iKen Studio

1
An IIT Bombay Research Project Spin-off
2
iKen Studio Live

• A SaaS (Software as Service) Delivery Platform
  (www.iKenStudio.com)
• An online development environment to develop
  web-based enterprise applications, decision
  support systems, knowledge-based websites and BI
  (Business Intelligence) applications backed by
  expert system, case-based reasoning and Hybrid AI
  technologies.
• It is a research spin-off of IIT Bombay

3
Contents

• iKen Studio Features
• Generic Applications of iKen Studio
• System Development Interfaces
• Core Engines
• Presentation Interfaces
• Database Management Interfaces
• System Parameters and configuration
• System Controls
• Comparing iKen Studio with other Expert
  System/CBR Tools/Shells
• Business Intelligence using iKen Studio
• iKen Studio Projects
• iKen Studio Web Services
• Accessing iKen Studio and Apps
• Case Studies and Demos

4
iKen Studio Core Engine and Interfaces
5
iKen Studio Features

• Completely Web-based
• Access, management and configuration through Web
• No desktop installation and management
• Minimal coding
• Generate automatic DHTML scripts and HTML web
  pages
• No explicit database programming required
• Various development interfaces
• Use of simple language for writing rules
• Support large number of operators, functions and
  data types
• Existing C/C APIs can be used
• Database integration
• Support popular databases MS-SQL Server, MYSQL,
  MS-Access, Excel, Text, etc.
• Simultaneously connects and accesses data from
  multiple databases
• In-built extraction, mapping and transformation
  engine
• Data access and manipulation through flexible
  external dynamic queries

6
iKen Studio Features

• XML and Web services
• All components and interfaces use XML
• SQL-XML and XML-SQL transformation
• Access to APIs and intelligent systems through
  web services
• AI Techniques
• Powerful expert system engine supporting large
  number of data types including matrix, trend, XML
  etc. and various SQL, matrix, list, chart,
  session management, report etc. functions
• Use of scripting language for implementing
  procedural logic
• Powerful CBR engine supporting structured and
  conversational CBR applications
• Applications can be developed using hybrids of
  expert system and CBR
• Security features
• Role-based access to various development
  interfaces
• Role and user based access to applications,
  databases and data
• Encryption to prevent unauthorised changes
• System tracks changes made by the users and save
  change history for later investigation

7
Generic Applications using iKen Studio
8
Generic ApplicationsKnowledge Automation

• Manage dynamic business rule
• Retain and reuse in-house expertise
• Maintain and assure regulatory compliance
• Enforce decision rules make them consistent and
  objective
• Make transaction and reporting systems
  intelligent by incorporating knowledge

9
Generic ApplicationsKnowledge-based Websites and
Intranets

• Move from information delivery to knowledge
  delivery
• Automate and deliver expertise on-line virtual
  consultant
• Save experts time and serve large user/customer
  base 24x7 days
• Understand user, customers and employees well.
  Recommend them the right products, deliver
  customized advice and information
• Lightweight, less crowded user interfaces
• Intelligent product advisory and selection
• Smart Intranets

10
Generic Applications Decision Support

• Advanced decision support system using
  rule-based, case-based systems and analytical
  methods
• Data Analysis, detect Inconsistencies
• Reuse experience like dealing with customers
• Analyse, match profiles and predict behaviour
• Identify up-selling and cross-selling
  opportunities

11
Generic Applications Automated Help-desks and
Support

• Reuse maintenance, support etc. experience
• Self-service Interfaces
• Intelligent help and troubleshooting

12
Generic Applications Monitoring and Reporting

• Monitor and report fraudulent, suspicious and
  abnormal activities
• Generate alerts and early warning signals

13
Generic ApplicationsInformation Search and
Retrieval

• Flexible and guided quick information retrieval
  from databases
• Set individuals retrieval criteria and
  requirements
• Retrieval based on context and conceptual
  similarity

14
Applications Demo ScreenshotsProduct Selectors
15
Applications ScreenshotsAdvisory Applications
16
Applications ScreenshotsAdvisory Apps
17
Applications ScreenshotsIntelligent Exams
18
Applications ScreenshotsIntelligent Matching
19
Applications ScreenshotsDecision Support
20
Applications ScreenshotsMonitoring
21
Applications ScreenshotsKnowledge Automation
22
Applications ScreenshotsPersonalization
23
iKen StudioLayered Architecture
iKen Studio
24
System Development Interfaces
25
Core Engines Expert System Engine (Rule Engine)

