Simplification of rules extracted from neural networks

Artificial neural networks (ANNs) have been proven to be successful general machine learning techniques for, amongst others, pattern recognition and classification. Realworld problems in agriculture (soybean, tea), medicine (cancer, cardiology, mammograms) and finance (credit rating, stock market) are successfully solved using ANNs. ANNs model biological neural systems. A biological neural system consists of neurons interconnected through neural synapses. These neurons serve as information processing units. Synapses carrt information to the neurons, which then processes or responds to the data by sending a signal to the next level of neurons. Information is strengthened or lessened according to the sign ..and magnitude of the weight associated with the connection. An ANN consists of cell-like entities called units (also called artificial neurons) and weighted connections between these units referred to as links. ANNs can be viewed as a directed graph with weighted connections. An unit belongs to one of three groups: input, hidden or output. Input units receive the initial training patterns, which consist of input attributes and the associated target attributes, from the environment. Hidden units do not interact with the environment whereas output units presents the results to the environment. Hidden and output units compute an output ai which is a function f of the sum of its input weights w; multiplied by the output x; of the units j in the preceding layer, together with a bias term fh that acts as a threshold for the unit. The output ai for unit i with n input units is calculated as ai = f("f:,'J= 1 x;w; - 8i ). Training of the ANN is done by adapting the weight values for each unit via a gradient search. Given a set of input-target pairs, the ANN learns the functional relationship between the input and the target. A serious drawback of the neural network approach is the difficulty to determine why a particular conclusion was reached. This is due to the inherit 'black box' nature of the neural network approach. Neural networks rely on 'raw' training data to learn the relationships between the initial inputs and target outputs. Knowledge is encoded in a set of numeric weights and biases. Although this data driven aspect of neural network allows easy adjustments when change of environment or events occur, it is difficult to interpret numeric weights, making it difficult for humans to understand. Concepts represent by symbolic learning algorithms are intuitive and therefore easily understood by humans [Wnek 1994). One approach to understanding the representations formed by neural networks is to extract such symbolic rules from networks. Over the last few years, a number of rule extraction methods have been reported (Craven 1993, Fu 1994). There are some general assumptions that these algorithms adhere to. The first assumption that most rule extraction algorithms make, is that non-input units are either maximally active (activation near 1) or inactive (activation near 0). This Boolean valued activation is approximated by using the standard logistic activation function /(z) = 1/( 1 + e-•z ) and setting s 5.0. The use of the above function parameters guarantees that non-input units always have non-negative activations in the range [0,1). The second underlying premise of rule extraction is that each hidden and output unit implements a symbolic rule. The concept associated with each unit is the consequent of the rule, and certain subsets of the input units represent the antecedent of the rule. Rule extraction algorithms search for those combinations of input values to a particular hidden or output unit that results in it having an optimal (near-one) activation. Here, rule extraction methods exploit a very basic principle of biological neural networks. That is, if the sum of its weighted inputs exceeds a certain threshold, then the biological neuron fires [Fu 1994). This condition is satisfied when the sum of the weighted inputs exceeds the bias, where (E'Jiz,=::l w; > 9i)• It has been shown that most concepts described by humans usally can be expressed as production rules in disjunctive normal form (DNF) notation. Rules expressed in this notation are therefore highly comprehensible and intuitive. In addition, the number of production rules may be reduced and the structure thereof simplified by using propositional logic. A method that extracts production rules in DNF is presented [Viktor 1995). The basic idea of the method is the use of equivalence classes. Similarly weighted links are grouped into a cluster, the assumption being that individual weights do not have unique importance. Clustering considerably reduces the combinatorics of the method as opposed to previously reported approaches. Since the rules are in a logically manipulatable form, significant simplifications in the structure thereof can be obtained, yielding a highly reduced and comprehensible set of rules. Experimental results have shown that the accuracy of the extracted rules compare favourably with the CN2 [Clark 1989] and C4.5 [Quinlan 1993] symbolic rule extraction methods. The extracted rules are highly comprehensible and similar to those extracted by traditional symfiolic methods

