NDLI: Efficient temporal keyword search over versioned text

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Efficient temporal keyword search over versioned text

Content Provider	ACM Digital Library
Author	Bedathur, Srikanta Anand, Avishek Berberich, Klaus Schenkel, Ralf
Abstract	Modern text analytics applications operate on large volumes of temporal text data such as Web archives, newspaper archives, blogs, wikis, and micro-blogs. In these settings, searching and mining needs to use constraints on the time dimension in addition to keyword constraints. A natural approach to address such queries is using an inverted index whose entries are enriched with valid-time intervals. It has been shown that these indexes have to be partitioned along time in order to achieve efficiency. However, when the temporal predicate corresponds to a long time range, requiring the processing of multiple partitions, naive query processing incurs high cost of reading of redundant entries across partitions. We present a framework for efficient approximate processing of keyword queries over a temporally partitioned inverted index which minimizes this overhead, thus speeding up query processing. By using a small synopsis for each partition we identify partitions that maximize the number of final non-redundant results, and schedule them for processing early on. Our approach aims to balance the estimated gains in the final result recall against the cost of index reading required. We present practical algorithms for the resulting optimization problem of index partition selection. Our experiments with three diverse, large-scale text archives reveal that our proposed approach can provide close to 80% result recall even when only about half the index is allowed to be read.
Starting Page	699
Ending Page	708
Page Count	10
File Format	PDF
ISBN	9781450300995
DOI	10.1145/1871437.1871528
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-10-26
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Synopses Partitioned inverted index Partition selection Time-travel search
Content Type	Text
Resource Type	Article

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