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Semantic Clustering Driven Approaches to Recommender Systems

Authors:

Prafulla Bafna,

Shailaja Shirwaikar,

Dhanya PramodAuthors Info & Claims

COMPUTE '16: Proceedings of the 9th Annual ACM India Conference

Pages 1 - 9

https://doi.org/10.1145/2998476.2998487

Published: 21 October 2016 Publication History

Abstract

Recommender Systems (RS) have increasingly evolved from novelties used by few E-commerce sites to an essential component of business tools handling the world of E-commerce. Recommender Systems have been widely used for product recommendations such as books and movies as well as, it is also gaining ground in service recommendations such as hotels, restaurants and travel attractions. Collaborative filtering based on reviews and ratings is usually applied that uses Clustering technique. The primary step of converting textual reviews into a Feature Matrix (FM) can be greatly refined by using semantic similarity between terms. In this paper Wordnet based Synset grouping approach is presented that not only reduces dimensions in FM but also generates Feature vectors (FV) for each cluster with significantly improved cluster quality. The paper presents a three step approach of validating the reviews, grouping of reviews and review based recommendations using Feature vector. Real datasets extracted from travel sites are used for experiments.

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Cited By

Bafna PSaini J(2020)On Readability Metrics of Goal Statements of Universities and Brand-Promoting Lexicons for IndustriesData Management, Analytics and Innovation10.1007/978-981-15-5616-6_5(63-72)Online publication date: 19-Aug-2020
https://doi.org/10.1007/978-981-15-5616-6_5

Index Terms

Semantic Clustering Driven Approaches to Recommender Systems
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
2. Information systems
  1. Information retrieval
    1. Evaluation of retrieval results

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Abstract
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COMPUTE '16: Proceedings of the 9th Annual ACM India Conference

October 2016

178 pages

ISBN:9781450348089

DOI:10.1145/2998476

Copyright © 2016 ACM.

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Association for Computing Machinery

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Publication History

Published: 21 October 2016

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ACM COMPUTE '16

ACM COMPUTE '16: Ninth Annual ACM India Conference

October 21 - 23, 2016

Gandhinagar, India

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COMPUTE '16 Paper Acceptance Rate 22 of 117 submissions, 19%;

Overall Acceptance Rate 114 of 622 submissions, 18%

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Cited By

Bafna PSaini J(2020)On Readability Metrics of Goal Statements of Universities and Brand-Promoting Lexicons for IndustriesData Management, Analytics and Innovation10.1007/978-981-15-5616-6_5(63-72)Online publication date: 19-Aug-2020
https://doi.org/10.1007/978-981-15-5616-6_5

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