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Добірка наукової літератури з теми "Flipkart"

Автор: Grafiati

Опубліковано: 6 вересня 2023

Оновлено: 11 вересня 2023

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Статті в журналах з теми "Flipkart"

Uttam, Yeramalla. "Aspect-Based Sentiment Analysis on Flipkart Data." International Journal for Research in Applied Science and Engineering Technology 11, no. 5 (May 31, 2023): 5498–503. http://dx.doi.org/10.22214/ijraset.2023.52620.

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Abstract: This research In this paper, an Aspect-Based Sentiment Assessment (ABSA) model using the The Long Short-Term Memory (LSTM) network for analyzing info on Flipkart sentiment The suggested model seeks to identify and extract certain elements of a product or service, as well as to characterise their related sentiment polarity as positive, negative, or neutral. On a Flipkart dataset that is open to the public, experiments were run to assess the effectiveness of the suggested model. The LSTMbased ABSA model surpasses other baseline models, according to the results, achieving an accuracy of above 90%. The suggested approach is also capable of locating and extracting the key features of a good or service that influence consumers' opinions. This research provides a valuable contribution to the field of sentiment analysis on Flipkart data, and has significant practical implications for Flipkart companies seeking to improve customer satisfaction and loyalty

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Kalakata, Aishwarya, Apoorv Anand, and Pranav Saxena. "Flipkart : Driving Ecommerce During COVID-19." Management Dynamics 21, no. 1 (April 21, 2022): 7–13. http://dx.doi.org/10.57198/2583-4932.1005.

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Tiwari, Sadhana. "Impact of COVID -19 Era on Supply Chain Management and Logistics of Flipkart Company." VEETHIKA-An International Interdisciplinary Research Journal 8, no. 4 (December 31, 2022): 25–27. http://dx.doi.org/10.48001/veethika.2022.08.04.005.

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Supply chain management has restructured how a business can be accomplished not only in India but also throughout the world. Currently Indian having over 500 million internet user which secured the 2nd position in the world after China. The hefty number of internet user sky rocketed E retailing market in India with consumer preferences. Flipkart is one of the big names in E retiling market of India getting over 10000 orders per day. The aim of this research paper to do a deep study of supply chain management and logistics that how Flipkart making the goods available to the consumer at distinct location through over India in given period of time at a minimal cost. Modern technology and network they have implemented over the years to run smooth operations and take a glance at impact of COVID -19 on E commerce business with reference to Flipkart

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Malhotra, Gunjan, and Ranjana Aggarwal. "GROWTH PROSPECTS OF E-RETAILING IN ELECTRONIC GOODS MARKETS." International Journal of Management & Entrepreneurship Research 1, no. 2 (June 21, 2020): 71–88. http://dx.doi.org/10.51594/ijmer.v1i2.7.

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E-retailing has emerged as a significant player in the retail industry in India. The major cutthroat competition happens between Flipkart, Amazon, and Snap deal. These merchants have a significant competitive edge on electronic goods over other merchants in Indian online shopping portals. Thus, the purpose of this paper is to understand and analyses the universal perception and satisfaction quotient of customers in India concerning to the purchase of electronic goods via these e-commerce merchants. We have used hypothesis testing and analysis of variance to understand customer satisfaction and customer perception. The results show that overall customer satisfaction is the highest for Flipkart. Also, the physical appeal and the quality of the product are the main reasons which impact the customer's perception toward not shopping online. This study is original in itself because it is limited to the purchase of electronic goods only from the emerging e-retail merchants- Flipkart, Snap deal, and Amazon in India.

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Bhaskaran, P. Bala, and Nasheman Bandookwala. "Walmart’s Acquisition of Flipkart: Emerging Paradigm of the Digital Era." South Asian Journal of Business and Management Cases 9, no. 1 (December 18, 2019): 24–39. http://dx.doi.org/10.1177/2277977919881404.

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The case is set around the acquisition of majority shares of Flipkart by Walmart. The case traces the evolution of Flipkart as a startup and explores the context of acquisition by Walmart as well as the strategic fit between the two firms. Technological changes—mainly the proliferation of internet, mobile technology and the consequent digitization—have irretrievable impacts on the retail segment in terms of convergence of on-line and off-line retail and globalization of the markets. The case explores the emerging digitization scenario and its impact on the retail segment as a trigger to the merger process. Flipkart as an Indian startup had to re-incorporate outside India due to policy restrictions on fundraising. The case points to the inadequacies in the Indian policy regime with respect to startup fundraising and differential voting rights. Based on international comparisons, the case triggers discussion on the directions to policy changes if India hopes to create a congenial start-up ecosystem and if the dream of Digital India is to be achieved.

