Veda Semantic Technology

Convert Data to Actionable Intelligence

2

Veda Overview – Origin and Growth

1.Semantic Technology IP

2.Originated at Fraunhoffer Institute, Germany

3.Product enhanced over the last decade

4.End to end Semantic Framework

3

Veda Overview - COP Model

1.Covers all aspects of a Business Solution

2.Has the ability to work on Structured and Unstructured Data

3.The framework enables rapid deployment of Semantic

Applications

4

Veda Overview - Product Portfolio Area Technology / Tools Description

C o

l l e

c t

Data Aggregation

Web Crawler Supports HTTP with authentication

Email Crawler Supports IMAP, POP3 protocols

Database Crawler Supports relational databases

File Crawler Word Reader, PDF Reader, Text Reader, HTML Reader

Information Extraction

Visual Entity Extractor Domain specific entity extraction platform

Term Extraction NLP based concept, phrase identification

O r

g a

n I

z e

Information Organization

Semantic Net API & Editor

S-net editor

Ontology Editor OWL editor, Rules

AutoClassification Lazy (term-based) and machine learning

Ontology Data Mapping

Maps data to the ontology

P r

e s

e n

t

Information Retrieval and Analysis

Semantic Matching Context based retrieval using semantic net

Inference Engine Supports OWL DL Lite

Latent Semantic Indexing

Latent semantic analysis and information retrieval

Semantic Rule Engine Rule engine with inferencing capabilities

Patents Filed Visual entity extraction technique

Method of Context-based information retrieval

5

Product Strategy

Semantic Search

Standards Text Analysis Automated

Reasoning Semantic

Content Mgmt. Knowledge

based applications

Semantic Social Computing

Linked Data

2011 2012 2013

Evo

luti

on

of

Sem

anti

c Te

chn

olo

gy

Matured

Advanced

Progressive

Inception

Legend

Semantic Search Standards Text Analysis Automated

Reasoning Semantic


based Apps Semantic Social

Computing Linked Data Predictive

Analytics

2014

Semantic Search


Reasoning Semantic




Analytics

Semantic Search


Reasoning Semantic




Analytics

6

Product Map vis-à-vis Opportunity Areas Functional Areas Technology Components Availability in

Veda

Content

Management

Social Media

Platform

Semantic

Search

Platform

Advertising

Tools

Text

Analysis

Consumer

Insights

Semantic

Mobile and

Web Apps

Content

Aggregators

Web crawler Yes Y Y Y Y

Email crawler Yes Y Y Y Y

File crawler Yes Y Y Y Y

Database crawler Yes Y Y Y

Adapter for Online Feeds (RSS, Atom) WIP Y Y Y Y Y

Adapter for Twitter Yes Y Y Y Y Y

Adapater for Facebook Yes Y Y Y Y Y

Adapter for LinkedIn Yes Y Y Y Y

Semantic Net Editor Yes Y Y Y Y Y Y

Ontology Editor Yes Y Y Y Y Y Y

Semantic Rule Editor Yes Y Y Y Y Y Y

Ontology storage (RDBMS) Yes Y Y Y Y Y

Semantic Net Storage (RDBMS, XML) Yes Y Y Y Y Y

Semantic Net based classification Yes Y Y Y Y Y

Bayes Naïve Classifier Yes Y Y Y

Ontology Inference Engine (support for

OWL 1.0)

Yes Y Y Y Y

Semantic Matching (Semantic Net) Yes Y Y Y

Semantic Browsing Yes Y Y Y Y

Latent Semantic Indexing Yes Y Y

Semantic Net API Yes Y Y Y

OWL API Yes Y Y Y Y

Preprocessing - Identification of

paragraphs and sentences

Yes Y Y Y Y Y Y Y

Preprocessing - Identification of POS Yes Y Y Y Y Y Y Y

Preprocessing - Identification of term Yes Y Y Y Y Y Y Y

Preprocessing - Word Stemming Yes Y Y Y Y Y Y Y

Preprocessing - Removal of stopwords Yes Y Y Y Y Y Y Y

Weighting schemes for terms Yes Y Y Y Y Y Y Y

Named Entity Recognition and

Relationships (NLP based)

WIP Y Y Y Y Y Y Y

Named Entity Recognition (Visual

Segregation)

Yes Y Y Y Y Y Y Y

Phrase Identification Yes Y Y Y Y Y Y Y

Sentiment Analysis WIP Y Y Y

Semantic Storage

of Content

Semantic

Organization of

Content

Semantic

Retrieval

Semantic

understanding of

content and

natural language

query

Content

Aggregators

Semantic

Network /

Ontology

• Configurable to any Business requirement across Industries

• Sources of content can be structured AND Unstructured

7

• Can be integrated to various Business Applications - ERP, Content Management, Portals, etc.

• Configurable User Interface with features such as:

– Saving of Search for later reference

– Tabbed Views

– No. of results to be displayed with sort order

Veda Solutions Currently Deployed Veda for Business Process Workflow

8

Veda Social Media Analytics

Registration & log in

Inputs from Social Media

Inputs from Blogs, Websites

Heirarchy & Relevance Analysis

Sentiment Analysis

Rich Reporting

Veda Solutions Currently Deployed

9

Veda Recruiter


10

Veda Patent Search

Registration & log in

Subscription

Payment Gateway

Keyword Search

Semantic Search

Rich Internet Application

Saved Search

Filters


Industry Examples of Applicability of Veda

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• Healthcare: Patient Treatment Process using

• Patient’s past records

• Recent treatment of similar ailments across the Hospital / State / Country, etc.

• Medical Research information available in the Internet

• Professionals: Tax / Legal / Patent Filing using

• Case Laws, Guidelines, Notifications

• Statutory Records, Past Filings

Industry Examples of Applicability of Veda

12

• Manufacturing: Purchase Process using

• Past Purchase documents

• Material documents / brochures

• Live Pricing information from websites of Suppliers, Exchanges, e-Commerce sites

• Human Relations: Recruitment / Appraisal Process using

• Past Employee Records

• Profiles from Social Networking sites

• Recent performance data

1. One of the few Semantic Product Companies

worldwide that has an end-to-end technology

coverage

2. One of the few Semantic companies worldwide

adopting a Business Application centric view

3. One of the few Semantic Organizations with a

strong in-house Implementation Team

4. Ability to provide different Commercial Models

based on Customer requirements

13

Key Differentiators

Thank You

Anand Ramakrishnan

President – Sales and Marketing

eMudhra Consumer Services Limited

[email protected]

+91 9900541568

mailto:[email protected]

mailto:[email protected]