Andere Kunden interessierten sich auch für
![Personalized Task Recommendation in Crowdsourcing Systems]( "Personalized Task Recommendation in Crowdsourcing Systems")
Personalized Task Recommendation in Crowdsourcing Systems37,99 €![Interest Based Collaborative Filtering Recommendation Engine]( "Interest Based Collaborative Filtering Recommendation Engine")
Interest Based Collaborative Filtering Recommendation Engine29,99 €![Hotel Recommendation System using Hadoop and Sentiment Analysis]( "Hotel Recommendation System using Hadoop and Sentiment Analysis")
Hotel Recommendation System using Hadoop and Sentiment Analysis39,99 €![Multi-Collaborative Filtering Trust Network For Online Recommendation]( "Multi-Collaborative Filtering Trust Network For Online Recommendation")
Multi-Collaborative Filtering Trust Network For Online Recommendation39,99 €![Recommendation System in Education]( "Recommendation System in Education")
Recommendation System in Education35,99 €![How to Design a Simple Recommendation System for any Large Database]( "How to Design a Simple Recommendation System for any Large Database")
How to Design a Simple Recommendation System for any Large Database42,99 €![A Combinatorial Approach for Movie Recommendation System]( "A Combinatorial Approach for Movie Recommendation System")
A Combinatorial Approach for Movie Recommendation System40,99 €
In this work, a study of personalized news filtering and recommendation systems is presented. An advance K-NN algorithm and its applicability in solving recommendation problems is proposed, a Chi-square statistics based (X2SB) version of the K-NN algorithm is proposed. The new X2SB-KNN algorithm can reduce run-time and increases execution speeds through the use of critical X2 value. The recommendation system can overcome scalability problem through Real-Time pattern discovery and online pattern matching. It can also alleviate information overloading and computational complexity problems common with many existing recommendation algorithms. A novel feature selection technique called Fuzzy expert based (FEB) feature selection technique is also proposed, this method is used at data pre-processing stage to select the best feature for the classification and recommendation system. An In-house Java program was developed to implement the (X2SB-KNN) classifier on an experimental website. Performance comparison between the proposed system, the Euclidean distance K-NN and Naïve Bayesian methods shows that the (X2SB-KNN) classifier can outperform the other methods studied.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.