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Mishra, Dr Ashamayee, and Prof Sujata Rath. "Impact of Flash Sales on E-Commerce Industry in India." International Journal for Research in Applied Science and Engineering Technology 10, no. 7 (July 31, 2022): 4794–98. http://dx.doi.org/10.22214/ijraset.2022.46048.

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Abstract: The Indian E-commerce industry is developing multifolds and is relied upon to reach $20 Billion by 2020. This is because of evolving outlook of the Indian clients and simplicity of shopping on the web. Significant Indian E-trade organizations have concocted techniques year on year to draw the clients – Flash deals one among them. Streak deals like Flipkart's – 'Large Billion Day', Amazon. In's-'Incredible Indian Shopping Festival' and Snap deal's-'Unpack Zindagi(Unbox Life)' give limited time deals on profoundly limited costs on significant Indian celebrations. Information identified with the blaze deals of 3 significant online retailers from 2011 to 2016 wiz Flipkart, Snapdeal and Amazon, was gathered from secondary sources to analyze the effect of Flash deals on E trade organizations concerning deals, incomes, site traffic and coordination’s. The analysis will help internet business organizations comprehend the effect of glimmered deals for them.

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Mishra, Dr Somabhusana Janakiballav. "Customer Perception Towards Amazon and Flipkart: A Comparative Analysis." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2147–57. http://dx.doi.org/10.22214/ijraset.2022.42770.

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Abstract: In the world of business, the competition is very high. Every firm, every corporation is in the race to win more and more customers as if they are in a war with one another where one organization attacks another with their strategies and other defends itself. As a world of red ocean where everyone is attacking one another and there’s always danger around them. This war can be distinctively seen in the e-commerce industry. The e-retails websites try to overtake their competitors by adopting new and advanced technologies and strategies to gain better goodwill in the market, which will ultimately increase their web traffic. This study is an insight of the scenario of the two giants e-commerce e-retailers of India. It aims to check the difference between these two giants in India viz. Amazon India and Flipkart under the customer perception towards them. Keywords: Amazon India, Flipkart, E-commerce, Customer Perception

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Kumari, Priyanka. "Comparing Customer Attitude towards Amazon and Flipkart in Patna." International Research Journal on Advanced Science Hub 2, Special Issue ICSTM 12S (December 1, 2020): 4–8. http://dx.doi.org/10.47392/irjash.2020.252.

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Sen, Mr Arpan, and Prof Sneha Kanade. "COMPARATIVE ANALYSISOF AFFILIATE MARKETING PROGRAM OF FLIPKART AND AMAZONINDIA ." International Journal of Social Science and Economic Research 6, no. 4 (April 30, 2021): 1165–73. http://dx.doi.org/10.46609/ijsser.2021.v06i04.004.

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Dutta, Nirankush, and Anil K. Bhat. "Flipkart: journey of an Indian e-commerce start-up." Emerald Emerging Markets Case Studies 4, no. 7 (November 26, 2014): 1–14. http://dx.doi.org/10.1108/eemcs-03-2014-0064.

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Subject area Principles of management, Marketing, Finance, Strategy, Supply Chain Management, Entrepreneurship. Study level/applicability Master's Degree level courses, after students have been taught most of the basics related to management, marketing, finance, strategy, supply chain management and entrepreneurship. Case overview Founded in 2007 with an initial investment of less than USA $10,000, Flipkart has come a long way to become the largest E-commerce player in India with a registered user base of 9.6 million and valued at USA $1.6 billion. Efficient use of various marketing strategies has catapulted the company to its success. Till now, they have overcome most of the hurdles successfully. However, a lot needs to be discussed to find out ways to meet the challenges thrown by its competitors, to maintain its supremacy over other online e-retailers and continue its exponential growth to meet USA $1 billion sales by 2015. Expected learning outcomes After discussion of the case study, the student should be able to appreciate general business processes and develop basic analytical skills to resolve challenges faced by a fast-growing online start-up company in an emerging country like India. At the end, the students should be able to prepare a marketing plan for their own business within a stipulated budget. Supplementary materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

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Більше джерел

Дисертації з теми "Flipkart"

YADAV, MOHIT PRAKASH. "A STUDY ON E-COMMERCE INDUSTRY WITH REFERENCE TO FLIPKART AND AMAZON." Thesis, 2019. http://dspace.dtu.ac.in:8080/jspui/handle/repository/19658.

