International Journal of Software Engineering and Knowledge Engineering

This paper presents some original methods for text summarization of a single source document by extraction. The methods are based on some of our own text segmentation algorithms. We denote them as logical segmentation because for all these methods (LTT, ArcInt and ArcReal) the score of a sentence is calculated starting from the number of sentences which are entailed by it. For a text (which is a sequence of sentences) the scores form a structure which indicates how the most important sentences alternate with less important ones and organizes the text according to its logical content. The second logical method, Pure Entailment also uses definition of the relation of entailment between two texts. At least to our knowledge, it is for the first time that the relation of Text Entailment between the sentences of a text is used for segmentation and summarization.

The third original method applies Dynamic Programming and centering theory to the sentences logically scored as above. The obtained ranked logical segments are used in the summarization. Our methods of segmentation and summarization are applied and evaluated against a manually realized segmentation and summarization of the same text by Donald Richie, "The Koan".

Given the advent of knowledge-based economies and virtual-enterprise business models, enterprises get the knowledge not only from themselves but also from others. Distributed case-based reasoning systems (DCBRS) play important roles in knowledge-driven virtual enterprises by supporting knowledge sharing.

This study develops a novel mechanism for ontology-based distributed case-based reasoning using ontology and a proposed multistage algorithm to effectively support knowledge sharing within a virtual enterprise environment. Tasks involved in this study are as follows: (i) design an ontology-based distributed case-based reasoning architecture and procedure, (ii) develop techniques related to the ontology-based distributed case-based reasoning, and (iii) implement an ontology-based distributed case-based reasoning mechanism. Developing methods associated with ontology-based distributed case-based reasoning involves the definition and representation of a user query model, definition and representation of a knowledge case model, definition and establishment of knowledge case index structure, and development of a distributed knowledge case retrieval and knowledge case adaptation methods. Study results will facilitate heterogeneous knowledge sharing among enterprises participating in a virtual enterprise.

Interoperability among different development tools is not a straightforward task since ontology editors rely on specific internal knowledge models which are translated into common formats such as RDF(S). This paper addresses the urgent need for interoperability by providing an exhaustive set of benchmark suites for evaluating RDF(S) import, export and interoperability. It also demonstrates, in an extensive field study, the state-of-the-art of interoperability among six Semantic Web tools. From this field study we have compiled a comprehensive set of practices that may serve as recommendations for Semantic Web tool developers and ontology engineers.

We apply an ontology based knowledge and software reuse methodology adhering to domain engineering principles. Our domain is trajectory simulation. A trajectory simulation is a piece of software to calculate the flight path and other parameters of a munition, such as its orientation and angular rates, from launch to impact. Trajectory Simulation ONTology (TSONT) has been constructed as part of the domain analysis. Object oriented and function oriented reuse infrastructures have been built based upon TSONT following a model-driven development approach. Use of these infrastructures in simulation development has been demonstrated.

Software maintenance becomes an integral part of software life cycle and constitutes the most important fraction of the total cost of the software lifecycle. Around 50–80 percent of the total lifecycle cost is consumed by maintenance for evolving system [35]. Thus systems with poor maintainability are difficult to modify and require more cost to maintain. This difficulty arises from the impact on the system components where the new requirements/goals will be implemented [9]. These new goals will result in modification of existing components and creation of new components. In this paper, we present the foundations for a new Hybrid-Based Maintainability Impact Analysis (HBMIA) methodology for assessing the impact of the new goals to be selected for implementation on new and existing system components. HBMIA uses not only the system history but it also gets benefit from the experts' experience. HBMIA balances between the system historical data and experts' data based on the system maturity and expert's experience for system components. A case study is performed to demonstrate the added value of the proposed HBMIA.