An analysis of the use of graphics for information retrieval

Several research groups have addressed the problem of retrieving vector graphics. This work has, however, focused either on domain-dependent areas or was based on very simple graphics languages. Here we take a fresh look at the issue of graphics retrieval in general and in particular at the tasks which retrieval systems must support. The paper presents a series of case studies which explored the needs of professionals in the hope that these needs can help direct future graphics IR research. Suggested modelling techniques for some of the graphic collections are also presented

Policy Conflict Analysis in Distributed System Management

Accepted versio

Building the Semantic Web of Things Through a Dynamic Ontology

The Web of Things (WoT) recently appeared as the latest evolution of the Internet of Things and, as the name suggests, requires that devices interoperate through the Internet using Web protocols and standards. Currently, only a few theoretical approaches have been presented by researchers and industry, to fight the fragmentation of the IoT world through the adoption of semantics. This further evolution is known as Semantic WoT and relies on a WoT implementation crafted on the technologies proposed by the Semantic Web stack. This article presents a working implementation of the WoT declined in its Semantic flavor through the adoption of a shared ontology for describing devices. In addition to that, the ontology includes patterns for dynamic interactions between devices, and therefore we define it as dynamic ontology. A practical example will give a proof of concept and overall evaluation, showing how the dynamic setup proposed can foster interoperability at information level allowing on the one hand smart discovery, enabling on the other hand orchestration and automatic interaction through the semantic information available

Curriculum integration as treaty praxis.

The article discusses the significance of curriculum integration on the promotion of principles of the Treaty of Waitangi, an agreement signed in 1840 by the Maori and the Crown people in New Zealand. It explores the challenges linked with this curriculum theory design. It also highlights a case study which analyzes the impact of curriculum integration in education

Katalog metapodataka u prostornim informacijskim sustavima

This paper gives the short review of the Open Geospatial Consortium (OGC) metadata catalogue services that have the key role in geospatial resource discovery in Spatial Data Infrastructures (SDI). The notion of Spatial Data Infrastructure comprises a collection of technologies, policies and institutional agreements that provide an easier access to geospatial data. The SDI is suitable for usage in geospatial data discovery, evaluation, and also various applications within government, commercial and non-profit sectors, academic institutions, etc. Metadata catalogue services have been specified in OGC Catalogue Service Implementation Specification. The part of the specification that specifies a web interface that supports the storage, retrieval, and management of data related to web services, is called Catalogue Service for the Web (CSW). Metadata catalogues are service brokers that represent a key component in a service-oriented architecture that manages shared resources and facilitates the discovery of resources within an open, distributed system. OGC services have gained significant popularity in recent years and the number of organizations using them has increased. However, the full potential of metadata catalogues has not yet been reached, not only because of the lack of appropriate documentation of data in the form of standardized metadata, but because the lack of semantics of the data. The analysis of the usage of metadata catalogue services in geodetic information systems has been given and the proposal for a possible solution for improvement has been made.U radu je prikazan kratki pregled usluga kataloga metapodataka Otvorenoga geoprostornog konzorcija (OGC) koji ima ključnu ulogu u otkrivanju geoprostornih izvora informacija u Prostornoj infrastrukturi podataka (SDI). Pojam Prostorne infrastrukture podataka obuhvaća skup tehnologija, strategija i institucionalnih sporazuma koji osiguravaju lakši pristup geoprostornim podacima. SDI je pogodan za upotrebu pri otkrivanju geoprostornih podataka, evaluaciji, kao i različitim primjenama unutar vladinog, komercijalnog i neprofitabilnog sektora, akademskih institucija, itd. Usluge kataloga metapodataka specificirane su u OGC Specifikaciji ostvarivanja usluga kataloga. Dio specifikacije koji se odnosi na web-sučelje koje podržava pohranu, učitavanje i upravljanje podacima koji se odnose na web-servise naziva se Kataloški servis za web (CSW). Katalozi metapodataka su agenti za usluge koji predstavljaju ključnu komponentu u arhitekturi namijenjenoj uslugama, a koja upravlja zajedničkim izvorima i olakšava otkrivanje izvora unutar otvorenoga distribuiranog sustava. OGC usluge stekle su značajnu popularnost u proteklim godinama, a broj organizacija koje ih koriste se povećao. Međutim, puni potencijal kataloga metapodataka još nije dostignut, ne samo zbog nedostatka odgovarajuće dokumentacije podataka u obliku standardiziranih metapodataka, već i zbog nedostatka semantike podataka. Napravljena je analiza korištenja usluga kataloga metapodataka u geodetskim informacijskim sustavima te je dan prijedlog za moguća rješenja u svrhu poboljšanja

