Meeting Scheduling System Research Articles

A graph based requirements clustering approach for component selection

In recent years, Component Based System (CBS) development has found widespread application, particularly in the domain of engineering software where it is often necessary to adapt and integrate existing software tools to handle new problems. The ability to identify suitable components that match system requirements is fundamental to CBS success. To date, CBS selection techniques often make an ideal assumption that there is one-to-one mapping between requirements and components. In reality, components are usually designed for general purposes and provide a range of features that can be adapted to meet the needs of a CBS. This implies that a component can potentially match more than one functionality of a CBS. On the other hand, system requirements are usually not independent of each other and a component selection process needs to consider the dependencies between system goals. Furthermore, the existing component selection methodologies usually provide a single solution for the component selection problem, thus limiting the options available to a CBS developer. In this paper, we present a component selection process that uses a signed graph to model interdependencies of CBS-to-be needs and groups related goals into clusters, based on the usage, non-functional and threat dependencies. Subsequently, the matching index of each cluster of related goals is used as a criterion to identify a portfolio of candidate components for a CBS, providing multiple solutions for the component selection problem whenever possible. The component selection process helps a developer to elicit stakeholder needs, analyze their interdependencies and select components for a CBS. We also present application of our approach to a Meeting Scheduling System (MSS) and a Construction Management System (CMS).

A genetic fuzzy agent using ontology model for meeting scheduling system

A Genetic Fuzzy Agent (GFA) using the ontology model for Meeting Scheduling System (MSS) is presented in this paper. The ontology model includes the Fuzzy Meeting Scheduling Ontology (FMSO) and the Fuzzy Personal Ontology (FPO) that can support to construct the knowledge base of the GFA. The FMSO is utilized to record and describe the meeting scheduling domain knowledge for the GFA. In addition, we implement a FMSO editor for generating the Web Ontology Language, OWL, that will be utilized by the GFA. Furthermore, the GFA will infer the suitable meeting time slots based on the ontology model. Moreover, it also adjusts the FMSO and FPO based on the results of the genetic learning mechanism for the next meeting. The experimental results show that our approach can effectively work for MSS.

Exploring alternatives during requirements analysis

Goal-oriented requirements analysis techniques provide ways to refine organizational and technical objectives, to more effectively explore alternatives during requirements definition. After selecting a set of alternatives to achieve these objectives, you can elaborate on them during subsequent phases to make them more precise and complete. The authors argue that goal-oriented analysis complements and strengthens traditional requirements analysis techniques by offering a means for capturing and evaluating alternative ways of meeting business goals. They detail the five main steps that comprise goal-oriented analysis. These steps include goal analysis, softgoal analysis, softgoal correlation analysis, goal correlation analysis, and evaluation of alternatives. To illustrate the main elements of the proposed analysis technique, they explore a typical scenario that involves defining requirements for a meeting scheduling system.

Task-based conceptual graphs as a basis for automating software development

It is widely recognized that requirements engineering is a knowledge-intensive process and cannot be dealt with using only a few general principles. Since knowledge plays a crucial role in software development, software engineers have to describe and organize various aspects of knowledge before the program can be written. A recent work by Robillard reveals that software development can be further improved by recognizing the relevant knowledge structures. In this paper, we propose the use of a task-based conceptual graphs (TBCB) framework as a basis for automating software development. By structuring and operationalizing conceptual graphs, TBCG specifications can be transformed into executable programs automatically. To construct a conceptual model, task-based specification methodology is used as the mechanism to structure the knowledge captured in conceptual models, whereas conceptual graphs are adopted as the formalism to express task-based specifications and to provide a reasoning capability for the purpose of automation. Once task-based graphs have been constructed and verified, a blackboard system will automatically transform TBCG specifications into a software system composed of database schemas, knowledge base, and user interfaces. A meeting scheduling system is used as an illustrative example to demonstrate our approach. © 2000 John Wiley & Sons, Inc.

Agent-based meeting scheduling: A design and implementation

The Letter describes the design and implementation of a distributed meeting scheduling system in which each user has an intelligent agent in their computer desktop which is responsible for arranging meetings. Knowing the preferences and commitments of their user, the agents negotiate with one another to find the most acceptable meeting times.