Research on schedule-based user recommendation model based on improved K-means algorithm
- 13 October 2016
- journal article
- Published by IOS Press in Journal of Computational Methods in Sciences and Engineering
- Vol. 16 (3), 691-700
- https://doi.org/10.3233/JCM-160650
Abstract
Nowadays all kinds of social platforms provide various recommendation services, greatly enriching people's life. In the condition that social platforms have become indispensable tools, people have more to except that the social platforms can provideKeywords
This publication has 10 references indexed in Scilit:
- Personalized recommendation of stories for commenting in forum-based social mediaInformation Sciences, 2016
- Who, Where, When, and WhatACM Transactions on Information Systems, 2015
- TWITOBI: A Recommendation System for Twitter Using Probabilistic ModelingPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- A Feasibility Study on Extracting Twitter Users' Interests Using NLP Tools for Serendipitous ConnectionsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2011
- Recommending twitter users to follow using content and collaborative filtering approachesPublished by Association for Computing Machinery (ACM) ,2010
- Recommendations in Twitter using conceptual fuzzy setsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2010
- Make new friends, but keep the oldPublished by Association for Computing Machinery (ACM) ,2009
- Information Retrieval Oriented Adaptive Chinese Word Segmentation SystemJournal of Software, 2006
- Amazon.com recommendations: item-to-item collaborative filteringIEEE Internet Computing, 2003
- Analysis of recommendation algorithms for e-commercePublished by Association for Computing Machinery (ACM) ,2000