Please wait, while we are loading the content...
Please wait, while we are loading the content...
Content Provider | Directory of Open Access Journals (DOAJ) |
---|---|
Author | Sunkuru Gopal Krishna Patro Brojo Kishore Mishra Sanjaya Kumar Panda Raghvendra Kumar Hoang Viet Long David Taniar Ishaani Priyadarshini |
Abstract | Recommendation System (RS) has been broadly utilized in various areas and discovers product recommendations during an active user interaction in E-Commerce sites. Tremendous growth of users and products in recent years has faced some key challenges. There are numerous online sites that present many decisions to the user at once, which is strenuous. Moreover, finding active user or right product is an important task in RS. Existing works have been proposed to recommend a product by considering user inclination and socio-demographic behaviour. In this paper, we propose a Hybrid Action-Related K-Nearest Neighbour similarity (HAR-KNN) recommender that consolidates the simplicity of hybrid filtering to enrich user behaviour matrix with formation of the vector of features. It will classify the features using race classifiers from both quality and quantity aspects. The proposed approach also addresses the problems of the previous methods to efficiently evaluate user preference on products and balance feature analysis. The K-NN classification method has been qualified online and real-time to find user behaviour data coordinating to a specific user group containing the relationship between the similarity of many users and target users from a huge amount of data. The proposed experimental result is evaluated based on measures such as Mean Absolute Error (MAE), Mean Square Error (MSE) and Root Mean Squared Error (RMSE) with the lowest error of 0.7165, 0.7201 and 0.7322 separately. High predictive measures like Precision (P), Recall (R) and F1 are found to have values 0.8501, 0.2201 and 0.3507 respectively. |
e-ISSN | 21693536 |
DOI | 10.1109/ACCESS.2020.2994056 |
Journal | IEEE Access |
Volume Number | 8 |
Language | English |
Publisher | IEEE |
Publisher Date | 2020-01-01 |
Publisher Place | United States |
Access Restriction | Open |
Subject Keyword | Electrical Engineering. Electronics. Nuclear Engineering Recommendation System (rs) User Behaviour Data Hybrid Filtering K-nn Behavioural Matrix |
Content Type | Text |
Resource Type | Article |
National Digital Library of India (NDLI) is a virtual repository of learning resources which is not just a repository with search/browse facilities but provides a host of services for the learner community. It is sponsored and mentored by Ministry of Education, Government of India, through its National Mission on Education through Information and Communication Technology (NMEICT). Filtered and federated searching is employed to facilitate focused searching so that learners can find the right resource with least effort and in minimum time. NDLI provides user group-specific services such as Examination Preparatory for School and College students and job aspirants. Services for Researchers and general learners are also provided. NDLI is designed to hold content of any language and provides interface support for 10 most widely used Indian languages. It is built to provide support for all academic levels including researchers and life-long learners, all disciplines, all popular forms of access devices and differently-abled learners. It is designed to enable people to learn and prepare from best practices from all over the world and to facilitate researchers to perform inter-linked exploration from multiple sources. It is developed, operated and maintained from Indian Institute of Technology Kharagpur.
Learn more about this project from here.
NDLI is a conglomeration of freely available or institutionally contributed or donated or publisher managed contents. Almost all these contents are hosted and accessed from respective sources. The responsibility for authenticity, relevance, completeness, accuracy, reliability and suitability of these contents rests with the respective organization and NDLI has no responsibility or liability for these. Every effort is made to keep the NDLI portal up and running smoothly unless there are some unavoidable technical issues.
Ministry of Education, through its National Mission on Education through Information and Communication Technology (NMEICT), has sponsored and funded the National Digital Library of India (NDLI) project.
Sl. | Authority | Responsibilities | Communication Details |
---|---|---|---|
1 | Ministry of Education (GoI), Department of Higher Education |
Sanctioning Authority | https://www.education.gov.in/ict-initiatives |
2 | Indian Institute of Technology Kharagpur | Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project | https://www.iitkgp.ac.in |
3 | National Digital Library of India Office, Indian Institute of Technology Kharagpur | The administrative and infrastructural headquarters of the project | Dr. B. Sutradhar bsutra@ndl.gov.in |
4 | Project PI / Joint PI | Principal Investigator and Joint Principal Investigators of the project |
Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon |
5 | Website/Portal (Helpdesk) | Queries regarding NDLI and its services | support@ndl.gov.in |
6 | Contents and Copyright Issues | Queries related to content curation and copyright issues | content@ndl.gov.in |
7 | National Digital Library of India Club (NDLI Club) | Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach | clubsupport@ndl.gov.in |
8 | Digital Preservation Centre (DPC) | Assistance with digitizing and archiving copyright-free printed books | dpc@ndl.gov.in |
9 | IDR Setup or Support | Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops | idr@ndl.gov.in |
Loading...
|