مشروع البحث: EXPLOITING DOMAIN KNOWLEDGE TO ENHANCE OPINION MINING USING A HYBRID SEMANTIC KNOWLEDGEBASE-MACHINE LEARNING APPROACH
تحميل...
المساهمين
الممولين
رقم التعريف
804
الباحث
رويدا عبد المجيد الفرجاني
الوصف
This research presents a Hybrid Semantic Knowledgebase-Machine Learning approach for mining opinions at the domain feature level and classifying the overall opinion on a multi-point scale. The proposed approach benefits from the advantages of deploying a novel Semantic Knowledgebase approach to analyse a collection of reviews at the domain feature level and produce a set of structured information that associates the expressed opinions with specific domain features. The information in the knowledgebase is further supplemented with domain-relevant facts sourced from public Semantic datasets, and the enriched semantically-tagged information is then used to infer valuable semantic information about the domain as well as the expressed opinions on the domain features by summarising the overall opinions about the domain across multiple reviews, and by averaging the overall opinions about other cinematic features. The retrieved semantic information represents a valuable resource for training a Machine Learning classifier to predict the numerical rating of each review
الكلمات الدالة
MACHINE LEARNING APPROACH