Construct redundancy in process modelling grammars: Improving the explanatory power of ontological analysis

Conceptual modelling supports developers and users of information systems in areas of documentation, analysis or system redesign. The ongoing interest in the modelling of business processes has led to a variety of different grammars, raising the question of the quality of these grammars for modelling. An established way of evaluating the quality of a modelling grammar is by means of an ontological analysis, which can determine the extent to which grammars contain construct deficit, overload, excess or redundancy. While several studies have shown the relevance of most of these criteria, predictions about construct redundancy have yielded inconsistent results in the past, with some studies suggesting that redundancy may even be beneficial for modelling in practice. In this paper we seek to contribute to clarifying the concept of construct redundancy by introducing a revision to the ontological analysis method. Based on the concept of inheritance we propose an approach that distinguishes between specialized and distinct construct redundancy. We demonstrate the potential explanatory power of the revised method by reviewing and clarifying previous results found in the literature

Machine learning : techniques and foundations

The field of machine learning studies computational methods for acquiring new knowledge, new skills, and new ways to organize existing knowledge. In this paper we present some of the basic techniques and principles that underlie AI research on learning, including methods for learning from examples, learning in problem solving, learning by analogy, grammar acquisition, and machine discovery. In each case, we illustrate the techniques with paradigmatic examples

Concurrent Lexicalized Dependency Parsing: The ParseTalk Model

A grammar model for concurrent, object-oriented natural language parsing is introduced. Complete lexical distribution of grammatical knowledge is achieved building upon the head-oriented notions of valency and dependency, while inheritance mechanisms are used to capture lexical generalizations. The underlying concurrent computation model relies upon the actor paradigm. We consider message passing protocols for establishing dependency relations and ambiguity handling.Comment: 90kB, 7pages Postscrip

Technological Spaces: An Initial Appraisal

In this paper, we propose a high level view of technological spaces (TS) and relations among these spaces. A technological space is a working context with a set of associated concepts, body of knowledge, tools, required skills, and possibilities. It is often associated to a given user community with shared know-how, educational support, common literature and even workshop and conference regular meetings. Although it is difficult to give a precise definition, some TSs can be easily identified, e.g. the XML TS, the DBMS TS, the abstract syntax TS, the meta-model (OMG/MDA) TS, etc. The purpose of our work is not to define an abstract theory of technological spaces, but to figure out how to work more efficiently by using the best possibilities of each technology. To do so, we need a basic understanding of the similarities and differences between various TSs, and also of the possible operational bridges that will allow transferring the results obtained in one TS to other TS. We hope that the presented industrial vision may help us putting forward the idea that there could be more cooperation than competition among alternative technologies. Furthermore, as the spectrum of such available technologies is rapidly broadening, the necessity to offer clear guidelines when choosing practical solutions to engineering problems is becoming a must, not only for teachers but for project leaders as well

Language acquisition and machine learning

In this paper, we review recent progress in the field of machine learning and examine its implications for computational models of language acquisition. As a framework for understanding this research, we propose four component tasks involved in learning from experience - aggregation, clustering, characterization, and storage. We then consider four common problems studied by machine learning researchers - learning from examples, heuristics learning, conceptual clustering, and learning macro-operators - describing each in terms of our framework. After this, we turn to the problem of grammar acquisition, relating this problem to other learning tasks and reviewing four AI systems that have addressed the problem. Finally, we note some limitations of the earlier work and propose an alternative approach to modeling the mechanisms underlying language acquisition

Graph Grammars for Knowledge Representation

This report consists of two papers presented at the March 1990 GRAGRA meeting in Bremen: the more general ''Representation of knowledge using graph grammars'' which argues for graphs as the universal KR formalism and the more specific ''The four musicians: analogies and expert systems -- a graphic approach'' which demonstrates the use of graphics for type inheritance and analogical reasoning

Using an ontology for guiding natural language interaction with knowledge based systems

