DOCSLIB.ORG

Database Repairing and Consistent Query Answering

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Database Repairing and Consistent Query Answering BERTOSSI SeriesSeriesSeries ISSN: ISSN:ISSN: 2153-5418 2153-54182153-5418 BERTOSSI BERTOSSI MMM MorganMorganMorgan & & & ClaypoolClaypoolClaypool PublishersPublishersPublishers SSSYNTHESISYNTHESISYNTHESIS L LLECTURESECTURESECTURES ON ONON D DDATAATAATA M MMANAGEMENTANAGEMENTANAGEMENT &&&CCC SeriesSeriesSeries Editor: Editor:Editor: M. M.M. Tamer TamerTamer Özsu, Özsu,Özsu, University UniversityUniversity of ofof Waterloo WaterlooWaterloo DATABASE REPAIRING AND CONSISTENT QUERYDATABASE ANSWERING DATABASE REPAIRING AND CONSISTENT QUERYDATABASE ANSWERING REPAIRING AND CONSISTENT QUERYDATABASE ANSWERING DatabaseDatabaseDatabase Repairing RepairingRepairing and andand Consistent ConsistentConsistent DatabaseDatabaseDatabase RepairingRepairingRepairing QueryQueryQuery Answering AnsweringAnswering LeopoldoLeopoldoLeopoldo Bertossi, Bertossi,Bertossi, Carleton CarletonCarleton University, University,University, Ottowa, Ottowa,Ottowa, Canada CanadaCanada andandand ConsistentConsistentConsistent QueryQueryQuery IntegrityIntegrityIntegrity constraints constraintsconstraints are areare semantic semanticsemantic conditions conditionsconditions that thatthat a a adatabase databasedatabase should shouldshould satisfy satisfysatisfy in inin order orderorder to toto be bebe an anan appropriate appropriateappropriate model modelmodel ofofof external externalexternal reality. reality.reality. In InIn practice, practice,practice, and andand for forfor many manymany reasons, reasons,reasons, a a adatabase databasedatabase may maymay not notnot satisfy satisfysatisfy those thosethose integrity integrityintegrity constraints, constraints,constraints, AnsweringAnsweringAnswering andandand for forfor that thatthat reason reasonreason it itit is isis said saidsaid to toto be bebe inconsistent inconsistentinconsistent. .However,. However,However, and andand most mostmost likely, likely,likely, a a alarge largelarge portion portionportion of ofof the thethe database databasedatabase is isis still stillstill semanticallysemanticallysemantically correct, correct,correct, in inin a a asense sensesense that thatthat has hashas to toto be bebe made mademade precise preciseprecise. .After. AfterAfter having havinghaving provided providedprovided a a aformal formalformal characterization characterizationcharacterization ofofof consistent consistentconsistent data datadata in inin an anan inconsistent inconsistentinconsistent database, database,database, the thethe natural naturalnatural problem problemproblem emerges emergesemerges of ofof extracting extractingextracting that thatthat semantically semanticallysemantically correctcorrectcorrect data, data,data, as asas query queryquery answers. answers.answers. TheTheThe consistent consistentconsistent data datadata in inin an anan inconsistent inconsistentinconsistent database databasedatabase is isis usually usuallyusually characterized characterizedcharacterized as asas the thethe data datadata that thatthat persists persistspersists across acrossacross all allall thethethe database databasedatabase instances instancesinstances that thatthat are areare consistent consistentconsistent and andand minimally minimallyminimally differ differdiffer from fromfrom the thethe inconsistent inconsistentinconsistent instance. instance.instance. Those ThoseThose are areare the thethe so-calledso-calledso-called repairs repairsrepairs of ofof the thethe database. database.database. In InIn particular, particular,particular, the thethe consistent consistentconsistent answers answersanswers to toto a a aquery queryquery posed posedposed to toto the thethe inconsistent inconsistentinconsistent databasedatabasedatabase are areare those thosethose answers