Speeding up string matching over compressed text on handheld devices using tagged sub-optimal code (TSC)

Bellaachia, Abdelghani; Rassan, Iehab Al

doi:10.1109/rttas.2004.1317259

Cited by 3 publications

(3 citation statements)

References 25 publications

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“…In another study [12], we found that using Tagged Suboptimal Code (TSC) on handheld devices could speed up string matching over compressed databases and avoid compression delay.…”

Section: Related Workmentioning

confidence: 99%

“…Two solutions to compress the entire database and keeps it accessible and manageable while it is on compressed form are introduced in our previous work [10,12], and can be used with SCTB and SCTT algorithms. Therefore, compression is done by compressing each record individually and retains the record references structure within the database unbroken.…”

Section: Handheld Data Files Organizationmentioning

confidence: 99%

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Efficiency of prefix and non-prefix codes in string matching over compressed databases on handheld devices

Bellaachia

Rassan

2005

Proceedings of the 2005 ACM Symposium on Applied Computing

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This paper shows the efficiency of prefix and non-prefix codes for searching over compressed handheld databases. Byte Pair Encoding (BPE), Tagged Suboptimal Code (TSC), and Huffman encoding are the compression techniques used in the evaluation. By compressing handheld databases and searching over compressed text without needing to expand the databases, more data will be stored and more applications can be used. Experimental results show that about 33% more space has been achieved in the compressed handhelds' databases when using Searching over Compressed Text using BPE (SCTB) or Searching over Compressed Text using TSC (SCTT) solutions. Moreover, both solutions are 6.6 times faster than decompressing the databases followed by a linear search in all different sizes of databases. Efficiency performance shows that SCTB is the recommended solution for databases consisting of large-sized records and rarely updated, and SCTT is the recommended method for frequently updated databases or consisting of smallsized records. TSC and BPE compression schemes could also be used to accelerate wireless connectivity, web clipping, or databases transfer between handheld devices and computers, since these databases are usually small in size.

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“…In another study [12], we found that using Tagged Suboptimal Code (TSC) on handheld devices could speed up string matching over compressed databases and avoid compression delay.…”

Section: Related Workmentioning

confidence: 99%

Section: Handheld Data Files Organizationmentioning

confidence: 99%

Efficiency of prefix and non-prefix codes in string matching over compressed databases on handheld devices

Bellaachia

Rassan

2005

Proceedings of the 2005 ACM Symposium on Applied Computing

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show abstract

“…To resolve the space-efficiency dilemma, some other methods have been proposed, in which text or index pre-processing means were developed. These methods, including a hybrid sorting algorithm [10], augmented suffix arrays [11], compression [12][13] [14], and coding techniques, such as Huffman coding [15] and Tagged Sub-optimal Code [16], have made great efforts for reducing the space-efficiency barrier.…”

Section: Introductionmentioning

confidence: 99%

String Filtering of a Large String Collection on Mobile Devices using a Neural Network

Ma¹,

Liu²

2006

Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)

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String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder using a neural network, can perform the task in a consistent manner regardlss of the number of strings in the collection. The string encoding process is executed on the server site, and the result is transmitted to the PDAs via the Internet. The server checks a remote database containing the most-updated data constantly, and thus renders the PDAs the accuracy in filtering the query strings. We conducted an experiment that simulates the stolen car license plate matching, and the results were favorable in both speed and memory space requirement.

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Fast blocking of undesirable web pages on client PC by discriminating URL using neural networks

2008

Expert Systems with Applications

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Speeding up string matching over compressed text on handheld devices using tagged sub-optimal code (TSC)

Cited by 3 publications

References 25 publications

Efficiency of prefix and non-prefix codes in string matching over compressed databases on handheld devices

Efficiency of prefix and non-prefix codes in string matching over compressed databases on handheld devices

String Filtering of a Large String Collection on Mobile Devices using a Neural Network

Fast blocking of undesirable web pages on client PC by discriminating URL using neural networks

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