Computer Science & Electrical
Received: 03 Jul 2018 , Published: 06 July 2018
Views: 92 , Download: 59
With the highly expanding usage of
social media, a huge amount of data is being
collected day by day. Proliferation of movies and
their related views on social media has posed
significant challenges in discovering the most
suitable movies. Personalized recommenders that
have been implemented to recommend movies use
only a source of data and largely overlooked
integration of several big data sources including
tweets, you tube comments, posts on movies and
comments. Moreover, most of the current
approaches focus on one single aspect i.e. either
content-based, collaborative filtering. Overlooking
the integration of multiple aspects with many data
provenances caused low effectiveness in current
approaches. Hence, to overcome these deficiencies
a novel, hybrid approach, KLC model which
integrated user-based collaborative filtering,
locality sensitive hashing and network-based
approach is proposed. The New KLC model has
been tested with 10000000 data items it
outperforms benchmark methods
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