answersanswers that thatthat can cancan be bebe simultaneously simultaneouslysimultaneously obtained obtainedobtained from fromfrom all allall the thethe database databasedatabase repairs. repairs.repairs. LeopoldoLeopoldoLeopoldo Bertossi BertossiBertossi AsAsAs expected, expected,expected, the thethe notion notionnotion of ofof repair repairrepair requires requiresrequires an anan adequate adequateadequate notion notionnotion of ofof distance distancedistance that thatthat allows allowsallows for forfor the thethe comparison comparisoncomparison ofofof databases databasesdatabases with withwith respect respectrespect to toto how howhow much muchmuch they theythey differ differdiffer from fromfrom the thethe inconsistent inconsistentinconsistent instancse. instancse.instancse. On OnOn this thisthis basis, basis,basis, the thethe minimality minimalityminimality conditionconditioncondition on onon repairs repairsrepairs can cancan be bebe properly properlyproperly formulated. formulated.formulated. InInIn this thisthis monograph monographmonograph we wewe present presentpresent and andand discuss discussdiscuss these thesethese fundamental fundamentalfundamental concepts, concepts,concepts, different differentdifferent repair repairrepair semantics, semantics,semantics, algorithms algorithmsalgorithms forforfor computing computingcomputing consistent consistentconsistent answers answersanswers to toto queries, queries,queries, and andand also alsoalso complexity-theoretic complexity-theoreticcomplexity-theoretic results resultsresults related relatedrelated to toto the thethe computation computationcomputation ofofof repairs repairsrepairs and andand doing doingdoing consistent consistentconsistent query queryquery answering. answering.answering. AboutAboutAbout SYNTHESIs SYNTHESIsSYNTHESIs MORGAN ThisThisThis volume volumevolume is isis a a aprinted printedprinted version versionversion of ofof a a awork workwork that thatthat appears appearsappears in inin the thethe Synthesis SynthesisSynthesis MORGANMORGAN DigitalDigitalDigital Library LibraryLibrary of ofof Engineering EngineeringEngineering and andand Computer ComputerComputer Science. Science.Science. Synthesis SynthesisSynthesis Lectures LecturesLectures provideprovideprovide concise, concise,concise, original originaloriginal presentations presentationspresentations of ofof important importantimportant research researchresearch and andand development developmentdevelopment topics,topics,topics, published publishedpublished quickly, quickly,quickly, in inin digital digitaldigital and andand print printprint formats. formats.formats. For ForFor more moremore information informationinformation & visitvisitvisit www.morganclaypool.com www.morganclaypool.comwww.morganclaypool.com & & CLAYPOOL CLAYPOOLCLAYPOOL ISBN:ISBN:ISBN: 978-1-60845-762-5978-1-60845-762-5978-1-60845-762-5 MorganMorganMorgan & & & Claypool ClaypoolClaypool Publishers PublishersPublishers 999000000000000 SSSYNTHESISYNTHESISYNTHESIS L LLECTURESECTURESECTURES ON ONON D DDATAATAATA M MMANAGEMENTANAGEMENTANAGEMENT www.morganclaypool.comwww.morganclaypool.comwww.morganclaypool.com 999777888111666000888444555777666222555 M.M.M. Tamer TamerTamer Özsu, Özsu,Özsu, Series SeriesSeries Editor EditorEditor Database Repairing and Consistent Query Answering Synthesis Lectures on Data Management Editor M.Tamer Özsu, University of Waterloo Synthesis Lectures on Data Management is edited by Tamer Özsu of the University of Waterloo. The series will publish 50- to 125-page publications on topics pertaining to data management. The scope will largely follow the purview of premier information and computer science conferences, such as ACM SIGMOD, VLDB, ICDE, PODS, ICDT, and ACM KDD. Potential topics include, but not are limited to: query languages, database system architectures, transaction management, data