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India’s e-commerce market, dominated by Flipkart Pvt. Ltd and Amazon.com Inc., can potentially grow more than fourfold to $150 billion by 2022, fuelled by rising incomes and a surge in internet users, according to a latest report. During the period, the size of India’s middle-class is expected to swell to 540 million from 380 million in 2017, showed the report by software industry lobby group Nasscom and consulting firm PwC India. The e-commerce market was pegged at $36 billion last year. “A ‘Make-for-India’ solution approach along with conducive policy environment can potentially make e-commerce a $150 billion market by 2022 with a globally leading compounded annualized growth rate of 35%. The number of internet users is expected to nearly double to 850 million in five years from 450 in 2017, the study showed. Of the total, 150 million users are expected to transact digitally and will emerge mainly from tier-2 and 3 cities with diverse language choices, payment modes and products.

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Garg, Surya Kant. "Migrating VM Workloads to Containers: Issues and Challenges." Thesis, 2019. https://etd.iisc.ac.in/handle/2005/5100.

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Modern day enterprises are adopting virtualization to leverage the benefits of improved server utilization through workload consolidation. Server consolidation provides this benefit to enterprise applications as many of these do not exercise all the system resources to their full capacities, all the time. But co-hosting multiple applications together leads to several challenges including regulating resource sharing, enforcing isolation, minimizing interference etc. To address these challenges, several solutions emerged namely hypervisor based system virtual machines (VMs) and process virtualization mechanisms like containers. Both of these system virtualization techniques have their advantages and disadvantages. Hypervisors abstracts the ISA (Instruction Set Architecture) layer and allow multiple guest operating systems to run simultaneously in isolated environments called virtual machines. On the other hand process virtual machines like container technology abstract operating system layer and use the operating system kernel features such as namespaces, cgroups and apparmor to control resource sharing and provide isolation. Containers offer better workload consolidation than VMs as they have lower memory footprint and faster provisioning time. This enables data centers to handle more workload with existing hardware for applications that can be consolidated using containers. This work explores containers as constructs for workload consolidation and explores issues and challenges in this space. It also exposes concerns while moving workloads from VMs to containers. Containerisation of workloads throws up several challenges that need to be addressed while moving from VMs. Containers share the host OS kernel and hence only workloads with same OS dependency can be co-hosted together. Further, sharing of OS resources such as kernel space data structures, process ids, file descriptors and network stack by co-hosted containers often results in interference and performance hit for applications. In the first part we use OS level micro-benchmarks to identify the cause and symptoms of the bottlenecks and interference visible on the applications co-hosted inside containers. We also identify the key metrics that can be used to measure such concerns with a view to monitor the changes in workload requirements and dynamically place containers to achieve desired isolation and performance. This study is carried out using real-life retail e-commerce workloads of M/s Flipkart hosted in their private data center. Key advantage for such private cloud workloads is that majority of these applications are naturally developed on same OS platforms which gives a strong motivation to use containers for consolidating them. In the second part of the work we look at constructs for managing the elastic scaling of the containerised workloads. It is observed that majority (more than 70\%) of the Flipkart's workloads are stateless which allows seamless cloning of containers across data centers. We leverage this capability through in-kernel load balancing and horizontal scaling to adjust to dynamic workload variation. E-commerce workloads in Flipkart data center exhibit seasonality and show similar workload variations everyday. These variations can be predicted using Seasonal ARIMA model with minimal errors. Containers are light weight in terms of resource footprint as compared to VMs and can be subjected to frequent vertical scaling without any overhead. Vertical scaling offers benefits of increased performance without loss of service or migration overhead and thus provide better elasticity. However, vertical scaling is feasible only based on idle resources available on the platform on which the container is hosted. With adaptive container placement strategies we can identify potential containers that can be dynamically migrated for creating necessary idle resources to enable vertical scaling for the desired containers. It compliments vertical scaling by filling the gaps to utilize idle resources or vacate the required resources for enabling vertical scaling. Exploiting seasonality, offered by workloads, resources can be provisioned proactively. We observe that predictive scaling reduces SLA violations as compared to reactive scaling by allocating required resources in advance. While in arbitrarily varying workloads, when future requirements cannot be predicted, proactive scaling cannot be used. We show that adjusting to variation in workloads dynamically by provisioning and de-provisioning resources automatically, allocated to containers, reduced average resource requirement as compared to fixed resource allocation. It enables us to consolidate more applications on the existing capacity.

