scholarly journals Extended Collaborative Filtering Technique for Mitigating the Sparsity Problem

2016 ◽  
Vol 11 (5) ◽  
pp. 631 ◽  
Author(s):  
Keunho Choi ◽  
Yongmoo Suh ◽  
Donghee Yoo
Keyword(s):  
Collaborative Filtering ◽  
Online Shopping ◽  
Recommendation Systems ◽  
Shopping Mall ◽  
Similarity Function ◽  
Shopping Malls ◽  
Transaction Data ◽  
User Similarity ◽  
Sparsity Problem ◽  
Rating Information

Many online shopping malls have implemented personalized recommendation systems to improve customer retention in the age of high competition and information overload. Sellers make use of these recommendation systems to survive high competition and buyers utilize them to find proper product information for their own needs. However, transaction data of most online shopping malls prevent us from using collaborative filtering (CF) technique to recommend products, for the following two reasons: 1) explicit rating information is rarely available in the transaction data; 2) the sparsity problem usually occurs in the data, which makes it difficult to identify reliable neighbors, resulting in less effective recommendations. Therefore, this paper first suggests a means to derive implicit rating information from the transaction data of an online shopping mall and then proposes a new user similarity function to mitigate the sparsity problem. The new user similarity function computes the user similarity of two users if they rated similar items, while the user similarity function of traditional CF technique computes it only if they rated common items. Results from several experiments using an online shopping mall dataset in Korea demonstrate that our approach significantly outperforms the traditional CF technique.

scholarly journals Personalized Suggestion For Music Based On Collaborative Filtering

2020 ◽  
Vol 9 (05) ◽  
pp. 25047-25051
Author(s):  
Aniket Salunke ◽  
Ruchika Kukreja ◽  
Jayesh Kharche ◽  
Amit Nerurkar
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Cold Start ◽  
The Internet ◽  
Music Recommendation ◽  
User Similarity ◽  
Content Based Filtering ◽  
Music Recommendation System ◽  
Cold Start Problem

With the advancement of technology there are millions of songs available on the internet and this creates problem for a person to choose from this vast pool of songs. So, there should be some middleman who must do this task on behalf of user and present most relevant songs that perfectly fits the user’s taste. This task is done by recommendation system. Music recommendation system predicts the user liking towards a particular song based on the listening history and profile. Most of the music recommendation system available today will give most recently played song or songs which have overall highest rating as suggestions to users but these suggestions are not personalized. The paper purposes how the recommendation systems can be used to give personalized suggestions to each and every user with the help of collaborative filtering which uses user similarity to give suggestions. The paper aims at implementing this idea and solving the cold start problem using content based filtering at the start.

scholarly journals Renaissance of Suburban Shopping

2021 ◽  
Author(s):  
Paul Limcangco
Keyword(s):  
Architectural Design ◽  
Online Shopping ◽  
Shopping Mall ◽  
Shopping Malls ◽  
Contemporary Culture ◽  
Online Retail ◽  
Architectural Form ◽  
One Dimensional ◽  
Online Channel ◽  
The Many

<p><b>This thesis interrogates Eastgate Mall in Christchurch, to develop a revived architectural design for the neglected shopping mall. Shoppers are becoming increasingly familiar with online shopping, with many now preferring this channel over the physical (Blázquez, 2014, p. 109). While shoppers are offered convenience and often a larger range of goods, malls now appear to be spaces solely for urgent shopping (Rouz, 2014, p. 1881). This has decreased footfall and lowered people’s tendency to appear in these spaces for recreational and non- economical purposes. Shopping malls like Eastgate are declining as the “centreless centrepieces of suburbs” that deny surrounding communities their diversity, and economic and cultural prosperity (Chavan et al., 2007, p. 59).</b></p> <p>This thesis argues that current architecture widely used in shopping malls is detrimental to retailers—particularly small local businesses. It acknowledges that retail spaces will no longer be solely for the sale of goods. Therefore, it proposes to enrich the showing and selling of experiences as a way to revive Eastgate Mall and further differentiate its physical retail spaces from those in the online channel. By enriching shoppers’ experiences, the mall can embody the contemporary culture of transience and immediacy that shift its retail spaces away from the static and one-dimensional to the multi-functional and hybrid.</p> <p>The proposed design aims to sever ties with traditional expectations of shopping malls, thereby conforming to the idea that,“[I]f closed spaces [ . . . ] truly perpetuate its society[, we must] look beyond the strictures of architectural form to understand the many attributes of what these spaces represent and what they can be” ( Jewell, 2016, p. 103).</p> <p>Overall, the research in response to the current stagnation of Eastgate and rising popularity of online shopping proposes an experiential mall design; it seeks to differentiate the physical from online retail spaces and contribute to fostering the sense of community that surrounding suburbs are strengthening.</p>

