Intelligent Information Expert System for Employment and General Purposed Fuzzy Shell

2 Technological centre: Solware Information Technology Ltd. Tasks: coordinator project leader software development Knowledge centre: Budapest University of Technology and Economics, Department of Telecommunication and Telematics Tasks: fuzzy algorithms aggregation - general searching-offering system - general fuzzy shell Members of the Consortium

3 Project goals Background - expert systems - fuzzy definitions - fuzzy rule-based expert systems (fuzzy shell) - comparison Project - fuzzy based searching-offering systems - employment expert system accomplishment with modern IT methods design, optimisation system parameters Conclusions Agenda

4 Goal: Development of a specific and a general purposed fuzzy rule-based expert system Two steps: 1. Development of a fuzzy-based searching-offering system 2. Development of a general purposed fuzzy-shell Mile stones: a. Fuzzy-based searching-offering subsystem b. Job searching subsystem c. Applicant searching subsystem d. Fuzzy shell e. Optimisation the parameters of employment (job and applicant searching) f. Design fuzzy-shell demo program Goal Project Goals, Tasks

5 Knowledge base Antecedence Consequence Conclusion Character of the knowledge base: The rules are applied to crisp values and intervals Difficulties: very large knowledge base, too many rules the uncertainties are handled not efficiently inflexible system: no applicable rule no result Backgr. Expert Systems

6 Fuzzy set A is a set on the X universe, Fuzzy set: belongs to the given A set so that the measure of this membership is not 1 or 0 (x belongs to A or not) but a value between the two Membership function The measure of the belonging Fuzzy logic Generalisation of the two-valued Boole type logic income (USD) Backgr USD A=more then 3000 USD Fuzzy Definitions

7 ObservationCrisp output Rule-base Backgr. Fuzzyfication unit Defuzzyfication unit Inference engine Inference Algorithm i.e. Mamdani Sugeno, etc.. IfIfThen Fuzzy Rule-Based Expert Systems (Fuzzy Shell)

8 Advantage over the classical expert systems: less rule decrease computational complexity c = decreasing factor against symbolical expert systems good handling the uncertainties robust system (overlapping rules) Disadvantage: decreasing accuracy Applications have great perspectives on the areas where the uncertainty is large and not needed very accurate result Additional new components comparing to other (fuzzy) expert systems: build in interpolative methods hierarchical systems Backgr. Comparison

9 Problems by finding the partners each other: - in discrete case: search offeroffer Similarity matrix Project 1 0 OfferSearch 0.45 A solution: using fuzzy sets - in continuos case: uncertainties: the searching partner doesn’t know exactly what he/she wants weight of viewpoints are differences and can be changing during the process Fuzzy Based Searching-Offering Systems

10 Variables were chosen and structured by professional employment experts Typical variable groups - income (salary and other) - personal skills (education, language etc.) - workplace information (distance, firm size) More problematical case were handled: - distance: - taking into account the infrastructure the system able to calculate the distance in time - branches: - all the branches are covered by similarity matrix - weight: - the weights of the variables can be iterated after the analysis of the output Project Employment Expert System

11 Algorithms - user surface on web and windows environment - SQL database - XML, MTS applications Project Job searching user surface Employment agency surface Job offering user surface User surfaces Database Application logic Fuzzy system Accomplishment

12 Architecture of Employment Expert System Project Internet client Web server Application server XML configuration files SQL data base

13 optimisation on real data the learning algorithm is a type of evolutionary algorithm: bacterial algorithm Optimisation with learning methods Check the results on test set Project Default parameters (employment experts) Choose the parameters for optimisation Design, Optimisation of System Parameters

14 Summa The method - Advantages and disadvantages of fuzzy-based expert systems - Motivation of using fuzzy methods Until now General searching-offering system right now: Job searching subsystem Future - Applicant searching subsystem - General purposes fuzzy shell Conclusions