• Rule-based Reasoning
• Web-based, XML-based Expert Systems can easily be
  developed and deployed.
• Easy to use and understand IF...THEN...ELSE rule
  format
• Supports rules for multiple expert systems, which
  are logically separated into application groups.
• Rules are stored in intermediate format at run
  time rather than interpreted each time. Rules
  are checked for various syntax and semantic
  errors. Rule Manager facilitates interactive
  environment to manage the rules.
• Supports
• Backward as well as forward reasoning
• Various data types number, real, text, date,
  list, dynamic list, trend, matrix, boolean,
  document, URL, etc
• Various mathematical, string, list, date, matrix,
  trend, graph, database, session management and
  report functions.
• Special operators and functions like INCLUDE, IS
  BETTER THAN, SCORE_OF, PROFILE_OF etc. to reduce
  number of explicit rules eg expressions like
• Customer.Education IS BETTER THAN Diploma,
• STATUS_OF Customer.Age IS Young
• Customer.Income Documents INCLUDE PAN,Form16
  etc.

26
Core Engines Expert System Engine (Rule Engine)

• User defined functions can be created to be
  invoked in expert system rules
• Supports many databases simultaneously, no
  explicit database programming is required like
  opening database connections, executing SQL
  command, opening record-sets, populating data
  etc. The database interfaces manage extraction,
  mapping and transformation of data. The data in
  response to SQL queries is populated into session
  data and vise-a-versa at run time.
• Use of JavaScript for WHEN NEEDED and WHEN ADDED
  methods. Expert system variables can directly be
  accessed directly in JavaScript for client-side
  as well as server-side functionality. This helps
  to implement procedural component to be
  implemented using scripting languages that are
  relatively easier and widely used.
• System can run in Debug mode to dump the data and
  know process status at run-time.
• An expert system can be invoked through URL and
  Web services
• System Interfaces like Form Designer and Report
  Designers are used to create HTML input templates
  and sessions reports to enter, validate data and
  get formatted output in HTML format.
• Existing C/C APIs can be used by wrapping them
  in DLL files
• Expert system engine can work as host system for
  accessing and controlling case-based reasoning
  systems or to develop hybrid systems

27
Core Engines Case based reasoning engine

• Domain independent Web-based CBR systems can be
  developed. The engine is tightly connected to
  expert system engine. Expert system engine can
  act as host. Expert system can be used to enter
  query or problem case (through QA or Forms).
  Run-time format of case format is XML, cases are
  stored in the database/s.
• No restructuring of database contents, existing
  contents can easily used and converted to cases
  on the fly (by mapping SQL-XML)
• Supports for all phases (Retrieve, Reuse, Revise
  and Retain) of CBR
• Uses combination of rule-base, SQL and nearest
  neighbour method for retrieval.
• Powerful rule-based engine for adaptation of
  cases.
• It can address structural as well as
  conversational CBR thereby supporting wide-range
  of applications from intelligent help desk to
  complex decision support.
• The engine supports taxonomy, hierarchy of CBRs
  and logical grouping of features.
• It supports large number of similarity functions
  and custom functions can be added.
• It can be configured to set similarities from
  databases based on criteria or procedural logic
  (query results), also to learn and adjust
  similarities automatically from the past
  transactions or examples.

28
Presentation Interfaces Form and Report Designer

• Create DHTML web pages for Input and Output
• Support all major HTML controls, tags, fonts,
  colors etc
• JavaScript code is automatically inserted into
  forms and reports for validation, formatting etc.
• Form designer interface used for designing and
  building inputs forms
• Report designer interface used for designing and
  building report templates. The system populates
  and calculates appropriate values at run-time
  when invoked or displayed.
• Studio supports default report templates with lot
  of client side functionality and navigation aids
• Support two basic types of reports
• Session Report to display session data at
  run-time
• Query Report to display dataset in multiple rows
  e.g. result of SQL query

29
Presentation Interfaces Example Form Preview
30
Presentation Interfaces Example Runtime Form
31
Presentation Interfaces Example Session Report
Preview
32
Presentation Interfaces Example Runtime Session
Report
33
Presentation Interfaces Example Default Reports
34
Domain VocabularyGlobal Variables, Menus, Range
Conversions and Lookup Table

• It facilitates to maintain global dictionary of
  domain terms (parameters/variables and their
  descriptions)
• These variables are used in various intelligent
  systems like in expert system, forms, reports,
  etc.
• Supports various variable types based on usage in
  the system
• Interface facilitates to enter detailed variable
  description like HTML formatting, validation
  criteria, WHEN NEEDED and WHEN ADDED scripts,
  linked intelligent systems and so on. Web pages
  are automatically for input type variables based
  on HTML formatting parameters selected.
• Various data types are supported
• Menu objects hold the information about various
  possible options (list of values) a variable can
  take.
• Symbolic values and numeric values (including)
  can be converted into numeric and qualitative
  respectively using range-list objects. These can
  be used to transform values. It helps to reduce
  the writing of explicit rules to convert values
  at run-time in expert system.
• Lookup table interface is used store table of
  values in memory at run-time instead of fetching
  them from database each time. Especially if
  taxonomy or abstract features for generalization
  is to be stored in memory instead fetching them
  each time from databases. e.g. to fetch Education
  Level, Education Discipline, etc. from Degree.

