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In community web management systems (CWMS), storage structures inspired by universal tables are being used increasingly to manage sparse datasets. Such a sparse wide table (SWT) typically embodies thousands of attributes, with many of them being undefined in each tuple, and low-dimensional structured similarity search on a combination of numerical and text attributes is a common operation. However,...
In recent years, there has been a growing interest for peer-to-peer (P2P) based computing and applications. One of the most important challenges in P2P environments is to quickly locate relevant data across many participating peers. In this demonstration, we present psiX, which is an Internet-scale service for publishing and locating XML documents. This service runs on several PlanetLab nodes geographically...
In this paper, we formalize the novel concept of incremental reverse nearest neighbor ranking and suggest an original solution for this problem. We propose an efficient approach for reporting the results incrementally without the need to restart the search from scratch. Our approach can be applied to a multi-dimensional feature database which is hierarchically organized by any R-tree like index structure...
Summary form only given. Consider a universe of items, each of which is associated with a weight, and a database consisting of subsets of these items. Given a query set, a weighted set similarity query identifies either (i) all sets in the database whose normalized similarity to the query set is above a pre-specified threshold, or (ii) the sets in the database with the k highest similarity values...
The PLUS system is designed to efficiently track moving object locations on a road network and execute continuous spatial queries in support of location-based services. PLUS implements a novel lazy position update mechanism that significantly reduces the communication overhead and server indexing load related to frequent location updates in moving object and moving query scenarios. The contribution...
This work addresses a novel spatial keyword query called the m-closest keywords (mCK) query. Given a database of spatial objects, each tuple is associated with some descriptive information represented in the form of keywords. The mCK query aims to find the spatially closest tuples which match m user-specified keywords. Given a set of keywords from a document, mCK query can be very useful in geotagging...
A common approach to performing keyword search over relational databases is to find the minimum Steiner trees in database graphs. These methods, however, are rather expensive as the minimum Steiner tree problem is known to be NP-hard. Further, these methods cannot benefit from DBMS capabilities. We propose a new concept called Compact Steiner Tree (CSTree), which can be used to approximate the Steiner...
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