NDLI: PIXS: programmable intelligence for cross-platform socialization

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PIXS: programmable intelligence for cross-platform socialization

Content Provider	ACM Digital Library
Author	Hu, Pili Lau, Wing Cheong Li, Junbo
Abstract	With the proliferation of the emerging Online Social Networks and other conventional communication services, there is an increasing need for a tool which can facilitate individual users to effectively socialize across multiple, heterogeneous platforms. While the diverse nature of the heterogeneous services already makes the design of a cross-platform socialization tool challenging, an even more daunting task is to tackle the "noisy" nature of the Social Networking Services (SNS). Existing solutions all lack flexibility and extensibility, especially in supporting advanced users to better manage their cross-platform socialization via customized information processing. In this paper, we propose PIXS (Programmable Intelligence for Cross-platform Socialization) -- an open-source, extensible middleware which provides efficient information acquisition and dissemination across heterogeneous SNSs. A distinguishing feature of PIXS is its support of script-based operations. As a proof-of-concept to demonstrate the flexibility and effectiveness of PIXS, we have developed for it a Python-based semi-supervised learning application which can prioritize incoming messages from different platforms via a Rank Preserving Regression (RPR) framework. This framework can readily incorporate the domain knowledge of the end user. Our SGD-based approach also enables adaptive and incremental training of the ranking system according to the gradual evolution of the user preference. Performance evaluation based on real message traces shows that the proposed system can boost the user's efficiency in identifying and forwarding important messages across heterogeneous SNS platforms. Additional use-cases of PIXS are also discussed.
Starting Page	33
Ending Page	38
Page Count	6
File Format	PDF
ISBN	9781450321778
DOI	10.1145/2491159.2491167
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-08-16
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Personalization Social networking services Middleware
Content Type	Text
Resource Type	Article

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