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New in HPE IDOL 11 March 2016
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Intuitive Knowledge Discovery for Self-Service Analytics
Business Intelligence for Human Information (BIFHI) Visualization to simplify analytics workflow What is it? A new end-user GUI provides a straightforward analytics workflow for diverse use cases. BIFHI incorporates visualization functionality such as topic map to highlight key concepts, sunburst diagram to enable easy filtering based upon extracted entities (e.g. people, place, company),result set comparison to examine how a change of search parameter may impact the outcome and rich contextual view where the query result includes not only the document itself, it shows the metadata and other relevant information such as documents by the same author or documents from around the same period. Why does it matter? The intuitive interface enables business users to perform self-service analytics and shortens time to insight. For example, the user can search for a topic, visualize the result breakdowns on the main panel, and refine the search parameters on the side panel with automated guidance based upon IDOL’s deep understanding of queried data, and see real-time result changes, all within the same window. Topics Map Sunburst Result Comparison Rich Contextual View
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Out Of The Box Foundation and Framework For Diverse Use Cases
Business Intelligence for Human Information (BIFHI) While BIFHI provides OTTB BI functionality, it is designed to be highly customizable and extensible. It serves as a foundation and framework for supporting diverse use cases so users can easily harness hundreds of advanced analytics functions in IDOL to address specific requirements now and in the future. HPE IDOL
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Discover Relationships for Richer Insight
Knowledge Graph Customer A is in Customer B’s network Customer C is linked to Customer E via Customer D What is it? It discovers relationships between entities (e.g. people, places, companies) that lead to richer and more impactful knowledge discovery. It identifies and reveals connections, connection path(s) and common traits. Why does it matter? It provides critical insights into how entities relate and facilitates investigation into potential network of influence. For example, it is now possible to answer the question of what your customers have in common besides using your flagship product. Customers F and G purchased the same model last year Customer H is the most influential in Customer B’s network
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Out Of The Box Enterprise Search Interface for instant productivity
HPE Find Open Source What is it? HPE Find, an open source tool contributed by HPE, is an extensible Enterprise Search user interface, which now ships with HPE IDOL for our customer’s convenience. It is designed to be a highly flexible foundation upon which custom-made applications can be based Why does it matter? The quick-to-start and easy-to-use interface enables almost instantaneous search productivity while accelerating the development of applications requiring intelligent search capabilities. Pre-integrated with HPE IDOL Accelerate search deployment Customizable and Extensible Easy embedding of intelligent search
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Faster and more accurate rich media analytics
Deep Neural Networks and Machine Learning In IDOL 11 release, we have implemented advanced DNN and ML algorithms to significant improve the speed and accuracy of rich media analytics. Some of the key areas benefiting from this are face recognition, speech-to-text and speaker identification Face Recognition Speech to Text Speaker Identification
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More accurate and flexible face recognition
False positives and negative down by 50% What is it? A new algorithm based on deep convolutional neural networks, which halves the face recognition error rate. The new face recognition algorithm also works on a much wider range of face angles, full frontal view of the face is not necessary. Why does it matter? It significantly elevates the level of accuracy by reducing false positives and false negatives by 50% Full frontal view not required
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More accurate speech to text
What is it? Accuracy optimizations to Deep Learning technology through the use of Convolutional Layers and Deep Neural Networks optimized acoustic processing as well as the release of voice call optimized language packs (English only). Language packs updated with this release include: •Broadband: British English, US English, Modern Standard Arabic, Farsi, French, Hungarian, Dutch •Telephony: British English, US English, Hungarian Why does it matter? Our latest English US Telephony language pack shows a 13% decrease in word error rate (WER), English UK Telephony language pack shows a 12% decrease, and Hungarian Broadband language packs also shows a 12% decrease in WER over sample test sets*. The enhanced accuracy will impact all speech-to-text use cases including broadcasting monitoring, and voice call analytics. *Stated figures are data dependent and may vary by environment and test set. UK Telephony English Word Error Rate down by 12% US Telephony English Word Error Rate down by 13%
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Speaker Identification
33% faster What is it? Extensive improvements to the underlying machine learning algorithms: •Faster processing speed •Lower memory requirements •Increased trained speaker capacity •Ability to define speaker sets •Simplified speaker training by allowing iteration output to be passed straight through to the next training iteration An example identification task using 200 trained speakers now runs 33% faster than the previous release, and uses less than 50% of the memory* Why does it matter? It significantly accelerates the identification of the most relevant speaker(s) over larger speaker groups while reducing hardware overhead. It also simplifies the process of identifying speakers over a large audio archive, by allowing an initial short speaker sample to be built upon as more matches are found across the archive. 50% less memory
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New language classifiers for multi-lingual environments (call centers)
Czech Danish Dutch English French Italian Polish Romanian Russian Spanish Swedish French Canada English US What is it? Released across our most popular Telephony language packs, allowing high accuracy Language Identification of voice calls out of the box. ENUS – English US ENUK – English UK ENAU – English Australia ESLA – Spanish Latin America ESES – Spanish Spain FRFR – French France FRCA – French Canada ITIT – Italian DADK – Danish NLNL - Dutch SVSE - Swedish RURU - Russian CSCZ - Czech RORO - Romanian PLPL - Polish Why does it matter? This supports multi-lingual environments such as a call center handling voice calls in a number of languages, as well as automatic indexing of large multi-lingual voice call archives. First the language is identified and then used in the subsequent speech to text process. Spanish English Australia
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Expanded license plate coverage
28 locations added New global total – 101 All 50 U.S. states covered Support expanded to include 28 new global locations and extended to all 50 states in U.S.A. Please see below for the complete list of supported locations What is it? Why does it matter? Enable out of the box implementation for these new locations and eliminate the need for custom development. Albania Algeria Argentina Australia - NSW Australia - Queensland Australia - South Australia Australia - Victoria Australia - Western Australia Austria Bahrain Belgium Brazil Colombia Czech Republic Denmark Finland France Germany Greece India Indonesia Ireland Israel Italy Japan Kingdom of Saudi Arabia Kuwait Mexico Netherlands New Zealand Nigeria Norway Oman Peru Philippines Poland Portugal Qatar Russia Serbia Slovenia South Africa Spain Sweden Switzerland Thailand Turkey Ukraine United Arab Emirates United Kingdom United States - Alabama United States - Alaska United States - Arizona United States - Arkansas United States - California United States - Colorado United States - Connecticut United States - Delaware United States - Florida United States - Georgia United States - Hawaii United States - Idaho United States - Illinois United States - Indiana United States - Iowa United States - Kansas United States - Kentucky United States - Louisiana United States - Maine United States - Maryland United States - Massachusetts United States - Michigan United States - Minnesota United States - Mississippi United States - Missouri United States - Montana United States - Nebraska United States - Nevada United States - New Hampshire United States - New Jersey United States - New Mexico United States - New York United States - North Carolina United States - North Dakota United States - Ohio United States - Oklahoma United States - Oregon United States - Pennsylvania United States - Rhode Island United States - South Carolina United States - South Dakota United States - Tennessee United States - Texas United States - Utah United States - Vermont United States - Virginia United States - Washington United States - West Virginia United States - Wisconsin United States - Wyoming Venezuela
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Learn more: IDOL - www. hpe
Learn more: IDOL - Rich media analytics –
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