Comparison of syntax tree visualization: Toward Malay Language (BM) syntax tree

This study will analyze natural language syntax tree visualizations to compare visualization methods in order to choose the optimum solution for visualizing a BM syntax tree.Currently no syntax tree visualization for BM has been introduced, and no visualization is yet available in the form of computer software or a prototype.Methods that can be dealt with in creating a BM syntax tree include: tokenizing, a performing search and comparison, matching with the associated rules, and composing.Ten systems were analyzed, and the Link Grammar system was found to be the most viable.The Link Grammar system does not have a hierarchical structure that reflects the language syntax as compared to the SSTC (Structured String-Tree Correspondence) application which does.However, the SSTC shows the tree structure in a hierarchical manner, but it does not have a suitable method to follow in visualizing the BM sentence syntax tree

Le raisonnement à partir de cas pour l'identification de rôles sémantiques dans des énoncés en langue naturelle

Colloque avec actes sans comité de lecture. nationale.National audienceLes énoncés en langue naturelle dans les domaines techniques présentent des constructions syntaxiques récurrentes. Nous proposons de mettre en oeuvre un système de raisonnement à partir de cas pour nous permettre de passer de l'analyse syntaxique d'une phrase à sa représentation conceptuell

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