TAG-BASED VISUAL AND FUNCTIONAL CHARACTERISTIC OF PRODUCTS USING SVM-CLASSIFICATION
Dr. Kanchana JS
, Sanjay M , Santhosh Kumar R , Sathish Chockalingam R
Fine-grained, Modeling, Support Vector Machine (SVM), Visual Aspects, Functional Characteristics
Recommender systems have become an important tool which can help users to select the information of interest in many web applications such as social networks, e-commerce, online reading and so on. Nevertheless, the decision-making process of users is highly complex, not only dependent on the personality and preference of a user, but also complicated by the characteristics of a specific product. This work, focus on fine-grained modeling of product characteristics to improve recommendation quality. Specifically, the proposed system first divides a product’s characteristics into visual and functional aspects which means the visual appearance and functionality of the product. One insight is that, the visual characteristic is very important for products of visually-aware domain, while the functional characteristic plays a more crucial role for visually non-aware domain. To address technical challenge, computationally efficient classification algorithm based on Support Vector Machine (SVM) will be devised. Furthermore, the system provides an online updating procedure of the algorithm, shedding some light on how to adapt the method to real-world recommendation scenario where data continuously streams in. Extensive experiments on real-world datasets demonstrate the effectiveness of the proposed system.
"TAG-BASED VISUAL AND FUNCTIONAL CHARACTERISTIC OF PRODUCTS USING SVM-CLASSIFICATION", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.7, Issue 5, page no.271 - 274, May-2022, Available :https://ijsdr.org/papers/IJSDR2205052.pdf
Volume 7
Issue 5,
May-2022
Pages : 271 - 274
Paper Reg. ID: IJSDR_200330
Published Paper Id: IJSDR2205052
Downloads: 000347214
Research Area: Information Technology
Country: Madurai, Tamil Nadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
