Product Recommendation System Design Using Cosine Similarity and Content-based Filtering Methods

2019 ◽  
Vol 3 (2) ◽  
pp. 42
Author(s):  
Cut Fiarni ◽  
Herastia Maharani
Keyword(s):  
System Design ◽  
Recommendation System ◽  
New Products ◽  
New Product ◽  
Similarity Score ◽  
Cosine Similarity ◽  
A Company ◽  
Content Based Filtering ◽  
Similarity Method ◽  
Suitable Product

The wide variety of products offered by a company, combined with the consistent demands of specific products from customers, create a certain problem for the organization when they want to market a new product. Organization need information that could help them promote the most suitable product based on their customer’s characteristics. The organization also need to suggest alternative products for customer if the requested product is unavailable. In this research, we design a Recommender System that could suggest either new or alternatif products to customer based on their characteristic and transaction history. This proposed system adopts Cosine Similarity method to calculate product similarity score and Content-based Filtering to calculate customer recommendation score and used as a model for the proposed system. Subsequently, these models are used to classify customers as well as products according to their transaction behavior and consequently recommends new products more likely to be purchased by them. Based on the testing results of the proposed system, it can be concluded that the chosen methods can be utilized to recommend products and costumer of products. It is shown that Precision and Recall of product similarity scores and customer recommendation for product scores are 100% and 93.47%.

scholarly journals Movie Recommendation System using Machine Learning

2021 ◽  
Vol 9 (VI) ◽  
pp. 4778-4781
Author(s):  
Ghanashyam Vibhandik
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
Cosine Similarity ◽  
Daily Lives ◽  
Movie Content ◽  
Movie Recommendation ◽  
The Many ◽  
The Individual ◽  
Content Based Filtering ◽  
Filtering Approach

Movies are very significant in our lives. It is one of the many forms of entertainment that we encounter in our daily lives. It is up to the individual to decide whatever type of film they choose to see, whether it is a comedy, romantic film, action film, or adventure film. However, the issue is locating acceptable content, as there is a large amount of information created each year. As a result, finding our favourite film is really difficult. The goal of this research is to improve the regular filtering technique's performance and accuracy. A recommendation system can be implemented using a variety of approaches. Content-based filtering and collaborative filtering strategies are employed in this work. The content-based filtering approach analyses the user's history/past behaviour and recommends a list of comparable movies depending on their input. K-NN algorithms and collaborative filtering are also employed in this paper to improve the accuracy of the results. Cosine similarity is utilised in this work to quickly discover comparable information. The correctness of the cosine angle is measured by cosine similarity. People may quickly find their favourite movie content thanks to all of this.

A strategy of innovation through the development of a portfolio of innovation capabilities

2014 ◽  
Vol 33 (1) ◽  
pp. 24-31 ◽  
Author(s):  
Yair Holtzman
Keyword(s):  
Competitive Advantage ◽  
New Product Development ◽  
Work Experience ◽  
New Products ◽  
New Product ◽  
Sustainable Competitive Advantage ◽  
Business World ◽  
Content Type ◽  
Novel Approach ◽  
A Company

Purpose – The purpose of this paper is to introduce the value in developing a portfolio of capabilities to fuel innovation. The author's experience suggests that a disciplined focus developing a portfolio of innovation capabilities is critical in the global competitive landscape. Traditionally, the business world has always been focussed on developing sustainable competitive advantage. This is optimal, but we find more and more situations where this notion of building a sustainable competitive advantage is no longer possible. In 2013 it is rare for a company to maintain a truly lasting advantage. Many times, the very success of the initiative drives competition, which in turn weakens the advantage. Innovation as a portfolio of capabilities that can continuously morph based on the traditional forces of the market can prove much more powerful. This paper discusses what is needed in developing a strategy for developing a portfolio of capabilities and the challenges that companies face in undertaking this goal. Design/methodology/approach – General viewpoint based upon over 20 years of consulting work experience by an expert in the field of innovation, new product development, and research and development. Findings – The relevance and importance of a novel approach to thinking about innovation is very creative and valuable to companies that are constantly struggling with the development of new products. Practical implications – This is a novel approach to thinking about developing new products, capabilities, or services within an organization. Originality/value – The paper is extremely valuable in that it highlights a new way to think about developing innovation and new product capabilities, new product features, in a competitive global environment.

