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Full-Text Articles in Physical Sciences and Mathematics
Indexable Bayesian Personalized Ranking For Efficient Top-K Recommendation, Dung D. Le, Hady W. Lauw
Indexable Bayesian Personalized Ranking For Efficient Top-K Recommendation, Dung D. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Top-k recommendation seeks to deliver a personalized recommendation list of k items to a user. The dual objectives are (1) accuracy in identifying the items a user is likely to prefer, and (2) efficiency in constructing the recommendation list in real time. One direction towards retrieval efficiency is to formulate retrieval as approximate k nearest neighbor (kNN) search aided by indexing schemes, such as locality-sensitive hashing, spatial trees, and inverted index. These schemes, applied on the output representations of recommendation algorithms, speed up the retrieval process by automatically discarding a large number of potentially irrelevant items when given a user …
Symphony: A Platform For Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Symphony: A Platform For Search-Driven Applications, John C. Shafer, Rakesh Agrawal, Hady W. Lauw
Research Collection School Of Computing and Information Systems
We present the design of Symphony, a platform that enables non-developers to build and deploy a new class of search-driven applications that combine their data and domain expertise with content from search engines and other web services. The Symphony prototype has been built on top of Microsoft's Bing infrastructure. While Symphony naturally makes use of the customization capabilities exposed by Bing, its distinguishing feature is the capability it provides to the application creator to combine their proprietary data and domain expertise with content obtained from Bing. They can also integrate specialized data obtained from web services to enhance the richness …
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
On Searching Continuous Nearest Neighbors In Wireless Data Broadcast Systems, Baihua Zheng, Wang-Chien Lee, Dik Lun Lee
Research Collection School Of Computing and Information Systems
A continuous nearest neighbor (CNN) search, which retrieves the nearest neighbors corresponding to every point in a given query line segment, is important for location-based services such as vehicular navigation and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server systems but not in the environment of wireless data broadcast, where uplink communication channels from mobile devices to the …
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
An Energy-Efficient And Access Latency Optimized Indexing Scheme For Wireless Data Broadcast, Yuxia Yao, Xueyan Tang, Ee Peng Lim, Aixin Sun
Research Collection School Of Computing and Information Systems
Data broadcast is an attractive data dissemination method in mobile environments. To improve energy efficiency, existing air indexing schemes for data broadcast have focused on reducing tuning time only, i.e., the duration that a mobile client stays active in data accesses. On the other hand, existing broadcast scheduling schemes have aimed at reducing access latency through nonflat data broadcast to improve responsiveness only. Not much work has addressed the energy efficiency and responsiveness issues concurrently. This paper proposes an energy-efficient indexing scheme called MHash that optimizes tuning time and access latency in an integrated fashion. MHash reduces tuning time by …
Dsim: A Distance-Based Indexing Method For Genomic Sequences, Xia Cao, Beng-Chin Ooi, Hwee Hwa Pang, Kian-Lee Tan, Anthony K. H. Tung
Dsim: A Distance-Based Indexing Method For Genomic Sequences, Xia Cao, Beng-Chin Ooi, Hwee Hwa Pang, Kian-Lee Tan, Anthony K. H. Tung
Research Collection School Of Computing and Information Systems
In this paper, we propose a Distance-based Sequence Indexing Method (DSIM) for indexing and searching genome databases. Borrowing the idea of video compression, we compress the genomic sequence database around a set of automatically selected reference words, formed from high-frequency data substrings and substrings in past queries. The compression captures the distance of each non-reference word in the database to some reference word. At runtime, a query is processed by comparing its substrings with the compressed data strings, through their distances to the reference words. We also propose an efficient scheme to incrementally update the reference words and the compressed …
Motion Characterization By Temporal Slices Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang, Roland T. Chin
Motion Characterization By Temporal Slices Analysis, Chong-Wah Ngo, Ting-Chuen Pong, Hong-Jiang Zhang, Roland T. Chin
Research Collection School Of Computing and Information Systems
This paper describes an approach to characterize camera and object motions based on the analysis of spatio temporal image volumes. In the spatio-temporal slices of image volumes, motion is depicted as oriented patterns. We propose a tensor histogram computation algorithm to represent these oriented patterns. The motion trajectories in a histogram are tracked to describe both the camera and object motions. In addition, we exploit the similarity of the temporal slices in a volume to reliably partition a volume into motion tractable units.