scholarly journals Recommendation Framework Combining User Interests with Fashion Trends in Apparel Online Shopping

2019 ◽  
Vol 9 (13) ◽  
pp. 2634 ◽  
Author(s):  
Ok ◽  
Lee ◽  
Kim
Keyword(s):  
Random Walk ◽  
Collaborative Filtering ◽  
Real World ◽  
Large Scale ◽  
Online Shopping ◽  
Experimental Studies ◽  
Empirical Evaluation ◽  
Personalized Recommendation ◽  
User Interests ◽  
Sparsity Problem

Although fashion-related products account for most of the online shopping categories, it becomes more difficult for users to search and find products matching their taste and needs as the number of items available online increases explosively. Personalized recommendation of items is the best method for both reducing user effort on searching for items and expanding sales opportunity for sellers. Unfortunately, experimental studies and research on fashion item recommendation for online shopping users are lacking. In this paper, we propose a novel recommendation framework suitable for online apparel items. To overcome the rating sparsity problem of online apparel datasets, we derive implicit ratings from user log data and generate predicted ratings for item clusters by user-based collaborative filtering. The ratings are combined with a network constructed by an item click trend, which serves as a personalized recommendation through a random walk. An empirical evaluation on a large-scale real-world dataset obtained from an apparel retailer demonstrates the effectiveness of our method.

scholarly journals Online Shopping Malls: Behavioral Impacts of Short- and Long-term Store Loyalty

2018 ◽  
Vol 11 (3) ◽  
pp. 10
Author(s):  
Yukihiro Miwa ◽  
Makoto Morisada ◽  
Wirawan D. Dahana
Keyword(s):  
Time Trend ◽  
Online Shopping ◽  
Shopping Mall ◽  
Store Loyalty ◽  
Type Ii ◽  
Shopping Malls ◽  
Purchase Incidence ◽  
Negative Effect ◽  
Short And Long Term

This study addresses how customers develop loyalty toward focal stores within an online shopping mall, and how this construct affects behavioral mall loyalty in both the short- and long-term. We employ a type II Tobit model to dynamically capture the short- and long-term impacts of store loyalty on purchase incidence and purchase amount. We further embed this model within a model of store loyalty formation to elucidate its driving factors. Applying the models to purchase history data of new customers in an online shopping mall, we observe that store loyalty has an immediate negative effect on purchase incidence; however, given a purchase, this variable increases the purchase amount in the long-term. Additionally, the formation of store loyalty appears to be significantly affected by gender, age, cumulative purchase amount, cumulative purchase frequency, and time trend. We discuss the implications of these findings for mall owners in an effort to increase revenue contribution of their tenants.

scholarly journals Developing a Measure for Online Shopping Mall Reputation (OSMR)

2021 ◽  
Vol 13 (7) ◽  
pp. 3818
Author(s):  
Heeseung Yu ◽  
Eunkyoung Han
Keyword(s):  
Customer Service ◽  
Delphi Study ◽  
Structural Equation ◽  
Discriminant Validity ◽  
Online Shopping ◽  
Shopping Mall ◽  
Equation Modeling ◽  
Shopping Malls ◽  
Convergent And Discriminant Validity ◽  
Confirmatory Factor

This study was conducted with the purpose of developing and validating multidimensional reputation criteria for evaluating online shopping malls, which have been growing explosively since the start of the COVID-19 pandemic. A Delphi study was conducted with a group of 31 professionals, and the initial items for online shopping mall reputation were derived from that study. Those items were used to devise a questionnaire that was administered to 531 consumers. Exploratory and confirmatory factor analysis resulted in 17 items based on four factors: reliability, technical skills, customer service, and accessibility. Convergent and discriminant validity were verified between the factors. Finally, structural equation modeling was used to verify the nomological validity of the scale. This online shopping mall reputation scale is expected to provide a standard for companies to effectively manage the reputations of online shopping malls in the future and for consumers to choose online shopping malls they can trust.

