jcolibri CBR Framework

Transcription

1 jcolibri Framework Juan A. Recio-García Group for Artificial Intelligence Applications Department of Software Engineering and Artificial Intelligence Universidad Complutense de Madrid Motivation problem new case is: learnt case previous cases retrieved case new case Successful AI subfield Mature & established repaired case confirmed solution Background Knowledge solved case suggested solution Building applications requires: Formalization Methodologies Implementation assistance 1

2 jcolibri2 Platform for developing applications Motivation Platform = Reference Architecture + Imple 2

3 Motivation Main features of jcolibri Extensible Reusable Different types of users and different purposes: Development, Research and/or Teaching Compatible with commercial applications and suitable for developing large scale applications Supporting different types of systems It is just a.jar file Suitable for web applications More than downloads Statistics visits to the web page in the last year Visits from ~100 countries 3

4 Academic & Commercial World Usage Many Universities using jcolibri for teaching or research purposes Université Pierre et Marie Curie (Paris, France) Georgia Institute of Technology (Georgia, USA) Indian Institute of Technology (Chennai, India) The Robert Gordon University (Aberdeen, United Kingdom) University College Cork (Cork, Ireland) Commercial Applications KOBAS: knowledge management system (Romania) Research Projects Intelligence system for failure diagnostics in trains (Portugal) European Project ONE (IST ) External Contributions Collaborations 4

5 Where to start? Installation 5

6 Examples More Examples 6

7 My first application with jcolibri Tutorial shows -step by step- how to build a travel advisor system Import jcolibri2 in Eclipse Just follow the steps described in the tutorial 7

8 Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems 8

9 Application Structure Cases & Persistance Cases representation: Java Beans Direct & simple representation Easy programming and debugging Automatic generation of GUI Compatibility with Web Interfaces Cases persistence: Connectors 9

10 Methods 5 Retrieval Strategies 7 Selection methods 30 Similarity Measures: Texts, Ontologies, my Parameter adjustment Transformation by local search Constructive reuse Retrieve Reuse Retain Maintenance algorithms: BBNR, CRR, RENN, RC, ICF, Revise User-Based Revision Preference elicitation Other Features Visualization of case bases Evaluation: N-fold, Leave-one-out, 10

11 How to continue Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems 11

12 Recommender systems: Example Cases Items Recommender Systems in jcolibri jcolibri provides 3 main templates to build recommender systems Can be instantiated into more than 20 different recommenders: Single-shot, Navigation by Asking, Navigation by Proposing, Collaborative, 15 different recommenders included as examples RecSys 08 12

13 Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems Distributed Systems: Example D 2 ISCO: Deliberative, Distributed and Collaborative System for Music recommendation case base A new pop song? case base case base ICCCI 09 case base case base 13

14 Distributed systems in jcolibri ALADIN: Abstract LAyer for DIstributed INfrastructures Main interfaces required to build (almost) any distributed system. Follows the IEEE FIPA standard for distributed systems. Can be implemented using different technologies: Sockets, JADE, SALADIN: Sockets based implementation of ALADIN Completely functional implementation of the ALADIN architecture Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems 14

15 Textual : examples Textual : Semantic methods Follow the Lenz layered model and includes two implementations that use OpenNLP and GATE IC 05 15

16 Textual : Statistical methods Good results in complex domains where the knowledge required to extract the information is not available T Workshop Challenge: Air Investigation Reports Statistical T Application: Guided Adaptation 16

17 Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems Data Intensive : example Textual application using texts from journals documents / 20 categories Huge case bases with uncertain/incomplete cases 17

18 Retrieval from a clustered case base Use a clustering method to organize the case base Extensions Textual Knowledge Intensive Distributed Data Intensive Recommender Systems 18

19 Knowledge Intensive applications Complement the knowledge required by applications by means of ontologies Knowledge Intensive Example Tale generator 19

20 jcolibri2 Needs graphical tools COLIBRI Studio Complete Graphical Development Environment for applications GUI for jcolibri2 integrated into Eclipse IDE 20

21 Easy compilation and execution COLIBRI Studio Case Structure Project Management Graphical composition of methods Case base organization Automatic source code generation Connector (Available in September) COLIBRI Studio 21

22 Wizard Easy to follow wizard to configure the basic building blocks of applications Graphical configuration of the system through templates. COLIBRI Studio Templates are abstract representations of common applications that can be customized. COLIBRI Studio will provide templates for standard systems, Textual applications and recommenders. for : A Case- Based Template Recommender System for Building Case-Based System. EC08, 2008 Semantic Templates for Case-Based Reasoning Systems (2009), in: The Knowledge Engineering Review, 24:Special Issue 03,

23 Graphical configuration of the system through templates. COLIBRI Studio Templates are abstract representations of common applications that can be customized. COLIBRI Studio will provide templates for standard systems, Textual applications and recommenders. for : A Case- Based Template Recommender System for Building Case-Based System. EC08, 2008 Semantic Templates for Case-Based Reasoning Systems (2009), in: The Knowledge Engineering Review, 24:Special Issue 03, 2009 COLIBRI Studio Coming soon at 23

24 Questions? Juan A. Recio-García 24