TY - GEN
T1 - DataSift
T2 - 2014 ACM SIGMOD International Conference on Management of Data, SIGMOD 2014
AU - Parameswaran, Aditya
AU - Teh, Ming Han
AU - Garcia-Molina, Hector
AU - Widom, Jennifer
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2014
Y1 - 2014
N2 - Traditional search engines are unable to support a large number of potential queries issued by users, for instance, queries containing non-textual fragments such as images or videos, queries that are very long, ambiguous, or those that require subjective judgment, or semantically-rich queries over non-textual corpora. We demonstrate DataSift, a crowd-powered search toolkit that can be instrumented over any corpus supporting a keyword search API, and supports efficient and accurate querying for a rich general class of queries, including those described previously. Our demonstration will allow conference attendees to issue live queries for image, video, and product search, as well as "play back" the results of a wide variety of prior queries issued on DataSift. Attendees will also be able to perform a side-by-side comparison between DataSift and traditional retrieval schemes.
AB - Traditional search engines are unable to support a large number of potential queries issued by users, for instance, queries containing non-textual fragments such as images or videos, queries that are very long, ambiguous, or those that require subjective judgment, or semantically-rich queries over non-textual corpora. We demonstrate DataSift, a crowd-powered search toolkit that can be instrumented over any corpus supporting a keyword search API, and supports efficient and accurate querying for a rich general class of queries, including those described previously. Our demonstration will allow conference attendees to issue live queries for image, video, and product search, as well as "play back" the results of a wide variety of prior queries issued on DataSift. Attendees will also be able to perform a side-by-side comparison between DataSift and traditional retrieval schemes.
UR - http://www.scopus.com/inward/record.url?scp=84904319857&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904319857&partnerID=8YFLogxK
U2 - 10.1145/2588555.2594510
DO - 10.1145/2588555.2594510
M3 - Conference contribution
AN - SCOPUS:84904319857
SN - 9781450323765
T3 - Proceedings of the ACM SIGMOD International Conference on Management of Data
SP - 885
EP - 888
BT - SIGMOD 2014 - Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data
PB - Association for Computing Machinery
Y2 - 22 June 2014 through 27 June 2014
ER -