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» Discovering Trends in Text Databases
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IEEEVAST
2010
14 years 4 months ago
Understanding text corpora with multiple facets
Text visualization becomes an increasingly more important research topic as the need to understand massive-scale textual information is proven to be imperative for many people and...
Lei Shi, Furu Wei, Shixia Liu, Li Tan, Xiaoxiao Li...
PVLDB
2008
124views more  PVLDB 2008»
14 years 9 months ago
DBPubs: multidimensional exploration of database publications
DBPubs is a system for effectively analyzing and exploring the content of database publications by combining keyword search with OLAP-style aggregations, navigation, and reporting...
Akanksha Baid, Andrey Balmin, Heasoo Hwang, Erik N...
SIGMOD
2006
ACM
137views Database» more  SIGMOD 2006»
15 years 9 months ago
Optimal multi-scale patterns in time series streams
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...
Spiros Papadimitriou, Philip S. Yu
73
Voted
VLDB
2005
ACM
122views Database» more  VLDB 2005»
15 years 2 months ago
Streaming Pattern Discovery in Multiple Time-Series
In this paper, we introduce SPIRIT (Streaming Pattern dIscoveRy in multIple Timeseries). Given n numerical data streams, all of whose values we observe at each time tick t, SPIRIT...
Spiros Papadimitriou, Jimeng Sun, Christos Falouts...
VLDB
2005
ACM
93views Database» more  VLDB 2005»
15 years 2 months ago
The TEXTURE Benchmark: Measuring Performance of Text Queries on a Relational DBMS
We introduce a benchmark called TEXTURE (TEXT Under RElations) to measure the relative strengths and weaknesses of combining text processing with a relational workload in an RDBMS...
Vuk Ercegovac, David J. DeWitt, Raghu Ramakrishnan