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Книги з теми "Flipkart"

Flipka. Booktrope Editions, 2013.

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Частини книг з теми "Flipkart"

Chakraborty, Sourav, Yagiz Oktay Deniz, and Shahd Omari. "A Comprehensive Analytical Study of the Walmart-Flipkart Deal – Mergers and Acquisitions." In Interdisciplinary Research in Technology and Management, 152–59. London: CRC Press, 2021. http://dx.doi.org/10.1201/9781003202240-25.

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Gupta, Sachin, Shreya Singhvi, and Giuseppe Granata. "Assessing the Impact of Artificial Intelligence in e-Commerce Portal: A Comparative Study of Amazon and Flipkart." In Industry 4.0 and the Digital Transformation of International Business, 173–87. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7880-7_10.

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Joshi, Deepal. "Walmart’s Acquisition of Flipkart: A Paradigm Shift in Retail Management Strategy—Current and Future Implications for Various Stakeholders." In Paradigm Shift in Management Philosophy, 65–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-29710-7_4.

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Ganguly, Pushpita, Giriraj Parihar, and M. Sivagami. "Real-Time Big Data Analysis Using Web Scraping in Apache Spark Environment: Case Study—Mobile Data Analysis from Flipkart." In Artificial Intelligence and Technologies, 177–85. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6448-9_20.

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Chanda, Ruby S., Vanishree Pabalkar, and Risita Gupta. "Analysis of the strategies of e-commerce giant FLIPKART to overcome COVID-19 crisis and corresponding impact on consumer buying behaviour." In Interdisciplinary Research in Technology and Management, 98–104. London: CRC Press, 2023. http://dx.doi.org/10.1201/9781003358589-14.

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Kanore, Lalit, and Priti Masatkar. "Never Flip Our Cart—We Are ‘Flipkart’." In Indian Business Case Studies Volume III, 163–68. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192869395.003.0018.

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Abstract Flipkart is not an Indian company since it is registered in Singapore and majority of its shareholders are foreigners. Because foreign companies are not allowed to do multi-brand e-retailing in India, Flipkart sells goods in India through a company called WS Retail. Other third-party sellers or companies can also sell goods through the Flipkart platform. Flipkart now employs more than 15,000 people. Flipkart allows payment methods such as cash on delivery, credit or debit card transactions, net banking, e-gift voucher, and card swipe on delivery. On 15 September 2007, Sachin Bansal and Binny Bansal (not related) started Flipkart as an online bookstore. The two had known each other since 2005 when they attended the Indian Institute of Technology Delhi (IIT-Delhi) together and were colleagues at Amazon briefly. Eleven years later, the world’s largest retailer, Walmart, has agreed to buy a controlling stake in the company, Softbank chief executive officer Masayoshi Son said today (09 May). Flipkart’s journey has been nothing short of a roller-coaster ride. The company went from record-breaking investments and an acquisition spree to failed business experiments and devaluations—only to bounce back.

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Pachpande, Sandeep, Asha Pachpande, and J. A. Kulkarni. "The ‘Walkart’ of India." In Indian Business Case Studies Volume I, 157—C17.P59. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192869371.003.0017.

