Movie Recommendation System using Cosine Similarity with Sentiment Analysis

Khatter, Harsh; Goel, Nishtha; Gupta, Naina; Gulati, Muskan

doi:10.1109/icirca51532.2021.9544794

Cited by 17 publications

(3 citation statements)

References 7 publications

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“…Various works are available which use the hybrid fuzzy models on different applications. The desired one is to work on the blog posts and recommend the relevant posts to the user like for recommendations [20][21][22] highlighted about the user's response on the recommendations by the system, whereas the blog-related work is discussed in [23,24].…”

Section: Related Workmentioning

confidence: 99%

Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS

et al. 2022

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Day by day, the number of blog users and microblog users is increasing worldwide. It is easy to say that blogs have captured a significant portion of other web services. In the past few years, the number of users has exponentially increased. User count of Facebook, Twitter, and Instagram applications is not hidden from anyone. Users on such platforms share ideas, experiences, stories, opinions, and views and want to interact with people with the same set of interests. As per the user’s expectation, there is a requirement of two things: content curation and recommendations. The content curation algorithm will find the people and their posts on personalized search results. In addition, the recommendation system will help to find the most appropriate match to interact with. In this paper, both approaches are combined to show the user’s curated and recommended results. The article focuses on the hybrid model named S-ANFIS, and the results are compared with the well-known approaches like ANN, Deep Neural Network (DNN), and Recurrent Neural Network (RNN).

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Section: Related Workmentioning

confidence: 99%

Adaptive and Personalized Web Blog Searching Technique Using S-ANFIS

et al. 2022

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“…The data used to support the findings of this study are available and can be accessed online through the GitHub platform [15].…”

Section: Data Availability Statementmentioning

confidence: 94%

“…The advantage of cosine similarity is that even if two documents are separated by a large Euclidean distance, they can still be considered similar. A smaller angle corresponds to a higher cosine similarity [15]. Figure 4 illustrates the assignment of different weights to each feature based on their importance and relationship.…”

mentioning

confidence: 99%

Promoting Sustainable Travel Experiences: A Weighted Parallel Hybrid Approach for Personalized Tourism Recommendations and Enhanced User Satisfaction

Alshamlan,

Alghofaili,

ALFulayj

et al. 2023

Sustainability

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With the growing significance of the tourism industry and the increasing desire among travelers to discover new destinations, there is a need for effective recommender systems that cater to individual interests. Existing tourism mobile applications incorporate recommendation systems to alleviate information overload. However, these systems often overlook the varying importance of different items, resulting in suboptimal recommendations. In this research paper, a novel approach is proposed: a weighted parallel hybrid recommendation system. By considering item weights and leveraging parallel processing techniques, this method significantly enhances the accuracy of the similarity between items, leading to improved recommendation quality and precision. With this approach, users can efficiently and effectively explore new destinations that align with their unique preferences and interests, thereby enhancing their overall tourism experience and satisfaction. To evaluate the effectiveness of the proposed weighted parallel hybrid recommendation system, we conducted experiments using a dataset consisting of 20 users. The results demonstrated that the proposed approach achieved an impressive classification accuracy of 80%. A comparative analysis revealed that the proposed approach outperformed that of existing systems and achieved the best results in terms of classification accuracy. This finding highlights the effectiveness and efficiency of the proposed method in generating and promoting sustainable travel experiences by developing a personalized recommendations system for the unique preferences and interests of individual users.

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