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Agence France-Presse to Deploy TEMIS Semantic Technology Within its New Editorial System
AFP renews his trust in TEMIS semantic content enrichment solution to annotate its news content in 6 different languages, including Arabic
PARIS, March 8, 2012/PRNewswire/ --
TEMIS, leading provider of Semantic Content Enrichment solutions for the Enterprise,
and Agence France-Presse (AFP), one of the three worldwide news agencies, today announced
that they are greatly expanding their strategic partnership to deploy semantic enrichment
on AFP's future editorial console.
Covering the world with a combined 5,000 stories a day in English, French, Spanish,
German, Portuguese and Arabic, AFP required to increase the productivity and consistency
of its news annotation process. To achieve that, AFP has launched a new innovative
editorial system called Iris including advanced tools for journalists. The roll-out of the
Iris system will begin Q2 2012.
Embedded within AFP's new editorial Iris workstation, TEMIS flagship Luxid(R) for
Content Enrichment Platform will annotate the news on-the-fly. This semi-automated process
will increase productivity, making news immediately available, as well as consistency of
tagging, making the search more relevant.
The editorial Iris workstation will embed Luxid(R) recently released version 6,
combined with Text Mining 360degree(s) Skill Cartridge(R) for entity extraction in
English, French, German, Spanish, Portuguese and Arabic.
"At AFP, we are always working on making our editorial processes more efficient. With
Luxid(R) semantic content enrichment, we can now provide our journalists and clients with
ever more relevant and powerful search and navigation tools", said Jean Francois Wets,
Director of Information Systems at AFP. "We are happy to expand our successful
collaboration with TEMIS to this new project, which will now include the whole AFP content
managed in Iris."
"TEMIS is thrilled to keep working with AFP on strategic projects while deploying
Luxid(R) latest release and leveraging our continued effort on Arabic language", said
Vincent Nibart, Director, Publishing Solutions at TEMIS.
Text Mining 360degree(s) Skill Cartridge(R) is an advanced multilingual text analysis
solution for extracting entities such as people names, companies, organizations,
locations, financial amounts, date & time, addresses, phone numbers, emails, etc..
Luxid(R) will also enrich AFP news authored in Arabic language. AFP and TEMIS are
indeed both involved in the SAMAR project, a sponsored research project led by AFP. The
project aims at building a new platform for managing Arabic language multimedia
information. In this project, TEMIS provides its core Text Mining technology to analyze
content in Arabic language and extract relevant entities.
Luxid(R) for Content Enrichment is also already embedded into ImageForum
(http://www.imageforum.afp.com/ImageForum), AFP's e-business platform for pictures.
ImageForum enables subscribers to access AFP and its partners' photos and graphics in real
time via the Internet. Every day, some 5,000 new images feed are added to ImageForum.
Luxid(R) automates the semantic enrichment of captions to produce metadata that help
ImageForum's search engine return more relevant results and provide an enhanced navigation
experience. Luxid(R) not only produces metadata from daily new captions but has also been
processing the 14-million volume of image archives of AFP.
About AFP
AFP is a global news agency delivering fast, accurate, in-depth coverage of the events
shaping our world from wars and conflicts to politics, sports, entertainment and the
latest breakthroughs in health, science and technology. With 2,900 journalists spread
across almost every country, AFP covers the world 24 hours a day in six languages.
http://www.afp.com
About TEMIS
TEMIS is the leading provider of Text Analytics-based semantic content enrichment
solutions, turning unstructured data into actionable knowledge, enabling advanced content
analysis and strategic information discovery. Its flagship Content Enrichment solution,
Luxid(R) automatically associates value-added metadata to content.
TEMIS' innovative solutions address the needs of publishers as well as Enterprises and
have attracted the business of leading organizations such as AAAS (American Association
for the Advancement of Science), ASM (American Society for Microbiology), BASF, Bayer
Schering Pharma, Editions Lefebvre-Sarrut, Elsevier, HCPro, HighWire, IOP Publishing,
Nature Publishing Group, Novartis, Sage, Sanofi-aventis, Simon & Schuster, Springer
Science+Business Media, The McGraw-Hill Companies, Thieme, and Thomson Reuters.
Founded in 2000, TEMIS has offices in the United States, Canada, the UK, France and
Germany, and is represented worldwide through its network of certified partners.
http://www.temis.com [http://http://www.temis.com ]
http://tagline.temis.com
Press contacts:
TEMIS
Martine Falhon
Corporate Communications
Tel: +33(0)4-56-38-24-03
martine.falhon[a]temis.com
Agence France-Presse
Pierre Fernandez
Tel: +33(0)1-40-41-49-23
pierre.fernandez[a]afp.com
Source: TEMIS
Agence France-Presse to Deploy TEMIS Semantic Technology Within its New Editorial System
AFP renews his trust in TEMIS semantic content enrichment solution to annotate its news content in 6 different languages, including Arabic
PARIS, March 8, 2012/PRNewswire/ --
TEMIS, leading provider of Semantic Content Enrichment solutions for the Enterprise,
and Agence France-Presse (AFP), one of the three worldwide news agencies, today announced
that they are greatly expanding their strategic partnership to deploy semantic enrichment
on AFP's future editorial console.
