Abstract:
In current consumer community there is an increase use of online platforms to share and
exchange opinions, suggestions and experiences regarding products and services which on the
other hand know as engage in electronic Word of Mouth (eWOM) communication. In review
and comment aspects, each individual and environments may refer to the same feature of a
mobile phone with many different vocabularies which is meant to be the same meaning as a
whole. To top it all, there are massive number of such review and comment collectors available
online and as a consumer who wants to make a well informed decision, it is required to go
through online reviews as much as possible in different sites as possible as the crowds are
different and the user experiences are different in each crowd hence it is important to get data
collected from multiple sources to get better comparison out of all.
The research of the project main focuses to identify what are the most effective factors that a
potential mobile phone buyer seeks form online reviews and how to make a massive amount of
available online data to be filtered to make an informed decision on the mobile phone industry
domain. In this document, a solution introduced named as Review analyzer to integrate multiple
heterogeneous data sources and filter out relevant comments and produce a quantitative rating
of the features as per the comments available online. Many consumers are not familiar with the
technical features of the product. In our proposed framework, we map product features to
product reviews by an ontology. So the review analysis is based on the exploration of the
semantic relations in the ontology. Statistical figure of feature is introduced as ‘Context
Associated Relatedness’ which describes the quality of feature of product. User allows to do a
free text search of reviews to find the most relevant reviews of their query. Cosine Similarity
Score is used to find the most relevant quires. As a Qualitative output of the product, the top
rated comments are displayed with further filtering and search option to the top comments
displayed.
The system implemented in Java language in the Apache Jena framework, with the use of OWL
to build the ontology. The common platform to integrate data sources configured in RDF with
SPARQL query language to conduct the complex queries on the large data set. Implemented
system was tested thoroughly under different conditions and the Review analyzer system was
evaluated by evaluators of various domains. Eventually, the test results attested that the analysis,
design, implementation and documentation have been carried out in an effective and in an
efficient manner.