warehousing, XML and databases, data stream systems, wide scale data distribution, multimedia data management, data mining, and related subjects. Database Repairing and Consistent Query Answering Leopoldo Bertossi 2011 Managing Event Information: Modeling, Retrieval, and Applications Amarnath Gupta and Ramesh Jain 2011 Fundamentals of Physical Design and Query Compilation David Toman and Grant Weddell 2011 Methods for Mining and Summarizing Text Conversations Giuseppe Carenini, Gabriel Murray, and Raymond Ng 2011 Probabilistic Databases Dan Suciu, Dan Olteanu, Christopher Ré, and Christoph Koch 2011 Peer-to-Peer Data Management Karl Aberer 2011 iv Probabilistic Ranking Techniques in Relational Databases Ihab F. Ilyas and Mohamed A. Soliman 2011 Uncertain Schema Matching Avigdor Gal 2011 Fundamentals of Object Databases: Object-Oriented and Object-Relational Design Suzanne W. Dietrich and Susan D. Urban 2010 Advanced Metasearch Engine Technology Weiyi Meng and Clement T. Yu 2010 Web Page Recommendation Models: Theory and Algorithms Sule Gündüz-Ögüdücü 2010 Multidimensional Databases and Data Warehousing Christian S. Jensen, Torben Bach Pedersen, and Christian Thomsen 2010 Database Replication Bettina Kemme, Ricardo Jimenez Peris, and Marta Patino-Martinez 2010 Relational and XML Data Exchange Marcelo Arenas, Pablo Barcelo, Leonid Libkin, and Filip Murlak 2010 User-Centered Data Management Tiziana Catarci, Alan Dix, Stephen Kimani, and Giuseppe Santucci 2010 Data Stream Management Lukasz Golab and M. Tamer Özsu 2010 Access Control in Data Management Systems Elena Ferrari 2010 v An Introduction to Duplicate Detection Felix Naumann and Melanie Herschel 2010 Privacy-Preserving Data Publishing: An Overview Raymond Chi-Wing Wong and Ada Wai-Chee Fu 2010 Keyword Search in Databases Jeffrey Xu Yu, Lu Qin, and Lijun Chang 2009 Copyright © 2011 by Morgan & Claypool All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted
Load more

Recommended publications
  • SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations
    SAQE: Practical Privacy-Preserving Approximate Query Processing for Data Federations Johes Bater Yongjoo Park Xi He Northwestern University University of Illinois (UIUC) University of Waterloo [email protected] [email protected] [email protected] Xiao Wang Jennie Rogers Northwestern University Northwestern University [email protected] [email protected] ABSTRACT 1. INTRODUCTION A private data federation enables clients to query the union of data Querying the union of multiple private data stores is challeng- from multiple data providers without revealing any extra private ing due to the need to compute over the combined datasets without information to the client or any other data providers. Unfortu- data providers disclosing their secret query inputs to anyone. Here, nately, this strong end-to-end privacy guarantee requires crypto- a client issues a query against the union of these private records graphic protocols that incur a significant performance overhead as and he or she receives the output of their query over this shared high as 1,000× compared to executing the same query in the clear. data. Presently, systems of this kind use a trusted third party to se- As a result, private data federations are impractical for common curely query the union of multiple private datastores. For example, database workloads. This gap reveals the following key challenge some large hospitals in the Chicago area offer services for a cer- in a private data federation: offering significantly fast and accurate tain percentage of the residents; if we can query the union of these query answers without compromising strong end-to-end privacy. databases, it may serve as invaluable resources for accurate diag- To address this challenge, we propose SAQE, the Secure Ap- nosis, informed immunization, timely epidemic control, and so on.
