Title :
Analysis of syntactic patterns for identification of features from unstructured reviews
Author :
Khan, Khairullah ; Baharudin, Baharum B.
Author_Institution :
Universiti Teknologi PERONAS Malaysia
Abstract :
Collecting consumer opinion about products through web is becoming more popular day by day. The opinion of users is helpful to consumers, retailors, and manufacturers in decision making. Due to the huge number user reviews it is impossible to summarize it. Therefore systems are required for mining consumer reviews data efficiently. Opinion mining is an interesting area of research due to its applications in various fields. One of the challenging issues in this area is the identification of opinion components from unstructured reviews. The work of opinion mining is natural language dependent. Therefore syntactic patterns play a key role in identifying the opinion components. In this paper we have presented analysis of synaptic patterns for products features identification from unstructured reviews. Basically the noun phrases are used for named entity identification; however all noun phrases are not features. The problem is how to restrict the patterns to get the features. After in-depth analysis and evaluation we identify a new pattern which shown comparatively best result.
Keywords :
Features Extraction; Opinion Mining; Syntactic Patterns;
Conference_Titel :
Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-1968-4
DOI :
10.1109/ICIAS.2012.6306180