Visualisasi pohon sintaksis berasaskan model dan algoritma sintaks ayat bahasa Melayu

Previous works that produce syntactic tree output has disregarded additional relevant components such as sentence checking, sentence correction, the syntax tree visualization and the words attributes of each sentence. As such, this study aims at producing an algorithm for syntactic tree output enhancement from which the relevant output component mentioned above can be produced. The additional components namely sentence checking, sentence correction, syntax tree visualization (VPS) and word attribute are modelled into a package prior to translating them into a tangible output. In term of rules, previous studies have used phrase-structure rules (RSF) in analysing the Malay sentence. But RSF has been found to be a non-universal formula. Our work has brought us to the introduction of X-bar rules for BM VPS, which consequently becomes one of the contributions of this study. To achieve these objectives (the algorithm, the model and the X-bar rules), five phases of research methods involved namely identifying the research gap, the sentence and rules categorization, model and algorithm design phase, prototype development evaluation and conclusion phase. Parseval assessment method, which is an output evaluation method in natural language processing, was used for the evaluation. Point of analysis were the recall and precision valuation metrics. For VPS output, the average results obtained were 100% for recall and 97.8% for precision. For sentence correction, the results given were 100% for recall and 87.8% for precision. These results proved that the algorithm and model, for syntactic tree output enhancement, are generalisable enough to be tested on other languages. User evaluation on the prototype was also performed yielding in the average subjective satisfaction of 87.9% and a mean score of 6.157, based on semantic differential scales of 1 to 7. Cognitive assessment was also recorded, obtaining average cognitive score of 84.6% with a mean score of 4.230, on the scale 5. Analysis on those results indicated positive scores on the model-based product specifically on usefulness, ease of use, ease of learning, subjective satisfaction, and cognitive measures. It can be concluded that the algorithm and model proposed were useful for the development of the prototype. The prototype is therefore beneficial as an educational assistance to understand Malay sentences when provided with enhanced output on sentence checking, sentence correction, syntax tree visualization (VPS) and words attribut

INTERACTIVE VISUALIZATIONS FOR TREES AND GRAPHS

Graphs are a very commonly used information structure, and have been applied to a broad range of fields from computer science to biology. There are several important issues to consider when designing graph visualizations. One of the most difficult problems researchers face is how to visualize large graphs. While an algorithm may produce good layouts for graphs of several hundred nodes, it may not scale well to several thousand nodes. And, as the size of the graph increases, performance will degrade rapidly, making it difficult to build an interactive system. Label readability will also suffer, hindering users ’ abilities to understand the graph data and perform many tasks. Finally, even if a system can lay out and display large graphs, the cognitive demands placed on the user by the visualization may be overwhelming. This dissertation describes and applies several design principles to various graph visualization domains to address these issues. Tightly-coupled and highly customized views were used for graph visualization in a novel way. A new tree layout approach to graph visualization was proposed with appropriate visualization and interaction techniques. When visualizing graphs as trees, a guiding metapho