Text Orientation Analysis Of Scenic Spots Reviews Based On Dependency Relation

With the improvement of people's living standard, tourism has become an important part of people's lives. Meanwhile, the online scenic spots reviews will be more and more. These reviews are considered as significant reference information for potential visitors and local scenic spots managements. Visitors have utilized this piece of this information to understand view of other visitors and plan trips through read online comments before traveling. In order to improve tourist attractions of service quality, managements of scenic spots may understand the opinions and attitudes about scenic spots. However, it needs to spend a lot of time and energy to artificial read mass reviews, and readers may have "lost", it is unable to identify and using the valuable information. In order to accurately and efficiently mine opinion information that is interested for visitors. Text sentiment orientation analysis is one of the key problems need to solve.This paper studies the review texts sentiment orientation classification and the method of extract the feature-opinion in review texts based on dependency relation. The major works of this thesis focuses on the following:(1) Getting chunks based on the rulesIn order to extract the useful information about sentiment orientation classification. By using the dependency relation between word and word words, this thesis constructs the rules to obtain chunks which contain sentiment orientation. Experimental results show that the method based on rule obtain chunks is feasible.(2) Review texts sentiment orientation classification based on chunk featuresThe thesis utilizes chunks combined with emotional words as features of sentiment orientation classification. Through the experiment of sentiment orientation classification about scenic spots reviews, experimental results show that adopting chunk information can improve the performance of text sentiment orientation classification.(3) Feature-opinion extractionFeature-Opinion Extraction is one of the key researches in the area of opinion mining. This thesis studies the method to extract the feature-opinion in review texts based on dependency grammar. By using the dependency relation between word and word, we construct the rules to obtain chunks which contain evaluation object and opinion word, as well as the algorithm to identify candidate evaluation object. On this basis, we design an algorithm to extract feature-opinion with sentiment orientation. Experimental results prove the method is effective.