@inproceedings{0ea3513f1a5644a88abf69337710f676,
title = "Personalized activity streams: Sifting through the {"}river of news{"}",
abstract = "Activity streams have emerged as a means to syndicate updates about a user or a group of users within a social network site or a set of sites. As the flood of updates becomes highly intensive and noisy, users are faced with a {"}needle in a haystack{"} challenge when they wish to read the news most interesting to them. In this work, we study activity stream personalization as a means of coping with this challenge. We experiment with an enterprise activity stream that includes status updates and news across a variety of social media applications. We examine an entity-based user profile and a stream-based profile across three dimensions: people, terms, and places, and provide a rich set of results through a user study that combines direct rating of the objects in the profile with rating of the news items it produces.",
keywords = "activity streams, news feed, personalization, real-time web, recommender systems, social media, social networks, social streams, Twitter",
author = "Ido Guy and Inbal Ronen and Ariel Raviv",
year = "2011",
month = dec,
day = "6",
doi = "10.1145/2043932.2043966",
language = "English",
isbn = "9781450306836",
series = "RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems",
pages = "181--188",
booktitle = "RecSys'11 - Proceedings of the 5th ACM Conference on Recommender Systems",
note = "5th ACM Conference on Recommender Systems, RecSys 2011 ; Conference date: 23-10-2011 Through 27-10-2011",
}