Jon Atle Gulla

An information retrieval approach to ontology mapping

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e., using instance information of the ontology to enrich the original ontology and calculate similarities between concepts in two ontologies. The functional settings for the mapping system are discussed and the evaluation of the prototype implementation of the approach is reported.

Semantic Enrichment for Ontology Mapping

In this paper, we present a heuristic mapping method and a prototype mapping system that support the process of semi-automatic ontology mapping for the purpose of improving semantic interoperability in heterogeneous systems. The approach is based on the idea of semantic enrichment, i.e. using instance information of the ontology to enrich the original ontology and calculate similarities between concepts in two ontologies. The functional settings for the mapping system are discussed and the evaluation of the prototype implementation of the approach is reported.

PPP: an integrated CASE environment

This article presents the PPP (Phenomena, Processes, and Programs) environment. PPP is based on a development strategy for information systems and consists of a diagrammatical language, a method, and a support tool. The strategy follows a top-down approach where specifications are developed in an incremental and iterative manner. Furthermore, we emphasize on integrating analysis and overall design.

Industrial application of semantic process mining

Process mining relates to the extraction of non-trivial and useful information from information system event logs. It is a new research discipline that has evolved significantly since the early work on idealistic process logs. Over the last years, process mining prototypes have incorporated elements from semantics and data mining and targeted visualisation techniques that are more user-friendly to business experts and process owners. In this article, we present a framework for evaluating different aspects of enterprise process flows and address practical challenges of state-of-the-art industrial process mining. We also explore the inherent strengths of the technology for more efficient process optimisation.

A general explanation component for conceptual modeling in CASE environments

In information systems engineering, conceptual models are constructed to assess existing information systems and work out requirements for new ones. As these models serve as a means for communication between customers and developers, it is paramount that both parties understand the models, as well as that the models form a proper basis for the subsequent design and implementation of the systems. New CASE environments are now experimenting with formal modeling languages and various techniques for validating conceptual models, though it seems difficult to come up with a technique that handles the linguistic barriers between the parties involved in a satisfactory manner. In this article, we discuss the theoretical basis of an explanation component implemented for the PPP CASE environment. This component integrates other validation techniques and provides a very flexible natural-language interface to complex model information. It describes properties of the modeling language and the conceptual models in terms familiar to users, and the explanations can be combined with graphical model views. When models are executed, it can justify requested inputs and explain computed outputs by relating trace information to properties of the models.

Model-Based Business Process Mining

Abstract As companies use enterprise resource planning (ERP) systems to support their business processes, they need to verify that the systems are configured appropriately and used in the most efficient way. This article describes the approach taken and results from a business process mining project at a midsized company in Norway. A newly released tool for analyzing ERP system logs is used to construct the underlying business flows and to provide new insights that can be used by the company to improve the procurement process.

A model-driven ERP Environment with search facilities

Traditional business models are primarily used in the initial phases of BPR or enterprise resource planning projects. They are static representations of systems requirements and business procedures, but have proven less useful in supporting the actual use of the systems. With the model-driven business management (MDBM) approach, dynamic and adaptable business models constructed as part of the implementation project are afterwards used to access the system and monitor the real business flows. In this paper, we present the linguistic aspects of the MDBM approach and discuss how the linguistic part and the modeling part of MDBM mutually support each other.

Ontology learning for search applications

Ontology learning tools help us build ontologies cheaper by applying sophisticated linguistic and statistical techniques on domain text. For ontologies used in search applications class concepts and hierarchical relationships at the appropriate level of detail are vital to the quality of retrieval. In this paper, we discuss an unsupervised keyphrase extraction system for ontology learning and evaluate its resulting ontology as part of an ontology-driven search application. Our analysis shows that even though the ontology is slightly inferior to manually constructed ontologies, the quality of search is only marginally affected when using the learned ontology. Keyphrase extraction may not be sufficient for ontology learning in general, but is surprisingly effective for ontologies specifically designed for search.

User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues

Intelligent dialogue systems usually concentrate on user support at the level of the domain of discourse, following a plan-based approach. Whereas this is appropriate for collaborative planning tasks, the situation in interactive information retrieval systems is quite different: there is no inherent plan-goal hierarchy, and users are known to often opportunistically change their goals and strategies during and through interaction. We need to allow for mixed-initiative retrieval dialogues, where the system evaluates the users individual dialogue behavior and performs situation-dependent interpretation of user goals, to determine when to take the initiative and to change the control of the dialogue, e.g., to propose (new) problem-solving strategies to the user. In this article, we present the dialogue planning component of a concept- oriented, logic-based retrieval system (MIRACLE). Users are guided through the global stages of the retrieval interaction but may depart, at any time, from this guidance and change the direction of the dialogue. When users submit ambiguous queries or enter unexpected dialogue control acts, abductive reasoning is used to generate interpretations of these user inputs in light of the dialogue history and other internal knowledge sources. Based on these interpretations, the system initiates a short dialogue offering the user suitable options and strategies for proceeding with the retrieval dialogue. Depending on the users choice and constraints resulting from the history, the system adapts its strategy accordingly.

A Conceptual Modeling Approach to Semantic Document Retrieval

This paper describes an approach to semantic document retrieval geared towards cooperative document management. In our conceptual modeling approach, a semantic modeling language is used to construct a domain model of the subject domain referred to by the document collection. This domain model is actively used for the tasks of document classification and search. Moreover, linguistic techniques are used to facilitate both the construction of the model and its use. This paper presents our prototype model-based classification and search tool and how it is applied on a document collection from a Norwegian company.