Intelligent Search: Connected, Search-Driven & Mobile · Don Miller –2 Rules and an Observation...

transcript

More Chocolate Chip Muffins vs. More Chihuahuas and how AI and Machine Learning are impacting the “Search User Experience”

Don Miller

BA Insight

Intelligent Search: Connected, Search-Driven & Mobile

Don Miller – 2 Rules and an Observation

• Information - Consistency equals transparency, transparency allows you to surface and find the right information

• Relevance is subjective, but consistent metadata makes everything equal even if it is over tagged.

• You need to immediately start looking at how Machine Learning can impact your business. This is not a typical Gartner Hype Cycle

Observation - Machine Learning will not go into trough of disillusionment

About BA Insight

Over 3.5 Million Users

AutoClassifier

70+ Enterprise Systems

SearchIndex(es)

Machine Learning

AI PlatformsGoogle Cloud AI

SmartHubConnectivityHub

Microsoft Cognitive Services

BA Insight Product Portfolio

Our Technology Strategy

▪ Natural Language Query

▪ Bots

▪ Intelligent Query Engine

▪ Search UI (HTML)

▪ Analytics: Reporting and Recommendations

▪ API: Custom UI Development

SmartHub: AI-Driven Platform

▪ Standalone with Elastic and Azure Search and Solr

▪ Integrated with SharePoint/O365

▪ Being Integrated With Existing Applications:

– SiteCore, Outlook, Teams, Browsers, Netdocs, ServiceNow

SmartHub Configurations

▪ Automated Metadata Generation and Tagging

▪ Multiple Tagging Methods:

– Rule-based engine for Auto-tagging, Pattern recognition (PII,

– AI / Machine Learning

o Natural Language Processing: Entity extraction, Document

Summary Generation

o Image Analysis & OCR, Video Analysis, Sentiment Analysis

– Extensible Enrichment

AutoClassifier

▪ Tight Integration with:

– ConnectivityHub: Tagging of content from all sources

– Microsoft / Google AI suites

▪ Plug-Ins for In-Place Tagging of Other Systems

▪ Supports SharePoint, Elastic, Azure Search, ClarityNow

AutoClassifier: Architecture

Connectors to Many Enterprise Systems

• Aderant

• Adobe Experience Manager

• Amazon Aurora

• Amazon RDS

• Amazon S3

• Alfresco

• Azure SQL

• Bentley - Assetwise

• Biomax

• Box

• Confluence

• CuadraSTAR

• Deltek Vision

• Elite / 3E

• File Shares

• Google Cloud

• Google Drive

• HP Consolidated Archive

• (EAS, aka Zantaz)

• HPE Records Manager/

HP TRIM

• IBM Connections

• IBM Content Manager

• IBM DB2

• IBM FileNet P8

• IBM Lotus Notes

• IBM WebSphere

• iManage Work

• Jive

• Kaltura

• LegalKEY

• LexisNexis Interaction

• Lotus Notes Databases

• MediaPlatform

• Microsoft Dynamics CRM

• Microsoft Exchange

• Exchange Public Folders

• Microsoft SQL Server

• MySQL

• NetDocuments

• Neudesic The Firm Directory

• Objective

• OneDrive

• Oracle Database

• OpenText Documentum

• OpenText eDOCS DM

• OpenText eRoom

• OpenText LiveLink/RM

• OpenText Media Manager

• Oracle WebCenter

• PLC/Practical Law

• PostgreSQL

• ProLaw

• Salesforce.com

• SAP ERP

• SAP HANA

• ServiceNow

• SharePoint Online

• SharePoint 2016

• SharePoint 2013

• SharePoint 2010

• SharePoint 2007

• Sitecore

• Slack

• Any SQL-based CRM system

• Veeva Vault

• Veritas Enterprise Vault

(Symantec eVault)

• Website Crawler

• West KM

• Workplace by Facebook

• Xerox DocuShare

• DocuShare

• Yammer

Plus a proven process for creating new connectors to complex systems

Agenda – Today’s topic is how to impact search

2019 Microsoft Search - Ignite

▪ SharePoint Multi-Geo

Hub Sites – Go big provide meaning in title

Graph and Delve – Cloud based

Siri or audio conversion

Why does search matter

Customer Use Cases/Applications

Metadata is context and structure about information

Consistency equals

transparency,

transparency allows

you to surface and

find the right

information

Relevance is

subjective, but

consistent metadata

makes everything

equal even if it is

over tagged.

Internet Sets the Bar for Enterprise Search

WWW leading the way: Search & Refine

Categorisation

Related Content

Refiners & Sorting

Results

Metadata

Imagery

Search

Navigation

▪ Large Fortune 500 Pharma

– Auto tag metadata but spent manual time going through content sources to figure out what

could be leveraged as a rule to assign consistent metadata, then wrote scripts in alignment with

content sources to automate the rule building process

o Manpower plus cash and platform investment

▪ Large Fortune 500 Oil and Gas

– Leverage picture tagging to assign metadata in alignment with rig maintenance

o Primarily cash plus platform investment

▪ Large Top 50 Legal

– Auto tag via entity extraction

o Primarily cash and platform investment

Examples of automating tagging process (Manual is to PAINFUL!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!)

She no worka….

Language and Entity Extraction

Video Image and Audio with Timestamp

Facial Recognition

Signature Recognition

Sentiment Analysis

Language Detection

Where is the Intranet heading?

