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06/05/2023
A Simple Yet High-Performing On-disk Learned Index: Can We Have Our Cake and Eat it Too?
While in-memory learned indexes have shown promising performance as comp...
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05/02/2023
Updatable Learned Indexes Meet Disk-Resident DBMS – From Evaluations to Design Choices
Although many updatable learned indexes have been proposed in recent yea...
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07/27/2021
Let Trajectories Speak Out the Traffic Bottlenecks
Traffic bottlenecks are a set of road segments that have an unacceptable...
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01/08/2021
Spatial Object Recommendation with Hints: When Spatial Granularity Matters
Existing spatial object recommendation algorithms generally treat object...
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11/09/2020
RMITB at TREC COVID 2020
Search engine users rarely express an information need using the same qu...
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04/06/2020
Dynamic Ridesharing in Peak Travel Periods
In this paper, we study a variant of the dynamic ridesharing problem wit...
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03/30/2020
Temporal Network Representation Learning via Historical Neighborhoods Aggregation
Network embedding is an effective method to learn low-dimensional repres...
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03/25/2020
A Survey on Trajectory Data Management, Analytics, and Learning
Recent advances in sensor and mobile devices have enabled an unprecedent...
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11/16/2018
The Potential of Learned Index Structures for Index Compression
Inverted indexes are vital in providing fast key-word-based search. For ...
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11/15/2018
Boosting Search Performance Using Query Variations
Rank fusion is a powerful technique that allows multiple sources of info...
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04/02/2018