General Motors
BP
Ford Motor Company
AstraZeneca
DaimlerChrysler
CNN
General Electric
US Senate
Credit Suisse First Boston
Volkswagen
Siemens
Philip Morris
Bloomberg
BBC
Verizon
BP
AT&T
FIAT
Nestle
Credit Lyonnais
HP
Philips
Swiss Army
Sun Microsystems
General Motors
General Dynamics
Hewlett Packard
ABN Amro
Lloyds
Macmillan Publishing
UBS Warburg
Merrill Lynch
New York Stock Exchange
Hewlett Packard
US State Department
The Economist
France Telecom
Boeing
AT&T
Lafarge
Safeway
People's Republic of China's
Ministry of Agriculture
Nordea
General Motors
Tesco
Pfizer
Philips
The Coca Cola Company
Sybase
Sprint
New York Life Insurance
Canon USA
BP
Novell
Nestle
Ericsson
EDS
Philip Morris International
Royal & SunAlliance
MOL
Novartis
HM Revenue & Customs
Credit Lyonnais
Sun Microsystems
British American Tobacco
Norsk Hydro
AstraZeneca
Vodafone Omnitel
Lloyds
Skanska
BAE Systems
Kodak
The Royal Mail Group
Henkel
Bank of Montreal
Hewlett Packard
3
Danske Bank
BMW
Kronos Corporation
Fujitsu Technology Services
Zurich Financial Services
General Electric
Sun Microsystems
Halliburton
BBC
General Motors
Blue Cross/Blue Shield of Massachusetts
T-Mobile
Channel 4 Corporation
Pfizer
VHA
Ericsson
Burges Salmon
Motorola
British Telecom
Ferrari
Ericsson
Lloyds
Deloitte & Touche
Sun Microsystems
Philips
AstraZeneca
PA Consulting
BP
US Army
UK Department of Trade & Industry
EMC Corporation
Danske Bank
US Department of Commerce
Encana Corporation
IEEE
Hewitt Associates LLC
T-Mobile
HEALTHvision
Paramount
3
BBC
AstraZeneca
Lexmark
US Department of Defense
JD Edwards
Ingersoll-Rand
3
PricewaterhouseCoopers
Vodafone Omnitel
Nomura
US State Department
Reed Elsevier
Dow Chemical Company
Siemens Power Generation
Texas Instruments
Forrester Research
McData
AstraZeneca
Wall Street Journal
Lloyds
NASA
SCA
Reuters
US Department of Commerce
ITN
AstraZeneca
IBM NICA
Siemens
Forbes.com
Nissan North America, Inc.
Toyota Motor
The McGraw-Hill Companies
Fox Sports
Society of Petroleum Engineers
US Department of Energy
European Commission
Telecom Italia
Harrah's
3
AXA
The McGraw-Hill Companies
US State Department
Sybase
General Motors
Nestle
Napster
US Department of Defense
3
Oracle
Compuware
Siemens
Olympus
ARM
Philips
Taylor & Francis
Federal Express
Philips
Ingersoll-Rand
Nissan Motor
Milward Brown Precis
Federal Government of Canada
UK Home Office
Henkel
Britvic Softdrinks
HM Revenue & Customs
3
UK Department of Trade & Industry
Harvard Business School
Britvic Softdrinks
MOL
Macmillan Publishing
Allianz Life Insurance Co
Swiss Army
Parliament of Singapore
AT&T
Nestle
VMS
Singapore Police Force
3
Sony Music
GSA Advantage!
Kaiser Permanente
Stanford Business School
Johns Hopkins
Wachovia
Standard Life Insurance
Raytheon
Commerzbank
Allstate Insurance
State of Washington
Royal & SunAlliance
Napa Valley County
Texas Department of Transportation
American HomePatient
TIBCO
UK Department of Trade & Industry
Sharper Image
US Department of Defense
Nestle
ABN Amro
Xerox
America Online
Lockheed Northrop Grumman
AstraZeneca
Dow Chemical Company
Draeger Medical
AstraZeneca
Sutter Health
Kenyan AIDS Clinic
New York Life Insurance
US State Department
University of Washington
State of Minnesota
World Wildlife Fund
Autonomy Group Customers
 
管理系
ユーザインタフェース
エンタープライズサーチ
分析&タクソノミ
コラボレーション&パーソナライゼーション

Functionality マルチデバイス対応(英語) | 自動カテゴライズ/タクソノミ生成(英語) | 自動クラスタリング
概要
関連イベント
導入事例
関連資料
関連ニュース

Automatic Classification and Taxonomy Generation

IDOL's classification solutions remove the time-consuming reliance on manual intervention required by traditional methods and overcomes issues caused by the exponential growth of unstructured data through its ability to automatically, consistently and accurately classify data. IDOL provides a wide range of highly automated and scalable classification solutions.

Automatic Categorization and Channels

By understanding the information in your enterprise, IDOL automatically generates taxonomies and instantly organizes the data into a familiar child/parent taxonomical structure. IDOL automatically identifies, names and creates each node based on an understanding of the concepts within the data set as a whole. IDOL eliminates the need for any human intervention, preventing the errors and inconsistency that are frequently associated with manual categorization.

Autonomy Collaborative Classifier (ACC)

ACC is a comprehensive management interface for people who know and use taxonomies, such as subject matter experts, and people responsible for the controlled vocabularies used within the enterprise, such as knowledge engineers. It enables cross functional collaboration between these experts, allowing improvements to be made in real-time so that the enterprise can adapt in response to changing business requirements.

Autonomy enables existing taxonomies to be imported, including: Web URLs, file paths, Autonomy taxonomies, as well as corporate and other third party taxonomies.

Taxonomy Libraries

Built by experienced knowledge engineers using best practices learned through hundreds of consulting engagements, Autonomy taxonomies let organizations rapidly deploy industry-standard taxonomies that can be combined with your corporate taxonomies or easily customized to meet company and industry-specific requirements. Each Autonomy taxonomy is based on industry standards, and built using IDOL's conceptual analysis that provides the highest level of accuracy.

The range of available taxonomies includes:

Biotechnology
Homeland Security
Civil / Criminal Procedure
Human Resources
Defense
Information Technology
Electronic, Mechanical and Structural Engineering
Petrochemical
Emergency Services
Pharmaceutical
Epidemiology
Sales and Marketing
Financial Services

今後開催されるイベントのページです。詳細は こちら もご覧ください。

IDOLサーバ 7 による 自動ハイパーリンキング

一部の導入事例をご紹介しています。より詳細は、 http://publications.autonomy.com/ をご覧ください。

IDOLサーバ 7 による 自動ハイパーリンキング

Functionality マルチデバイス対応(英語) | 自動カテゴライズ/タクソノミ生成(英語) | 自動クラスタリング
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