Katalog metapodataka u prostornim informacijskim sustavima

This paper gives the short review of the Open Geospatial Consortium (OGC) metadata catalogue services that have the key role in geospatial resource discovery in Spatial Data Infrastructures (SDI). The notion of Spatial Data Infrastructure comprises a collection of technologies, policies and institutional agreements that provide an easier access to geospatial data. The SDI is suitable for usage in geospatial data discovery, evaluation, and also various applications within government, commercial and non-profit sectors, academic institutions, etc. Metadata catalogue services have been specified in OGC Catalogue Service Implementation Specification. The part of the specification that specifies a web interface that supports the storage, retrieval, and management of data related to web services, is called Catalogue Service for the Web (CSW). Metadata catalogues are service brokers that represent a key component in a service-oriented architecture that manages shared resources and facilitates the discovery of resources within an open, distributed system. OGC services have gained significant popularity in recent years and the number of organizations using them has increased. However, the full potential of metadata catalogues has not yet been reached, not only because of the lack of appropriate documentation of data in the form of standardized metadata, but because the lack of semantics of the data. The analysis of the usage of metadata catalogue services in geodetic information systems has been given and the proposal for a possible solution for improvement has been made.U radu je prikazan kratki pregled usluga kataloga metapodataka Otvorenoga geoprostornog konzorcija (OGC) koji ima ključnu ulogu u otkrivanju geoprostornih izvora informacija u Prostornoj infrastrukturi podataka (SDI). Pojam Prostorne infrastrukture podataka obuhvaća skup tehnologija, strategija i institucionalnih sporazuma koji osiguravaju lakši pristup geoprostornim podacima. SDI je pogodan za upotrebu pri otkrivanju geoprostornih podataka, evaluaciji, kao i različitim primjenama unutar vladinog, komercijalnog i neprofitabilnog sektora, akademskih institucija, itd. Usluge kataloga metapodataka specificirane su u OGC Specifikaciji ostvarivanja usluga kataloga. Dio specifikacije koji se odnosi na web-sučelje koje podržava pohranu, učitavanje i upravljanje podacima koji se odnose na web-servise naziva se Kataloški servis za web (CSW). Katalozi metapodataka su agenti za usluge koji predstavljaju ključnu komponentu u arhitekturi namijenjenoj uslugama, a koja upravlja zajedničkim izvorima i olakšava otkrivanje izvora unutar otvorenoga distribuiranog sustava. OGC usluge stekle su značajnu popularnost u proteklim godinama, a broj organizacija koje ih koriste se povećao. Međutim, puni potencijal kataloga metapodataka još nije dostignut, ne samo zbog nedostatka odgovarajuće dokumentacije podataka u obliku standardiziranih metapodataka, već i zbog nedostatka semantike podataka. Napravljena je analiza korištenja usluga kataloga metapodataka u geodetskim informacijskim sustavima te je dan prijedlog za moguća rješenja u svrhu poboljšanja