NDLI: Information processing in social networks

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Information processing in social networks

Content Provider	ACM Digital Library
Author	Chen, Ming-Syan
Abstract	In the current social network, a user may have hundreds of friends and find it very time consuming to categorize and tag every friend manually. When a user is going to initiate an activity by issuing a corresponding query, he/she needs to consider the relationship among candidate attendees to find a group of mutually close friends. Meanwhile, he/she also needs to consider the schedule of candidate attendees to find an activity period available for all attendees. It would certainly be desirable if the efficiency of such process is improved. In this talk, information processing in social networks will first be reviewed in three phrases, namely (i) from content to social relationship, (ii) mining on social relationship, and (iii) from social relationship to content organization. In addition, we shall present an effective procedure which helps a user to organize an event with proper attendees with minimum total social distance and commonly available time. Moreover, it is noted that the information retrieved from the social networks is also able to facilitate those user-dependent and human-centric services. In light of this, we shall explore the quality of recommendation through incorporating the notion of social filtering and collaborative filtering. Finally, it is recognized that the cloud computing has offered many new capabilities of storing and processing huge amounts of heterogeneous data in social networks. In view of this, we shall also examine how this paradigm shift will affect the information processing in social networks.
Starting Page	1403
Ending Page	1403
Page Count	1
File Format	PDF MP4
ISBN	9781450314626
DOI	10.1145/2339530.2339747
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-08-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Recommendation systems Social network
Content Type	Audio Text
Resource Type	Article

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