Ewe ☺

The 4 Must Dos

The missing concierge – Where do your searches/information requests fail?

High Value

– Manual

High Value

– Auto Tag

Low Value

– Manual

Low Value

– Auto Tag

High Value

– Multi

System

Search

High Value

– Single

Search

Low Value –

System

Search

Low Value –

Single

Search

Nearly every Search will need to add

1. Connectivity

Connectors to content & systems outside of O365

2. Structure

Information Architecture & Tags for navigation & findability

3. Context

Personalization through behavioural information

Connectors to Many Enterprise Systems

• Aderant

• Adobe Experience Manager

• Amazon Aurora

• Amazon RDS

• Amazon S3

• Alfresco

• Azure SQL

• Bentley - Assetwise

• Biomax

• Box

• Confluence

• CuadraSTAR

• Deltek Vision

• Elite / 3E

• File Shares

• Google Cloud

• Google Drive

• HP Consolidated Archive

• (EAS, aka Zantaz)

• HPE Records Manager/

HP TRIM

• IBM Connections

• IBM Content Manager

• IBM DB2

• IBM FileNet P8

• IBM Lotus Notes

• IBM WebSphere

• iManage Work

• Jive

• Kaltura

• LegalKEY

• LexisNexis Interaction

• Lotus Notes Databases

• MediaPlatform

• Microsoft Dynamics CRM

• Microsoft Exchange

• Exchange Public Folders

• Microsoft SQL Server

• MySQL

• NetDocuments

• Neudesic The Firm Directory

• Objective

• OneDrive

• Oracle Database

• OpenText Documentum

• OpenText eDOCS DM

• OpenText eRoom

• OpenText LiveLink/RM

• OpenText Media Manager

• Oracle WebCenter

• PLC/Practical Law

• PostgreSQL

• ProLaw

• Salesforce.com

• SAP ERP

• SAP HANA

• ServiceNow

• SharePoint Online

• SharePoint 2016

• SharePoint 2013

• SharePoint 2010

• SharePoint 2007

• Sitecore

• Slack

• Any SQL-based CRM system

• Veeva Vault

• Veritas Enterprise Vault

(Symantec eVault)

• Website Crawler

• West KM

• Workplace by Facebook

• Xerox DocuShare

• DocuShare

• Yammer

Plus a proven process for creating new connectors to complex systems

Only SharePoint and OneDrive Content Surfaces in Delve,

InfoPedia, etc. via the Office Graph

SAP / Oracle

OpenText/Filenet/

Documentum

Content from Other Systems Surfaces in Delve, InfoPedia, etc. via the Office Graph

1. Connectivity

2. Structure

3. Context

Personalization through behavioural information

AutoClassifierrules-driven core, combined with learning-based modules

Enhanced Content

Enriched with

Metadata and

Content Types

Search Visualization Workflow

1. Connectivity

2. Structure

3. Context

Personalization through behavioral information

SmartHub - Context equal personalization

The fourth must do for search success

1. Connectivity

2. Structure

3. Context

4. Measure

Agent Bots Cognitive Machine Learning Augmented RealityMicrosoft Cortana Bot Framework Cognitive Services

- Vision- Speech- Language- Knowledge- Search- Labs

Azure MLCognitive Toolkit

Hololens

Google Google Assistant API.AI Cloud Vision APICloud Video IntelligenceCloud Speech APICloud Natural Language APIGoogle Knowledge GraphGoogle Custom SearchML Advanced Solutions Lab

Cloud ML EngineTensorFlow

Glass at WorkDaydream/Tango

IBM Watson Virtual Agent Watson Conversation Watson APIs- Vision- Speech- Language- Data Insights

Watson ML ServiceApache SystemML

Amazon Alexa Amazon Lex RekognitionPolly

Amazon ML

Apple Siri SiriKitSpeech

Core ML ARKit

Facebook Facebook M ParlAI FastTextCommAI

Torch Oculus Rift

The Cognitive Arms Race

Today’s Session – Recap

More examples

AutoClassifier

SearchIndex(es)

Machine Learning

Content

ContentProcessing

SearchIndex

/ Graph

Search UI

Enhancing Content with Cognitive Services

QueryProcessing

Content

Enrichment

AutoClassifierrules-driven core, combined with learning-based modules

Enhanced Content

Enriched with

Metadata and

Content Types

Adding Text Analytics to ContentUser

Uploads Content Event

Content Text

Analysis

Sentiment - Is text positive or negative?

Key Phrases - What are people discussing in a single article?

Topics - What are people discussing across many articles?

Language - What language is text written in?

Add metadata to item

Shows in O365 search

Adding Translation to ContentUser

Content Text

Analysis

Translation – Copy existing content and translate to specified language

save in SharePoint

Create new file/content for specific language

Image SearchUser

Computer Vision

Image Processing – recognize objects and text inside images

Add metadata to item

Extract image(s)

from documents

Image Classifier and Search

project libraries

issue detection

Where is the Intranet heading?

Search Provides A Unified View

Making O365 search intelligent using Azure Cognitive Services

Start with understanding how it works

Matching IntentContent

Context

ContentEnrichment

Connections

QueryAugmentation

Internet Sets the Bar for Enterprise Search, How do we make search happen on the intranet?

Insight Data Sets