A similarity measure based on Kullback–Leibler divergence for collaborative filtering in sparse data

2018 ◽  
Vol 45 (5) ◽  
pp. 656-675 ◽  
Author(s):  
Jiangzhou Deng ◽  
Yong Wang ◽  
Junpeng Guo ◽  
Yongheng Deng ◽  
Jerry Gao ◽  
...  
Keyword(s):  
Collaborative Filtering ◽  
Similarity Measure ◽  
Similarity Measures ◽  
Predictive Performance ◽  
Probability Density Distribution ◽  
User Similarity ◽  
Kl Divergence ◽  
Active User ◽  
Leibler Divergence ◽  
Sparsity Problem

In the neighbourhood-based collaborative filtering (CF) algorithms, a user similarity measure is used to find other users similar to an active user. Most of the existing user similarity measures rely on the co-rated items. However, there are not enough co-rated items in sparse dataset, which usually leads to poor prediction. In this article, a new similarity scheme is proposed, which breaks free of the constraint of the co-rated items. Moreover, an item similarity measure based on the Kullback–Leibler (KL) divergence is presented, which identifies the relation between items based on the probability density distribution of ratings. Since the item similarity based on KL divergence makes full use of all ratings, it owns better flexibility for sparse datasets. The CF algorithm using our proposed similarity scheme is implemented and compared with some classic CF algorithms. The compared results show that the CF using our similarity has better predictive performance. Therefore, our similarity scheme is a good solution for the sparsity problem and has great potential to be applied to recommendation systems.

scholarly journals Consumer reviews analysis on cycling pants in online shopping malls using text mining

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Chunjeong Kim ◽  
Youngjoo Na
Keyword(s):  
Text Mining ◽  
Online Shopping ◽  
Product Information ◽  
Cost Effective ◽  
Shopping Mall ◽  
Accurate Information ◽  
Shopping Malls ◽  
Consumer Awareness ◽  
Difficult Time ◽  
Occurrence Matrix

AbstractThis study was investigated trends and consumer awareness on cycling pants by analyzing the reviews on bib shorts, bib tights, shorts, and tights in online shopping malls using text mining. The reviews and product information on cycling pants from Jan. 2017 to the first half of 2020 were crawled, and a total of 7241 cases were analyzed. The keywords of cycling pants were extracted using a Korean morphological analyzer (KoNLP), calculated to the term-document matrix, and then converted into a co-occurrence matrix. The number of reviews of cycling pants increased by 39% per year, and especially in the first half of 2020, the number of reviews has doubled over compared to the first half of last year. Bib shorts accounted for more than 50% of the number of reviews of cycling pants and received the highest rating, making them the most preferred. Positive reviews on cycling pants appeared 15 times over than that of negative reviews, and most of the cycling pants were evaluated positively. Size and cost-effective appeared as the important keywords both in positive and negative reviews. However, it was found that consumers have a difficult time choosing the size not only in the negative but also in the positive reviews. Pad was the keyword that appeared the most in negative reviews, and it was the most dissatisfied factor in the cycling pants. Therefore, in an internet shopping mall, it is necessary to provide intuitive and accurate information that is easy for consumers to understand about information on the size and pad of the cycle pants.

scholarly journals Renaissance of Suburban Shopping

2021 ◽  
Author(s):  
Paul Limcangco
Keyword(s):  
Architectural Design ◽  
Online Shopping ◽  
Shopping Mall ◽  
Shopping Malls ◽  
Contemporary Culture ◽  
Online Retail ◽  
Architectural Form ◽  
One Dimensional ◽  
Online Channel ◽  
The Many

