By Topic

Searching the Long Tail of Social Media Streams on the Web

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

Information is increasingly being distributed in the form of dynamic streams instead of static web pages. It began with news RSS feeds, but with the emergence of social media services such as twitter and facebook, now encompasses instant status updates as well as shared links to various types of web content. While one of the challenging tasks in using such stream based services is to search quality streams of interests, existing work has mainly focused on the retrieval models for individual posts or classification frameworks for blogs, leaving the problems arising in building a dedicated stream search engine in real-world settings largely unexplored. This paper presents a novel stream search engine, named FeedMil, that can satisfy the need for retrieving quality streams of topical relevance for the purpose of subscription. Through addressing the issues unique to the stream search problem, FeedMil is able to give a new search experience that is focused on quality and topic relevance beyond just a sim-ple query matching, enabling users to quickly discover high quality but less popular streams located in the long tail of millions of streams.

Published in:

IEEE Intelligent Systems  (Volume:PP ,  Issue: 99 )