35
Data ServicesDatabase Connection

• This interface is used for setting up database
  connections. It can also be used to add, remove,
  and update database connections.
• The system maintains the list of database
  connections as an application object. Each
  connection has a logical ID
• Supports databases SQL Server, Oracle,
  MS-Access, MS-Excel, MySQL, Text Files etc.
• System supports OLEDB or ODBC connection type
• One of the databases (core db) in the system is
  treated as core database. The core database is
  used by the system to store the user list,
  session tracking, database access queries etc.

36
Data ServicesDynamic Queries

• Dynamic query facilitates retrieval of data at
  run-time by just using their IDs and filters (by
  populating filter values at run-time)
• Queries can be predefined to bring datasets for
  lists, dynamic lists, collaborative filtering,
  content filtering, clustering etc.
• These queries save lot of explicit coding inside
  Rule-base.

37
Data ServicesDatabase Variable Linking

• Mapping between variables and database fields can
  be set to exchange the data between database and
  system.
• Data can be transformed on the fly after
  retrieval and before updates to database/s.
• Mapping can be set for read or update access.
• Variable linking can be done for fields from
  different databases.
• Mapping and transformation is applied to all
  queries sent to database/s.
• It helps to populate data into variables
  automatically and vice-a-versa without explicit
  data population in rule etc.
• Because of mapping, cursors can be simulated and
  used in expert system coding

38
Data ServicesDatabase Access Configuration

• Query objects hold the information about database
  links to various components of the systems.
  Database access can not be done unless query
  objects are defined.
• Query object can have multiple queries with
  respect to role, goal, intelligent system, etc.
• Access to data can be controlled based role,
  application, read or write, etc.

39
Data Services SQL-XML Mapping and Transformation
Engine

• Responses from SQL calls are converted into XML
  and XML data is converted to SQL requests
• Fields are mapped to variables and data is
  transformed at the time of retrieval from
  database/s and vice-a-versa.
• Engine can fetch data from multiple databases or
  update to many databases simultaneously.
• Various access rights can be set to access data
  based on user, role as well as type of
  intelligent system accessing data.
• Frequently required data can be stored in look-up
  tables, this data is populated in every record
  based in key-field value return from the SQL call
  
• Table data can be converted into multi-valued
  fields for analysis through option of child query.

40
Data ServicesSQL-Builder and Rule Filter

• A SQL interface to build SQL queries
  interactively
• Data from multiple queries can be in integrated
  or merged from different databases
• Data retrieved from queries further filtered
  using logical rules involving complex criteria
  making it database independent. Large number of
  date, string, trend analysis, list, math
  functions available to be included in rule filter
• Filters are saved with logical names

41
Data Services Example Rule Filter
42
System Interfaces Load Application and File
Upload

• Interface to load required applications in the
  project
• Backup and restoration of selected applications
  at client location
• Shows application load status and errors while
  loading and building applications
• Files can be uploaded to server from client
  location

43
System Interfaces Access Rights and Roles

• Access rights to roles, users can be defined.
• It allows to set different options to roles. Each
  role includes access to system interfaces,
  applications, databases and variable groups.
• An user can have multiple roles

44
System Interfaces System Parameters
Configuration

• Various project level parameters can be set which
  are applicable to all applications in that
  project
• Applications and linked variable groups can be
  defined with some applications can be loaded as
  default applications when iKen Studio starts
• These include parameters for connecting to SMTP
  server, use navigation button names, virtual
  directory path, script files path, default
  formats, max number of rules, max number of
  tokens in expression etc.