scholarly journals Movie Recommending System Using Collaborative Filtering

2021 ◽  
Vol 9 (VII) ◽  
pp. 1034-1038
Author(s):  
P. Rama Rao
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Cosine Similarity ◽  
Nearest Neighbours ◽  
And Performance ◽  
Content Based Filtering

Movies are one of the sources of entertainment, but the problem is in finding the content of our choice because content is increasing every year. However, recommendation systems plays here an important role for finding the content of desired domain in these situations. The aim of this paper is to improve the accuracy and performance of a filtration techniques existed. There are several methods and algorithms existed to implement a recommendation system. Content-based filtering is the simplest method, it takes input from the users, checks the movie and its content and recommends a list of similar movies. In this paper, to prove the effectiveness of our system, K-NN algorithms and collaborative filtering are used. Here, the usage of cosine similarity is done for recommending the nearest neighbours.

scholarly journals The value of customer involvement in new product development for company

Marketing ◽  
2020 ◽  
Vol 51 (4) ◽  
pp. 271-282
Author(s):  
Mirjana Gligorijević ◽  
Jovan Rusić
Keyword(s):  
Product Development ◽  
New Product Development ◽  
New Products ◽  
New Product ◽  
Market Size ◽  
Local Market ◽  
Customer Involvement ◽  
The Past ◽  
Development Processes ◽  
A Company

Modern companies are facing much tougher competition than before. In the past, companies were competing, mostly with other companies locally. Now companies can offer their products to customers beyond the local market. Globalization presents a huge chance for companies to grow by an increase in the market size, but as the market size grows, the same happens with the competition. If a company wants to endure, a company is under pressure to innovate, and including customers can affect new product development. The goal of this paper is to determine if including consumers in new product development can affect faster and better quality new product development processes and increase new product value for the company. This analysis should provide us with an answer to the question, should we include consumers, and if we should, when? The results of this paper could act as a guide for managers in developing new products.

scholarly journals A Movie Recommendation System Based on A Convolutional Neural Network

2021 ◽  
Vol 9 (12) ◽  
pp. 1445-1455
Author(s):  
Jyoti Kumari
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Collaborative Filtering ◽  
Recommender System ◽  
Recommendation System ◽  
Cosine Similarity ◽  
The Other ◽  
Human Effort ◽  
Movie Recommendation ◽  
Content Based Filtering

Abstract: Due to its vast applications in several sectors, the recommender system has gotten a lot of interest and has been investigated by academics in recent years. The ability to comprehend and apply the context of recommendation requests is critical to the success of any current recommender system. Nowadays, the suggestion system makes it simple to locate the items we require. Movie recommendation systems are intended to assist movie fans by advising which movie to see without needing users to go through the time-consuming and complicated method of selecting a film from a large number of thousands or millions of options. The goal of this research is to reduce human effort by recommending movies based on the user's preferences. This paper introduces a method for a movie recommendation system based on a convolutional neural network with individual features layers of users and movies performed by analyzing user activity and proposing higher-rated films to them. The proposed CNN approach on the MovieLens-1m dataset outperforms the other conventional approaches and gives accurate recommendation results. Keywords: Recommender system, convolutional neural network, movielens-1m, cosine similarity, Collaborative filtering, content-based filtering.

scholarly journals LAUNCHING INNOVATIVE COSMETICS PRODUCTS TO LITHUANIAN MARKET

2021 ◽  
Vol 13 (0) ◽  
pp. 1-8
Author(s):  
Ieva Vaičiūtė
Keyword(s):  
Development Process ◽  
New Products ◽  
New Product ◽  
Life Cycles ◽  
Product Development Process ◽  
Key Factors ◽  
Global Marketplace ◽  
Product Success ◽  
The Relationship ◽  
A Company

In this global marketplace, as products supply grow, product life cycles are shortened and consumer loyalty is declining. It is more important than ever for companies to bring new products to market in less time and periodically. This article examines the Lithuanian cosmetics industry and what difficulties a company face when introducing a new product to the market. The cosmetics industry in Lithuania is reviewed and the product development process is analyzed. Identify the factors of a successful product and the relationship between them. The paper presents the results of the surveyed companies involved in the development of cosmetics industry products. The reasons and key factors influencing product success are identified. Based on the results of the study, a model for the development of new products for the cosmetics industry is presented and conclusions and suggestions are presented.

