Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Content-based book recommending using learning for text categorization
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Principles of data mining
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Discriminative models for information retrieval
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
A tutorial on support vector regression
Statistics and Computing
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Top 10 algorithms in data mining
Knowledge and Information Systems
Query-level loss functions for information retrieval
Information Processing and Management: an International Journal
Why we twitter: understanding microblogging usage and communities
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Do you know?: recommending people to invite into your social network
Proceedings of the 14th international conference on Intelligent user interfaces
Make new friends, but keep the old: recommending people on social networking sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Personalized recommendation of social software items based on social relations
Proceedings of the third ACM conference on Recommender systems
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Document recommendation in social tagging services
Proceedings of the 19th international conference on World wide web
What is Twitter, a social network or a news media?
Proceedings of the 19th international conference on World wide web
Relevance and ranking in online dating systems
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
Discovering users' topics of interest on twitter: a first look
AND '10 Proceedings of the fourth workshop on Analytics for noisy unstructured text data
Characterization of the twitter @replies network: are user ties social or topical?
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Measuring message propagation and social influence on Twitter.com
SocInfo'10 Proceedings of the Second international conference on Social informatics
Modeling Information Diffusion in Implicit Networks
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Who says what to whom on twitter
Proceedings of the 20th international conference on World wide web
Empirical study of topic modeling in Twitter
Proceedings of the First Workshop on Social Media Analytics
Comparing twitter and traditional media using topic models
ECIR'11 Proceedings of the 33rd European conference on Advances in information retrieval
Analyzing user modeling on twitter for personalized news recommendations
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
An exploration of improving collaborative recommender systems via user-item subgroups
Proceedings of the 21st international conference on World Wide Web
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
| Hi-index | 0.00 |
Nowadays, micro-blogging systems like Twitter have become one of the most important ways for information sharing. In Twitter, a user posts a message (tweet) and the others can forward the message (retweet). Mention is a new feature in micro-blogging systems. By mentioning users in a tweet, they will receive notifications and their possible retweets may help to initiate large cascade diffusion of the tweet. To enhance a tweet's diffusion by finding the right persons to mention, we propose in this paper a novel recommendation scheme named as whom-to-mention. Specifically, we present an in-depth study of mention mechanism and propose a recommendation scheme to solve the essential question of whom to mention in a tweet. In this paper, whom-to-mention is formulated as a ranking problem and we try to address several new challenges which are not well studied in the traditional information retrieval tasks. By adopting features including user interest match, content-dependent user relationship and user influence, a machine learned ranking function is trained based on newly defined information diffusion based relevance. The extensive evaluation using data gathered from real users demonstrates the advantage of our proposed algorithm compared with the traditional recommendation methods.