Des dels anys 80, els sistemes basats en el coneixement, programes que utilitzen una gran quantitat de informació per modelar situacions i resoldre problemes, han adquirit gran importància en el camp industrial, financer i científic. La complexitat d'aquests sistemes fa que el seu ús presenti més dificultats que altres aplicacions informàtiques. La comunicació entre els sistemes basats en el coneixement i l'usuari presenta, doncs, nous reptes. Tot i que el llenguate natural es especialment apropiat per comunicar-se amb aquests sistemes, són pocs els que incorporen interfícies en llenguatge natural. Els motius principals són els problemes d'eficiència que presenta el processament del llenguatge natural i l'elevat cost de desenvolupar les bases de coneixement (conceptual i lingüístic) necessàries per a cada aplicació. L'objectiu d'aquesta tesi és millorar la comunicació en llenguatge natural amb els sistemes basats en el coneixement. Aquesta recerca s'ha centrat en el disseny d'una representació reutilitzable dels diferents tipus de coneixement involucrats en aquesta comunicació, que permetir de generar de forma automàtica la interfície més adequada per a cada aplicació. S'ha desenvolupat un sistema, GISE (Generador de Interfaces a Sistemas Expertos), que genera interfícies en llenguatge natural per diferents tipus d'aplicacions. Aquest sistema adapta automàticament les bases de coneixement lingüístic generals als requeriments d'una aplicació concreta, obtenint la gramàtica més apropiada. El disseny del sistema està basat en una representació reutilitzable i modular dels diferents tipus de coneixement necessaris en la comunicació en llenguatge natural. Aquesta informació consisteix en els conceptes de l'aplicació, les tasques de comunicació, el coneixement lingüístic i les relacions generals entre el coneixement conceptual i la seva realització lingüística. Tres bases de coneixement s'han dissenyat per representar aquesta informació: la ontologia conceptual, la ontologia lingüística i un conjunt de relges de producció. El coneixement conceptual s'ha representat en la ontologia conceptual. Aquest coneixement inclou aspectes sobre el domini i la funcionalitat. Tota la informació necessària per modelar l'aplicació i tots els possibles actes de comunicació estan representats en la ontologia conceptual. La complexitat dels sistemes basats en el coneixement fa necessària una representació formal i explícita de la seva funcionalitat i domini.El coneixement lingüístic general necessari per expressar en llenguatge natural les possibles tasques del sistema es representen en la ontologia lingüística.La informació que permet relacionar el coneixement lingüístic general a una aplicació concreta per tal d'obtenir la gramàtica més adequada es representada mitjançant un conjunt de regles de producció.L'organització modular dels diferents tipus de coneixement que intervenen en la comunicació facilita l'adaptació del sistema a diferents tipus d'aplicacions i usuaris.Les gramàtiques generades pel sistema GISE utilitzen un llenguatge alhora ric i precís, adaptat a l'aplicació. La interfície del sistema incorpora un sistema de finestres que guia a l'usuari a introduir les opcions en llenguatge natural que el sistema reconeix.GISE s'ha aplicat a diferents sistemes: a SIREDOJ, un sistema expert en lleis i a un sistema que dóna informació sobre trens.Since the 1980's, knowledge based systems (KBSs), programs that use knowledge to model situations and solve problems, have spread throughout industry, finance and science. Human communication with these systems deals with complex concepts and relationships that are not present in other software applications. Allthough the natural language (NL) is especially appropriate for expressing these concepts, there are not many KBSs incorporating NL interfaces. The main reasons for this are problems of efficiency in NLI performance, lack of adequacy to the communication needs of the applications and the high cost of developing and maintaining them.The aim of this thesis is to study how the communication process and engineering features can be improved in NL interaction with KBSs. This study has been focused on the efficient and reusable representation of the knowledge involved in NL communication with KBSs. GISE (Generador de Interfaces a Sistemas Expertos), a system supporting NL communication with KBSs has been developed. This system adapts the general linguistic resources to application requirements in order to automatically obtain application-restricted grammars. The main issue of the system design is a separate and reusable representation of all types of knowledge involved in communication with KBSs. This knowledge consists of the application knowledge appearing in the communication, the tasks of communication, the linguistic knowledge supporting their expression and the general relationships between conceptual knowledge and its linguistic realization. Three general bases were designed to represent all this knowledge : the Conceptual Ontology (CO), the Linguistic Ontology (LO) and a set of control rules.Conceptual knowledge is represented in the CO. This conceptual knowledge includes domain and functionality issues. All knowledge required to model the applications as well as the description of all possible communication acts is provided in the CO. The CO is the skeleton for anchoring the domain and the functionality of the applications. The complexity of KBS performance makes a formal and explicit representation of their domain and functionality necessary. The general linguistic knowledge needed to cover the expression in NL of the tasks the system performs is represented by means of the LO and a set containing all possible realizations of the application terms. The LO is domain and application independent. The control information to relate the general linguistic knowledge to conceptual application knowledge in order to generate the application-restricted grammars is represented by a set of production rules. The modular organization of the relevant knowledge into separate data structures provides great flexibility for adapting the system to different types of applications and users.The grammars generated by GISE use expressive and precise language tuned to the application and adapted to the evolution of the communicative process. A menu-system to guide the user in introducing the NL is integrated into the GISE interface. GISE has been applied to a couple of applications: SIREDOJ, an ES in law and a railway communication system

Guidelines for empirical evaluations of conceptual modeling grammars

Conceptual modeling grammars are used to create scripts that represent someone's perception, or some group's negotiated perception, of domain semantics. For many years, researchers have evaluated conceptual modeling grammars to determine ways that they can be improved. One way to evaluate them is to empirically evaluate the strengths and weaknesses of the grammars in terms of their effectiveness and efficiency in generating scripts. A number of researchers have proposed guidelines for the design of empirical research to conduct such evaluations. Although these guidelines have proved useful, further clarification is needed in relation to (1) criteria for evaluating grammar performance, (2) characteristics of grammars that can influence grammar performance, and (3) factors that must be considered when testing the effect of grammar characteristics on grammar performance. We review past conceptual modeling research and provide guidelines for addressing these three issues. We also illustrate how the guidelines would apply to studies that evaluate conceptual modeling grammars from an ontological perspective. Finally, we discuss how the guidelines extend those offered in past research and the implications of our work for future research