Discovery

Abstract
[IN2]Discovery is an integrated semantic search solution that enables to change the huge amount of information internally scattered in an organization to knowledge through a sharp observation, reorganization and analysis from various angles, and to re-utilize as knowledge asset of an organization through discovery of hidden issues and values.

[IN2]Discovery, as a new paradigm of integrated search beyond the general search, is an enterprise information analysis platform with high scalability that enables discovery of critical insight through intellectual text analytics of a huge quantitative structured and unstructured data and information such as call center log, blog and e-mails in a company or an organization.

[IN2]Discovery means a strong combination of business intelligence applied to search platform through integration and control of all the information needed for business intelligence solution, and will be resulted in better decision making through enabling 360 degree view on employees, customers, partners and external point of view and ROI improvement over the investment.

Distinctive Features

Innovativeness
1. Analysis of 85% stored structured and unstructured enterprise document and intellectualization.
2. Suggestion of analysed information of related information, tendency and related personnel.
3. Highly reliable analysis quality by proven technology

Functionality
1. Automatic clustering, classification and information search of big quantity contents
2. Relationship and trend analysis through semantic mining
3. Knowledge network analysis, semantic search and visualization

Convenience
1. Application of intellectual distribution computing and grid technology
2. Existing search engine may be used
3. May be interlinked with business intelligence and data mining system

Key Functions
Integrated Search
Integrated search of web, wiki/blog, home page and e-mail
Synonym search

Structural Search Results and User Interface Browsing
Automatic classification
Automatic clustering & visualization
Faceted navigation
Dynamic selection
-Integrated/Intuitive Graphical reporting
-Search and multi-analysis and reporting on Structured/Unstructured data search
Pattern learning
Trends analysis
Link analysis
Association analysis
Entity extraction
TopicRank based relationship analysis
-Automatic creation of semantic meta data
-Semantically related information search and analysis
-Reasoning based strong alert and personalization
User behavior based machine-learning
Role-based search
Dynamic Ranking
Social Search
-Social network Analysis external information linkage
-High grade managerial function
Integrated setting and management
Ranking model and weight value management
Preliminary management
Excellent statistics and reporting
-Strong security/Privacy and standard framework support
-Customization) and excellent scalability
-Super quantitative distribution search engine built-in

System structure
(To be updated)

Introduction Effect
-Search of structured and unstructured data contents and all round knowledge information analysis through semantic mining
-Discovery of hidden information which is impossible by concept based and keyword search and understanding of semantic relationship
-Supporting of decision making through enabling the valuable information search by knowledge discovery beyond the information search
-Integrated analysis of internal and external information such as market and competitor trends through linkage to OWLIM
-Intuitive information recognition through strong visualization