How to successfully introduce concurrent engineering into new product development?

2020 ◽  
pp. 1063293X2096792
Author(s):  
Lidija Rihar ◽  
Tena Žužek ◽  
Janez Kušar
Keyword(s):  
Project Management ◽  
Product Development ◽  
New Product Development ◽  
Concurrent Engineering ◽  
Development Time ◽  
New Products ◽  
New Product ◽  
Low Costs ◽  
A Company ◽  
Reduced Time

Today, three conditions are crucial for a company to be competitive on the market: quality, reduced time and low costs for the development of new products. The paper shows how companies developing new products (NPD) for the market can successfully implement concurrent engineering as an improvement of project management, in order to reduce product development time and costs and to ensure the quality expected by customers. The methodology presented in this paper is based on three main pillars of knowledge: project management, teamwork and concurrent engineering. The methodology provides a step-by-step guideline for the introduction of concurrent engineering in a company. This paper also presents the results of 10 Slovenian companies where this methodology has been tested on 20 pilot projects. The results show that managed projects upgraded with the principles of concurrent engineering lead to cost reduction, shorter development time and fewer discrepancies.

scholarly journals A novel Based-Approach Composed of Clustering Algorithm & Cosine Similarity for Products Recommendation

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Collaborative Filtering ◽  
Clustering Algorithm ◽  
Recommendation System ◽  
Cosine Similarity ◽  
New Approach ◽  
System A ◽  
Weak Points ◽  
Cosine Similarity Measure ◽  
High Level ◽  
Content Based Filtering

There are huge tons of transactions being accomplished online every day. This implies that ecommerce is facing the problem of data and information overloads. While customers are shopping via websites, they spend a lot of time to search for the required products based on their needs. This problem can easily be alleviated by having an accurate recommendation system based on a strong algorithm and confident measures in this regard. There are two main techniques for products recommendation; content-based filtering and collaborative filtering. If one of these two techniques implemented on the e-commerce system, a lot of limitations and weak points will appear. This paper aims at generating an optimal list of product, which, in turn, generates an accurate and reliable list of items. The new approach is composed of three components; clustering algorithm, user-based collaborative filtering, and the Cosine similarity measure. This approach implemented using a real dataset of past experienced users. The accuracy of the search results is a matter to users, it recommends the most appropriate products to users of the e-commerce website. This approach shows trustworthy results and achieved a high level of accuracy for recommending products to users.

NEW PRODUCT DEVELOPMENT–INDUSTRY APPROACH1

1970 ◽  
Vol 33 (10) ◽  
pp. 464-480
Author(s):  
William F. Stoll
Keyword(s):  
Research And Development ◽  
New Product Development ◽  
New Technology ◽  
New Products ◽  
New Product ◽  
Market Place ◽  
Development Activity ◽  
A Company ◽  
Product Concepts ◽  
Changing Society

Vitality of our economy today stems in part from industry's activity in new products. Industries content to rest on past accomplishments have found themselves in an unfavorable competitive position. In our changing society we find changing needs. What is good for today would not have met the needs of an earlier time nor will it be sufficient for a future day. This is the philosophy which is necessary for corporate survival in our rapidly changing society. New product activity may be merely innovation of old product concepts but sufficiently new to warrant research and development activity and development expenditures. As new technology develops, new product concepts which were unfeasible become reality. Organization within a company, necessary for successful development of new products, is complex. Marketing, accounting, production, and research and development efforts must be coordinated to implement the introduction of a new product. New product activity is hazardous for there are many pitfalls. Failures are common in the market place; however, the rewards are great for the creator of a successful products.

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