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Brisbane, Australia Australia
Apr. 8, 2013 to Apr. 12, 2013
ISBN: 978-1-4673-4909-3
pp: 1288-1291
A. Nandi , Ohio State Univ., Columbus, OH, USA
S. Paparizos , Search Labs., Microsoft Res., Mountain View, CA, USA
J. C. Shafer , Search Labs., Microsoft Res., Mountain View, CA, USA
R. Agrawal , Search Labs., Microsoft Res., Mountain View, CA, USA
ABSTRACT
A typical person has numerous online friends that, according to studies, the person often consults for opinions and advice. However, public broadcasting a question to all friends risks social capital when repeated too often, is not tolerant to topic sensitivity, and can result in no response, as the message is lost in a myriad of status updates. Direct messaging is more personal and avoids these pitfalls, but requires manual selection of friends to contact, which can be time consuming and challenging. A user may have difficulty guessing which of their numerous online friends can provide a high quality and timely response. We demonstrate a working system that addresses these issues by returning an ordered subset of friends predicting (a) near-term availability, (b) willingness to respond and (c) topical knowledge, given a query. The combination of these three aspects are unique to our solution, and all are critical to the problem of obtaining timely and relevant responses. Our system acts as a decision aid - we give insight into why each friend was recommended and let the user decide whom to contact.
INDEX TERMS
Availability, Search engines, Twitter, Electronic mail, Bars, Indexes,
CITATION
A. Nandi, S. Paparizos, J. C. Shafer, R. Agrawal, "With a little help from my friends", ICDE, 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013 IEEE 29th International Conference on Data Engineering (ICDE) 2013, pp. 1288-1291, doi:10.1109/ICDE.2013.6544926
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