Covering the world with a combined 5,000 stories a day in English, French, Spanish,
German, Portuguese and Arabic, AFP required to increase the productivity and consistency
of its news annotation process. To achieve that, AFP has launched a new innovative
editorial system called Iris including advanced tools for journalists. The roll-out of the
Iris system will begin Q2 2012.
Embedded within AFP's new editorial Iris workstation, TEMIS flagship Luxid(R) for
Content Enrichment Platform will annotate the news on-the-fly. This semi-automated process
will increase productivity, making news immediately available, as well as consistency of
tagging, making the search more relevant.
The editorial Iris workstation will embed Luxid(R) recently released version 6,
combined with Text Mining 360degree(s) Skill Cartridge(R) for entity extraction in
English, French, German, Spanish, Portuguese and Arabic.
"At AFP, we are always working on making our editorial processes more efficient. With
Luxid(R) semantic content enrichment, we can now provide our journalists and clients with
ever more relevant and powerful search and navigation tools", said Jean Francois Wets,
Director of Information Systems at AFP. "We are happy to expand our successful
collaboration with TEMIS to this new project, which will now include the whole AFP content
managed in Iris."
"TEMIS is thrilled to keep working with AFP on strategic projects while deploying
Luxid(R) latest release and leveraging our continued effort on Arabic language", said
Vincent Nibart, Director, Publishing Solutions at TEMIS.
Text Mining 360degree(s) Skill Cartridge(R) is an advanced multilingual text analysis
solution for extracting entities such as people names, companies, organizations,
locations, financial amounts, date & time, addresses, phone numbers, emails, etc..
Luxid(R) will also enrich AFP news authored in Arabic language. AFP and TEMIS are
indeed both involved in the SAMAR project, a sponsored research project led by AFP. The
project aims at building a new platform for managing Arabic language multimedia
information. In this project, TEMIS provides its core Text Mining technology to analyze
content in Arabic language and extract relevant entities.
Luxid(R) for Content Enrichment is also already embedded into ImageForum
(http://www.imageforum.afp.com/ImageForum), AFP's e-business platform for pictures.
ImageForum enables subscribers to access AFP and its partners' photos and graphics in real
time via the Internet. Every day, some 5,000 new images feed are added to ImageForum.
Luxid(R) automates the semantic enrichment of captions to produce metadata that help
ImageForum's search engine return more relevant results and provide an enhanced navigation
experience. Luxid(R) not only produces metadata from daily new captions but has also been
processing the 14-million volume of image archives of AFP.
About AFP
AFP is a global news agency delivering fast, accurate, in-depth coverage of the events
shaping our world from wars and conflicts to politics, sports, entertainment and the
latest breakthroughs in health, science and technology. With 2,900 journalists spread
across almost every country, AFP covers the world 24 hours a day in six languages.
http://www.afp.com
About TEMIS
TEMIS is the leading provider of Text Analytics-based semantic content enrichment
solutions, turning unstructured data into actionable knowledge, enabling advanced content
analysis and strategic information discovery. Its flagship Content Enrichment solution,
Luxid(R) automatically associates value-added metadata to content.
TEMIS' innovative solutions address the needs of publishers as well as Enterprises and
have attracted the business of leading organizations such as AAAS (American Association
for the Advancement of Science), ASM (American Society for Microbiology), BASF, Bayer
Schering Pharma, Editions Lefebvre-Sarrut, Elsevier, HCPro, HighWire, IOP Publishing,
Nature Publishing Group, Novartis, Sage, Sanofi-aventis, Simon & Schuster, Springer
Science+Business Media, The McGraw-Hill Companies, Thieme, and Thomson Reuters.
Founded in 2000, TEMIS has offices in the United States, Canada, the UK, France and
Germany, and is represented worldwide through its network of certified partners.
http://www.temis.com [http://http://www.temis.com ]
http://tagline.temis.com
Press contacts:
TEMIS
Martine Falhon
Corporate Communications
Tel: +33(0)4-56-38-24-03
martine.falhon[a]temis.com
Agence France-Presse
Pierre Fernandez
Tel: +33(0)1-40-41-49-23
pierre.fernandez[a]afp.com
Source: TEMIS