<p><b>This thesis interrogates Eastgate Mall in Christchurch, to develop a revived architectural design for the neglected shopping mall. Shoppers are becoming increasingly familiar with online shopping, with many now preferring this channel over the physical (Blázquez, 2014, p. 109). While shoppers are offered convenience and often a larger range of goods, malls now appear to be spaces solely for urgent shopping (Rouz, 2014, p. 1881). This has decreased footfall and lowered people’s tendency to appear in these spaces for recreational and non- economical purposes. Shopping malls like Eastgate are declining as the “centreless centrepieces of suburbs” that deny surrounding communities their diversity, and economic and cultural prosperity (Chavan et al., 2007, p. 59).</b></p> <p>This thesis argues that current architecture widely used in shopping malls is detrimental to retailers—particularly small local businesses. It acknowledges that retail spaces will no longer be solely for the sale of goods. Therefore, it proposes to enrich the showing and selling of experiences as a way to revive Eastgate Mall and further differentiate its physical retail spaces from those in the online channel. By enriching shoppers’ experiences, the mall can embody the contemporary culture of transience and immediacy that shift its retail spaces away from the static and one-dimensional to the multi-functional and hybrid.</p> <p>The proposed design aims to sever ties with traditional expectations of shopping malls, thereby conforming to the idea that,“[I]f closed spaces [ . . . ] truly perpetuate its society[, we must] look beyond the strictures of architectural form to understand the many attributes of what these spaces represent and what they can be” ( Jewell, 2016, p. 103).</p> <p>Overall, the research in response to the current stagnation of Eastgate and rising popularity of online shopping proposes an experiential mall design; it seeks to differentiate the physical from online retail spaces and contribute to fostering the sense of community that surrounding suburbs are strengthening.</p>

scholarly journals Shopping mall vs Online Retail- Consumer shopping preference in the city of Bengaluru

2021 ◽  
Vol 9 (11) ◽  
pp. 1400-1406
Author(s):  
Neha Sahay
Keyword(s):  
Consumer Behaviour ◽  
Online Shopping ◽  
Consumer Preference ◽  
Public Spaces ◽  
The United States ◽  
Developing Nations ◽  
Shopping Mall ◽  
Shopping Malls ◽  
Online Retail ◽  
The City

Abstract: Ever since the first fully enclosed and climate controlled mall opened in the United States in 1956 It has caught the fancy of consumers. It revolutionized the way retail was looked at. With everything available under one roof, customers thronged the air-conditioned environments to shop in comfort. Slowly they evolved into a recreation space, with multiplex, food courts, gaming zones which ensured that there was something for everyone in a mall. The replicas were erected all across the world, and embraced with much gusto, as malls became the symbol of urbanization and aspirations for developing nations. In the last two decades or so, India has seen a massive boom in no. and size of a shopping mall. It seemed malls are here to stay even though the high value shoppers were decreasing steadily and the only places you could see crowds were the food courts and the multiplexes, or some large lifestyle stores. The mid and smaller size stores renting out exorbitantly priced floor spaces were starting to wear deserted looks. Then the Covid-19 pandemic hit and forced millions to their homes for months. With shops and malls closed, the online retail exploded and became one of the biggest happening of the last two years. Sitting in comforts of their homes, people were buying food, clothes, electronics, furniture from all over the country, offered to them at an eye watering discount which the physical stores could never match. So has the consumer preference changed in favour of online shopping or malls are still favoured once the lockdown is lifted ?Given the Strong commercial impact that malls have had on Indian retail economy, an attempt was made to understand shopping preference of the consumers in the city of Bengaluru through a questionnaire survey collecting 120 responses. The analysis revealed that consumers still prefer offline shopping for clothes, shoes and accessories. While online shopping is preferred for household items. Groceries, Beauty & cosmetics, Electronics were equally preferred through online or offline mode. Participants were also inclined towards having more open public spaces and sports related facilities in the mall indicating that in Bengaluru malls are also places to socialise and spend quality time together rather than mere shopping spaces. Keywords: E-Commerce, Retailing, Consumer Behaviour, Shopping Preferences, Shopping malls

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