},\r\n mendeley-tags = {\\#News\\_Aggregator,\\#attribution,\\#authorship,\\#content},\r\n url = {http://portal.acm.org/citation.cfm?id=1373451}\r\n}\r\n\r\n","author_short":["Juola, P."],"key":"Juola2006a","id":"Juola2006a","bibbaseid":"juola-authorshipattribution-2006","role":"author","urls":{"Paper":"http://portal.acm.org/citation.cfm?id=1373451"},"keyword":["#News_Aggregator","#attribution","#authorship","#content"],"downloads":0,"html":""},"bibtype":"article","biburl":"http://delicias.dia.fi.upm.es/prov-xgCURATED.bib","downloads":0,"keywords":["#news_aggregator","#attribution","#authorship","#content"],"search_terms":["authorship","attribution","juola"],"title":"Authorship attribution","title_words":["authorship","attribution"],"year":2006,"dataSources":["drTBSwRdnSo2Wujnd"]}