News Feed Filtering with Explanation Using Textual Concepts and Social Contacts
Date Issued
2010
Date
2010
Author(s)
Lin, Jia-Yan
Abstract
In recent years, the amount of information flowing on the internet is raising.
People absorb messages from media and tranfer information to others.
As more applications and web services step involved in our daily life, the affection of information overload spreaded.
Historially, many studies try to deal with this problem by using recommendation system.
That is, recommending users items they might like based on user profiling or content similarity.
However, the importance of sharing information might partially depends on the closeness between users.
Another popular way to solve information overload is to summarize documents.
System gives a general summarization or part of content related to specified keywords.
In this thesis, we investigate if social contact information and summarization help users geting more interested in sharing content.
The summarization for sharing content is based on ConceptNet which stores sematic relations between words.
In addiction, explanations for each sharing contents address the relevance to summarized topics and the strength of social relations with senders.
Experiment was established as a Facebook Application.
The result showed that for users receiving many unimportant sharing content, social contact was hardly to filter out interesting ones out of them.
However, summarization gave users an overview of sharing information and users felt much more interested in them with explanations provided.
Subjects
Social network recommendation
ConceptNet
Type
thesis
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