Redefining Perspectives - June 2015

Redefining Perspectives A thought leadership forum for technologists interested in defining a new future

June - 2015

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Session 2

Semantic Search – the technology and its application in financial markets


Search

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Search

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Keyword based Search Engine

Search Engine User

“Give me what I Said”

ENTERPRISE ECOSYSTEM

Search – Enterprise Ecosystem


60% of Enterprise Data are Unstructured

Structured Data

Trading

Reference

SecuritySearch Silos

Keyword Based Search

Semi Structured Data

Wiki

Vendor Data

Reports

“Give me what I asked”

Unstructured Data

Research

Company Filings

Feeds Data

Search Silos

Custom Search Application

Custom Search Application

Semantic Search – Making Results Relevant


Context & Intent based,

Meaning & Relationships among words

Semantic Search – Making Results Relevant


Disambiguate

“Give me what I Want; Not just what I Say”

Search – Enterprise Semantic Ecosystem


Enterprise Semantic

Search

Knowledge Discovery

Enterprise Content Enterprise Semantic Search

Linked Data

DBPedia

Freebase

Internal Knowledge

Base

Enterprise Data Models

Content Extraction

Context Mapping

Contextual Meaning

Inferencing

Structured

Unstructured

Semi-Structured

We’ll focus on…

• We will consider a Financial Domain Investment Bank Use Case

• How Semantic Search Platform is built technically in-line with the use case


The Use Case – Investment Research


A typical Research team in an Investment Bank performs the following:

• Manually gather research information• Analyze gathered documents to find

requested information

Challenges:

• High volume of research corpus

• Manual Analysis results in• Inaccuracy• Longer Response Time• Time to Market• Lower ROI

Automate Routine Requests Faster response. But limited benefit. Problem still remains for Complex Information

Requests

Outsourcing Research Team Potential Cost Savings Problem not solved but moved to a different place.

QoS risks.

Ontology Based Semantic Search

Faster Response More Relevant and Contextual Search Results Knowledge Discovery through Inferencing Domain and technology expertise required

Current Scenario Options Pros/Cons

The Use Case – Investment Research


Build a Semantic Search platform that leverages latest advancements in Search and Natural Language Processing to make Investment Research Experience significantly more efficient and effective

Maximize ROI on Market Research Spending

Get Insight to Timely Industry Information

Find and Discover Actionable Knowledge

Perform Informed Investment Decisions

The Use Cases – Potential Search Queries


‘HSBC Holdings Plc’ ‘Asset Write down’ Asia

Interest rate risk private banks Western Europe

Documents about banks based out of Paris and talk about interest rates volatility in Western Europe

Companies in Eastern Europe whose turnover is greater than $100 million and face challenge of nationalization

Show me documents about Retail Banks in South Asia whose P/E ratio is greater than 20.0

Do a proximity search on ‘Regulatory Change’ with reference to ‘Retail Banking’

Looking for documents published by HSBC and authored by Ronit Ghose

Enabling Semantic Search - Approaches

1. Lexicon and Ontological Based Search

2. Statistical Analysis and/or Pattern Matching Search


Enabling Semantic Search – 4 Pillars


Reasoning Engines

Natural Language

Processing

Ontology

Semantic Analysis

Enabling Semantic Search – Core Concepts


Model defined using constructs for:

• Concepts – classes

• Relationships – properties (object and data)

• Rules – axioms and constraints

• Instances of concepts – individuals (data)

• Uses W3C standards RDF/S and OWL

Relationships

Concepts/Classes

Instances

What is Ontology ?

It’s an Knowledge Model, assembly of concepts in which all possible relationships that might exist among concepts are explicitly mapped. it captures knowledge so that,

• Questions can be answered• New Insights can be generated

Enabling Semantic Search – Core Concepts


Data stored in TriplesExpressed as Subject : Predicate : Object

Internal Knowledge

Base

DISCOVER NEW INSIGHTS

Pranab Mukherjee New Delhi IndiaLives in Is in

Lives inGet me documents about Retail Banks in Eastern Europe which have net profit great than $10 million and are facing challenges of nationalization

Putting It All Together - Application Process Flow


Content Providers

Content Extraction & Standardization

StandardizedDocument

Step 1

Content Ingestion

Classification

Ontology Tagging

Meta Data

Document Store

XML and Triple Storage

Indexing &Querying

Step 2

Content Delivery

Search

Engagement

Step 3

Components – Content Extraction & Standardization


Unstructured Content

Text Extraction & Standardization

Metadata Extracted Textual Content

• Extract Meaning from Unstructured Data

• Transform into Structured Data for Auto Tagging

Components – Content Ingestion


Ontology Management

A tool that supports lists, controlled vocabularies, taxonomies, thesauri or ontologies:• Concepts/Terms• Taxonomy• Associative Relationships• Synonyms

http://wiki.opensemanticframework.org/index.php/Ontology_Tools

Components – Content Ingestion


Content Classification

• Analyze document

• Add metadata ‘tags’ that describe that documents which are sourced from Ontology

Example : Classification Results

Components – Data Store & Search Engine


Typical Architecture


CO

RE

PL

AT

FO

RM

STORAGE LAYER

PRESENTATION LAYER

Free-Text Search

Ontology Driven Search

Graph Search Collaboration Engagement

CORE SERVICES

Logging

Caching

Security

Monitoring

IndexesContent Store

Triples

Inferencing

SPARQL

XQUERY

Classification Server

Ontology Server

RuleSets

Inference Engine

ONTOLOGY MGMT

Ontology Creation

RuleSets

Entity Extraction

Inferencing

CONTENT DELIVERY

Query pre-processor

Query Builder

Inference Engine

Results post-processor

CONTENT INGESTION

Import

Classification/ Indexing

Standardization / Structuring

Storage

Semantic Search – Opportunities & Beyond


Augmented Reality

Other Possibilities?

http://augmentedpixels.com/wp-content/uploads/2014/04/augmented-reality-iphone-football-concept.jpg

http://www.ventures-africa.com/wp-content/uploads/2015/01/original_aefd15169aaebd3f037b5ed672db6de1.png

Question AnswerThank you


Technology

Redefining Perspectives - June 2015