data ninja services - data science summit talk 2016

DATA NINJA ServicesPero SubasicOpen Service Innovation GroupDOCOMO Innovations, Inc.

July 13, 2016

@DataNinjaAPIdataninja.net

NTT DOCOMO, Inc.

• Japan’s largest mobile phone operator • 67M subscribers in Japan• 46% are smart phones• DOCOMO Innovations is a subsidiary

4G subscribers 3G subscribers 2G subscribersNTT DOCOMO mobile market share in Japan

Data Ninja Team

• Part of Open Service Innovation Group at DII• Formed in 2012 with 10+ researchers and engineers

– 7 members with Ph.D. degree – 80+ years of combined experience with more than 50 patents and 120

peer-reviewed papers– Diverse and extensive international large company and startup

experience – Experts in data science and text analysis

Data Ninja Technologies, Applications and Customers

• Technologies– Natural Language Processing (NLP) and Machine Learning– Large-scale Data Analytics and Cloud Computing

• Applications– Personal voice assistants, car navigation assistants– Personalization and recommendation systems– Data management platforms and online advertising– Automated text categorization system

• Customers– Large enterprises including NTT DOCOMO, Toyota, Pioneer, Nissan

– Companies utilizing analytics to enhance service offerings and effectively provide relevant, appropriate and targeted content

Our mission is to enable companies of all sizes to build smart services with content intelligence without having in-house advanced data science and machine learning teams.

Data Ninja Mission

Smart Content Smart Sentiment

Smart Data Smart Learning

Content Intelligence Platform

Data Ninja API

Smart Content

Smart Data

Smart Learning

Smart Sentiment

REST APIpublic cloud or technology licensing API Endpoints

Smart Applications and Services

Unstructured Data (text)

Structured Data (Concepts, Categories and Entities with Sentiments)

http://dataninja.net

Smart Data Service

Smart Data service provides access to our knowledge graphs to complement the Smart Content service allowing development of sophisticated data-science applications.

Concept-category hierarchy Concept relationship graph

Semantic Interpretation

Animals with feathersFarm animals

Small domestic animalsFarm animals - Concept nodes act as network sensors

- Category inference- Concept inference- Learning

- Interaction with content- Communication

- Communication participants’ knowledge bases are different: there is no common grounding -> customization is necessary

- Knowledge bases are continually updated

Knowledge Base Updates

Real World

Timely Updates

Knowledge Base

Interpretation Engine

Environment and customization• General background knowledge• Vertical customization

Automated, timely KB updates• New concepts, categories and

relationships• Custom entities, concepts,

taxonomiesNew, improved interpretations• Finer resolution, increased

accuracy • Enriched interpretation

Smart Data Demo

Smart Data Use Cases

• Concept & Category Contextual Search: Keyword suggestion & expansion

• Related Concept Contextual Search– Personalization by building user profiles based on usage history– Recommendation based on similar concepts (e.g. during cold

starts) • Concept Popularity Lookup

– Smart search using concepts in addition to keywords to increase accuracy

– Popularity-based disambiguation– Trending visualization by finding trends of concepts and categories

for better decision making• Smart Graph

– Generation of linguistics resources for domain-specific applications• Induction Engine

– Discovery of hidden relationships among concepts to better reason with text

Smart Content Overview

Smart Content service extracts meaningful categories, concepts, entities and keywords from unstructured text for broad use in analytics and data science applications.

Smart Content collects relevant data continually to add to its knowledge-base.

Smart Content knowledge-base is extendable through its configurable resource repository with custom user-defined taxonomies and entity dictionaries.

Smart Content Use Cases

Example Use Cases:• Topic Detection and Tracking • Concept-based Retrieval • Image Recommendation for Online Publishing• Contextual Music Recommendation• Semantic Analysis of News Articles - demo

Smart Sentiment Service

Smart Sentiment assigns a positive, negative, neutral, or “none” sentiment value to the content of a natural language text document.

Pre-defined, custom trained models are available for three domains: product reviews, social networks and news articles.

Sentiments are assigned to each extracted entity and keyword.

Smart Sentiment Use Cases

Example Use Cases:• Brand reputation analysis/monitoring

• Product sentiment around release date

• Product reviews

0.4 Sentiment for “Volkswagen” in Sep. ‘15

The U.S. Environmental Protection Agency said Friday that Volkswagen intentionally skirted clean air laws by using a piece of software that enabled about 500,000 of its diesel cars to emit fewer smog-causing pollutants during testing than in real-world driving conditions.The agency ordered VW to fix the cars at its own expense.

201509

Sentiment for entity Volkswagen

Toyota sales fell 9 percent, Honda was down 7 percent and Volkswagen brand vehicles were down 8 percent.

German auto giant Volkswagen posted a 2.8 per cent decline …

Volkswagen’s finance chief Hans Dieter Poetsch is set to become its next chairman, putting Europe’s biggest car maker on course for calmer waters after rival factions including ousted patriarch Ferdinand Piech united to back him.

Newsbot Ninja

https://newsbot.dataninja.net

Newsbot Ninja

Smart Learning Overview

Smart Learning service identifies the intent of a short piece of text, such as natural-language request to perform some action.

The service recognizes 30+ intent categories such as call request, email, news, information seeking, play music, transportation, schedule, shopping, take a photo, and similar.

Smart Learning Use Cases

Use Cases:• Intelligent Personal Assistants such as Siri, Cortana,

and Google Now

• Car Navigation Assistants

• Query and sentence classification

• Intent identification and query extraction in mobile apps

Example: “Find me Italian restaurant in Palo Alto.”Task: Restaurant search Target: Italian restaurant Place: Palo Alto

Thank You!

- Web sites: dataninja.net,demo.dataninja.net. newsbot.dataninja.net

- Visit us at our booth in the expo area

- Sign up for a demo or API

We are hiring!

Backup

DOCOMO Innovations, Inc.

• DOCOMO Innovations is a subsidiary of NTT DOCOMO• We collaborate with business partners, research laboratories, start-

ups and engineers to develop innovative products and services

Smart Content Advantages

• More entities extracted than competitors• Broader concept tagging to provide higher recall• Exclusive access to knowledge-graph hierarchy and

induction engine to facilitate custom advanced development• More categories in taxonomy classification for broader

coverage• Other signals including concept similarity, ranking, and

popularity for further disambiguation• Outstanding price/performance

Smart Content Pricing

data ninja services - data science summit talk 2016

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