45
iKen Studio Project
46
iKen Studio Project Example
47
iKen StudioGeneric Solution Architecture
48
iKen Studio Web-Services

• Web Services are designed to
• access iKen Studio components, applications and
  live sessions
• configure iKen Studio projects at run-time
• synchronize data transfer between external
  applications and iKen Studio application
  databases
• All of the objects of application such as expert
  systems, CBRs, rule-filters, user-defined
  functions, session, databases are accessed using
  unique ID. Which helps to implement business
  logic in iKen Studio and executing functionality
  just using object ID and data in XML format and
  limited number of webs services.
• Supports XML and text data transfers
• External parameters can be mapped to iKen Studio
  application variables to facilitate data exchange
  between external applications and iKen Studio
  applications

49
iKen Studio App and Web Services
External App
External App
External App
iKen Studio Web Services (accessing objects
through their IDs)
Databases
Databases
Project Objects (External App Paramslt-gtiKen
Studio App Var Mapping) Expert Systems, CBRs,
UDFS, Session, Rule Filters, Databases
Models Config.Files
Databases
iKen Studio Core Framework
50
Web Services Examples
51
Accessing iKen Studio and Apps
52
Accessing Web Services Adaptive Framework using
iKen Studio
Web Service UDF_ExecuteWithList
List of function parameters and values
iKen Studio Web Services
Notifying download
http//www.iKenStudio.com/iKenStudio.asmx/UDF_Exec
uteUsingList?P_FunctionIDMovieMart.AddTransaction
p_ArgumentList1,21925,212,B,Sanjay20Dutt,KY
seq. U_ID,C_ID,H_ID,D_Type,Keyword,Key_Type
returns status OK1
Name of Internal UDF defined in iKen Studio
List of values passed to UDF MovieMart.AddTransact
ion
Generating Global User Profile
http//www.iKenStudio.com/iKenStudio.asmx/UDF_Exec
uteUsingList?p_FunctionIDMovieMart.GenerateGlobal
UserProfilep_ArgumentList1
returns status OK1
Generating Local User Profile
http//www.iKenStudio.com/iKenStudio.asmx/UDF_Exec
uteUsingList?p_FunctionIDMovieMart.GenerateUserPr
ofilep_ArgumentList1,212
returns status OK1
Calculating Best Recommended
WebService ExpertSystem_RunWithDatap_GoalVariable
MovieMart.iPushGoalp_xmlDataltCasegtltCDgtltNgtMovieM
art.Actionlt/NgtltVgtNextPushlt/Vgtlt/CDgtltCDgtltNgtMovieMart
.User_IDlt/NgtltVgt1lt/Vgtlt/CDgtlt/Casegtp_OutputVariableL
istMovieMart.NextPushCID_HID,SystemInterface.Sol
ution_Matching
ltstringgtltCase No"1"gtltCDgtltNgtMovieMart.NextPushCID_
HIDlt/NgtltVgt 22298212,23424212,24696212,2498821
2,24348212,24362140,24157212,22490212,2339921
2,24685212,22027212,23583212,24008212,2447721
2,24943212,22083140,22233140,22501140,2458214
0,24691212lt/Vgtlt/CDgtltCDgtltNgtSystemInterface.Soluti
on_Matchinglt/NgtltVgt64.29 64.29 64.29 64.29 59.04
56.78 56.38 55.6 55.2 55.2 54.83 54.83 54.83
54.83 54.83 54.8 54.8 54.8 54.8 54.6 54.3 53.85
53.55 53.08 53.08 53.08 52.55 52.33 52.33
lt/Vgtlt/CDgtlt/Casegtlt/stringgt
53
Case studies demonstrating iKen Studio
capabilities and integration models
54
Accessing iKen Studioe.g. iKen Studio App
embedded in portal
55
Comparing with other Expert System Tools/Shells
56
Comparing with other Expert System Tools/Shells
57
Comparing with other CBR Tools/Shells
58
Business Intelligence Using iKen Studio

• Effective and powerful combination of human
  intelligence (business rules and logic through
  rule-based expert systems and filters) and domain
  knowledge-aided machine intelligence (content
  filtering, intelligent matching, knowledge-based
  clustering and collaborative filtering using CBR
  technology)
• On-the-fly intelligence using lazy learning
• Self-learning and adaptive intelligence
• Intelligence can be programmed, customized and
  configured. It can integrated into existing
  operational systems using web services or APIs.
• No need to restructure existing database for BI
  applications
• Can be programmed to support micro-level
  intelligence (what an individual user or customer
  does, likes etc.) and macro-level intelligence
  (what specific group of users or customers do,
  like etc.)
• Can address classification, clustering,
  associations and sequence problems effectively
• KM and decision support components can be
  implemented

Client Browser
Client Browser
Client Browser
BI Applications
Domain Knowledge, Rule-Filters, Rules (business,
decision support and customization) and Models
Data retrieval, mapping and transformation
(on-the-fly)
Database
Database
Database
59
For Case Studies and Demo Applications

• Log-on
• To
• www.ikenstudio.com

60

• Thanks