Consummate Approach for Classification and Pattern Matching for a Web usage based Recommendation System

2018 ◽  
Vol 6 (6) ◽  
pp. 826-830
Author(s):  
Hutashan Vishal Bhagat ◽  
Shashi Bhushan ◽  
Sachin Majithia
Keyword(s):  
Pattern Matching ◽  
Recommendation System ◽  
Web Usage

scholarly journals Dynamic Recommendation System Using Web Usage Mining for E-commerce Users

2015 ◽  
Vol 45 ◽  
pp. 60-69 ◽  
Author(s):  
Prajyoti Lopes ◽  
Bidisha Roy
Keyword(s):  
Recommendation System ◽  
Web Usage Mining ◽  
Web Usage

A Movie E-Shop Recommendation Model Based on Web Usage and Ontological Data

2011 ◽  
pp. 51-68
Author(s):  
Andreas Aresti ◽  
Penelope Markellou ◽  
Ioanna Mousourouli ◽  
Spiros Sirmakessis ◽  
Athanasios Tsakalidis
Keyword(s):  
Artificial Intelligence ◽  
User Modeling ◽  
Web Mining ◽  
Recommendation System ◽  
Recommendation Systems ◽  
Model Based ◽  
Web Usage ◽  
One To One ◽  
Online Shops

Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today’s e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling, and profiling setting up a successful recommendation system is not a trivial or straightforward task. This chapter argues that by monitoring, analyzing, and understanding the behavior of customers, their demographics, opinions, preferences, and history, as well as taking into consideration the specific e-shop ontology and by applying Web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users’ interaction, increase its usability, convert users to buyers, retain current customers, and establish long-term and loyal one-to-one relationships.

scholarly journals Ontology Based Web Page Recommendation System

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1373-1376
Keyword(s):  
Recommendation System ◽  
Semantic Information ◽  
Initial Step ◽  
Domain Ontology ◽  
Web Usage Mining ◽  
The Other ◽  
Web Page ◽  
Web Usage ◽  
Content Based Filtering ◽  
Filtering Approach

The emerging web page development requires semantic applications with customized administrations. The proposed methodology presents a customized suggestion framework, which makes utilization of item representations and also client profiles created based on ontology. The domain ontology helps the recommender to improve the personalization: from one perspective, client’s interests are displayed in an increasingly powerful and precise route by applying an area based derivative technique; on the other side, the stemmer algorithm derived content- based filtering approach, gives an evaluation of resemblance among a thing and a client, upgraded by applying a semantic likeliness strategy. Recommender frameworks and web personalize were assumed by Web usage mining as a critical job. The proposed strategy is s successful framework dependent on ontology and web usage mining. Extricating highlights from web reports and building applicable ideas is the initial step of the methodology. At that point manufacture metaphysics for the site exploit the ideas and huge terms separated from reports. As per the semantic similitude of web archives to bunch them into various semantic topics, the distinctive subjects suggest diverse inclinations. The proposed methodology incorporates semantic information into Web Usage Mining and personalization process

An Intelligent Web Recommendation System: A Web Usage Mining Approach

2002 ◽  
pp. 342-350 ◽  
Author(s):  
Hiroshi Ishikawa ◽  
Toshiyuki Nakajima ◽  
Tokuyo Mizuhara ◽  
Shohei Yokoyama ◽  
Junya Nakayama ◽  
...  
Keyword(s):  
Recommendation System ◽  
Web Usage Mining ◽  
Web Usage ◽  
System A
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