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Abstract US retail giant Walmart has signed a definitive agreement to acquire a 77% stake in India’s largest e-commerce marketplace Flipkart with an investment of around $16 billion, making it the largest transaction in the history of the online retail space globally. The deal, which wiped away $10 billion of Walmart’s market capitalization as investors reacted negatively in early morning trade on the New York Stock Exchange, stands out for several exits. The biggest was Sachin Bansal selling his entire 5.96% stake for $1.23 billion and parting ways with Flipkart that he had founded in 2007 along with a friend from IIT, Binny Bansal (not related). Sachin was nowhere around at the Flipkart campus when the Walmart top team led by CEO Doug McMillon addressed employees in a town hall meeting. Another significant exit is that of Soft Bank, the largest investor in Flipkart. In a strange coincidence, the deal, valuing Flipkart at $20.8 billion, was announced to the world by Soft Bank Chief Executive Masayoshi Son in a webinar with investors hours before Walmart did so. He also confirmed that Soft Bank would get about $4 billion from its $2.5-billion investment in Flipkart last August. Flipkart’s valuation at $20.8 billion is a 75% increase over its previous valuation in the range of $11–12 billion last August. Out of the $16-billion investment, Walmart will put in $2 billion in new equity funding, while the rest will be utilized to acquire stakes of existing investors in the Bengaluru-based company. The case study focuses on Effect of regulatory restrictions in Indian Ecommerce Markets for Global MNCs.

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Kumari, Meenu. "Marketing Strategies in the Era of COVID-19." In Advances in Marketing, Customer Relationship Management, and E-Services, 192–202. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-4496-2.ch012.

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The way consumers used to think about making purchases is totally changed in the period of COVID-19. Due to the coronavirus, consumers are less likely to visit a physical store to buy almost anything. Consumers are being forced to change their shopping behaviour. People are buying products online that they never have before. It could not have been possible if these e-commerce platforms were not available. One of these major platforms is Flipkart, which is grabbing a larger share of the e-commerce market. However, with the announcement of nationwide lockdown, everything came to a standstill at Flipkart. The company accepted the challenge and came out with practical solutions. This chapter analyses the strategies adopted by Flipkart and offers suggestions for other online/offline retailers to overcome this unfavourable time.

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Casanova, Lourdes, Peter Klaus Cornelius, and Soumitra Dutta. "Flipkart and the Race to the Top of Indian e-Commerce." In Financing Entrepreneurship and Innovation in Emerging Markets, 133–57. Elsevier, 2018. http://dx.doi.org/10.1016/b978-0-12-804025-6.00006-x.

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Singh, Surabhi. "Affiliate Marketing and Customer Satisfaction." In Driving Traffic and Customer Activity Through Affiliate Marketing, 1–10. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2656-8.ch001.

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The different tools used in digital marketing are meant to increase the web traffic. One of the important components is Affiliate Marketing. This chapter will bring huge transitions in industry of digital marketing. The affiliate marketing has benefits of increasing customer satisfaction and value driven efficiency in any organization. The study of affiliate programs need to be activated in organizations in order to exploit the potential of same. The companies like Amazon, snapdeal, and flipkart are running affiliate programs and the brand of these companies remain unbeatable. The purpose behind affiliate marketing is to use publisher or affiliate website for promotion of merchant's own products. The underlying benefit is its low customer acquisition cost and marketing expenses.

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Тези доповідей конференцій з теми "Flipkart"

Datar, Mayur. "Data Science at Flipkart - An Indian E-Commerce company." In KDD '18: The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3219819.3219939.

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Kanakamedala, Venkata Chaitanya, Sonal Hukampal Singh, and Rishitha Talasani. "Sentiment Analysis of Online Customer Reviews for Handicraft Product using Machine Learning: A Case of Flipkart." In 2023 International Conference for Advancement in Technology (ICONAT). IEEE, 2023. http://dx.doi.org/10.1109/iconat57137.2023.10080169.

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Nadkarni, Prajit, and Narendra Varma Dasararaju. "Visually Similar Products Retrieval for Shopsy." In International Conference on Signal Processing and Vision. Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.122203.

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Visual search is of great assistance in reseller commerce, especially for non-tech savvy users with affinity towards regional languages. Product attributes available in e-commerce have potential for building better visual search systems [2, 20, 29]. We design a visual search system for reseller commerce using a multi-task learning approach and address challenges like image compression, cropping, etc, faced in reseller commerce. Our model consists of three tasks: attribute classification, triplet ranking and variational autoencoder (VAE). We introduce an offline triplet mining technique which utilizes information from multiple attributes to capture relative order within data. This technique displays better performance compared to traditional triplet mining [27] baseline. We compare and report incremental gain achieved by our unified multi-task model over each individual task separately. The efsfectiveness of our method is demonstrated using in-house dataset of images from the Lifestyle business-unit of Flipkart. To efficiently retrieve images in production, we use Approximate Nearest Neighbor (ANN) index.

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