Detecting Relationship between Features and Sentiment Words using Hybrid of Typed Dependency Relations Layer and POS Tagging (TDR Layer POS Tags) Algorithm
How to cite (IJASEIT) :
Ahmad, Siti Rohaidah, et al. “Detecting Relationship Between Features and Sentiment Words Using Hybrid of Typed Dependency Relations Layer and POS Tagging (TDR Layer POS Tags) Algorithm”. International Journal on Advanced Science, Engineering and Information Technology, vol. 6, no. 6, Dec. 2016, pp. 1120-6, doi:10.18517/ijaseit.6.6.1483.
Citation Format :
Through online product reviews, consumers share their opinions, criticisms and satisfactions on the products they have purchased. However, the abundance of product reviews may be confusing and time-consuming for prospective customers as they read and analyze differing views before buying a product. The unstructured format of product reviews needs a sentiment mining approach in analyzing customers’ comments on a product and its features. In this paper, the researchers explore and analyze the hybrid role of typed dependency relations (TDR) and part-of-speech tagging (POST) in detecting the relation between features and sentiment words. The researchers have also created a list of combination rules using TDR and POST to serve as a guide in identifying the relation between features and sentiment words in sentences. Results have shown that the hybrid algorithm could assist in identifying such a relationship and improve performance.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).