    [Show full text]
  • WIN: an Efficient Data Placement Strategy for Parallel XML Databases
    WIN : An Efficient Data Placement Strategy for Parallel XML Databases Nan Tang† Guoren Wang‡ Jeffrey Xu Yu† Kam-Fai Wong† Ge Yu‡ † Department of SE & EM, The Chinese University of Hong Kong, Hong Kong, China ‡ College of Information Science and Engineering, Northeastern University, Shenyang, China {ntang, yu, kfwong}se.cuhk.edu.hk {wanggr, yuge}@mail.neu.edu.cn Abstract graph-based. Distinct from them, XML employs a tree struc- The basic idea behind parallel database systems is to ture. Conventional data placement strategies in perform operations in parallel to reduce the response RDBMSs and OODBMSs cannot serve XML data well. time and improve the system throughput. Data place- Semistructured data involve nested structures; there ment is a key factor on the overall performance of are much intricacy and redundancy when represent- parallel systems. XML is semistructured data, tradi- ing XML as relations. Data placement strategies in tional data placement strategies cannot serve it well. RDBMSs cannot, therefore, well solve the data place- In this paper, we present the concept of intermediary ment problem of XML data. Although graph partition node INode, and propose a novel workload-aware data algorithms in OODBMSs can be applied to tree parti- placement WIN to effectively decluster XML data, to tion problems, the key relationships between tree nodes obtain high intra query parallelism. The extensive ex- such as ancestor-descendant or sibling cannot be clearly periments show that the speedup and scaleup perfor- denoted on graph. Hence data placement strategies mance of WIN outperforms the previous strategies. for OODBMSs cannot well adapt to XML data either.
    [Show full text]
  • Tepzz¥ 67¥¥Za T
    (19) TZZ¥ ¥¥Z_T (11) EP 3 267 330 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 10.01.2018 Bulletin 2018/02 G06F 17/30 (2006.01) (21) Application number: 16187202.3 (22) Date of filing: 05.09.2016 (84) Designated Contracting States: (72) Inventors: AL AT BE BG CH CY CZ DE DK EE ES FI FR GB • Abolhassani, Neda GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO Athens, GA Georgia 30605 (US) PL PT RO RS SE SI SK SM TR • Sheausan Tung, Teresa Designated Extension States: San Jose, CA California 95120 (US) BA ME • Gomadam, Karthik Designated Validation States: San Jose, CA California 95112 (US) MA MD (74) Representative: Müller-Boré & Partner (30) Priority: 07.07.2016 US 201662359547 P Patentanwälte PartG mbB 03.08.2016 US 201615227605 Friedenheimer Brücke 21 80639 München (DE) (71) Applicant: Accenture Global Solutions Limited Dublin 4 (IE) (54) QUERY REWRITING IN A RELATIONAL DATA HARMONIZATION FRAMEWORK (57) A query rewriting processor (processor) analyz- an SQL query). The processor may then pass the rela- es database semantic models (e.g., RDF knowledge tional database query to another system or process (e.g., graphs) that capture the interconnections (e.g., foreign a data virtualization layer) for execution against the indi- and primary key links to other tables) present in a rela- vidual relational databases. In this manner, the processor tional database. The processor generates an enriched automatically translates queries for information about the model query given an initial model query (e.g., a SPARQL relational database structure to a corresponding or query) against the semantic model.
    [Show full text]
  • Conjunctive Query Answering in the Description Logic EL Using a Relational Database System
    Conjunctive Query Answering in the Description Logic EL Using a Relational Database System Carsten Lutz - Universität Bremen, Germany David Toman - University of Waterloo, Canada FrankWolter - University of Liverpool, UK Presented By : Jasmeet Jagdev Background • One of the main application of ontologies is data access • Ontologies formalize conceptual information about the data • Calvanese et al. have argued, true scalability of CQ answering over DL ontologies can only be achieved by making use of RDBMSs • Not straight forward ! Background • RDBMSs are unaware of Tboxes (the DL mechanism for storing conceptual information) and adopt the closed-world semantics • In contrast, ABoxes (the DL mechanism for storing data) and the associated ontologies employ the open-world semantics Introduction • Approach for using RDBMSs for CQ answering over DL ontologies • We apply it to an extension of EL family of DLs • Widely used as ontology languages for large scale bio-medical ontologies such as SNOMED CT and NCI Introduction • EL allows – Concept Intersection – Existential restrictions dr • ELH⊥ = EL + bottom concept, role inclusions, and domain and range restrictions Main Idea • To incorporate the consequences of the TBox T into the relational instance corresponding to the given ABox A • To introduce the idea of combined first-order (FO) rewritability • It is possibly only if: – A and T can be written into an FO structure – q and T into FO query q* Main Idea • Properties of this approach: – It applies to DLs for which data complexity of CQ dr answering
    [Show full text]
  • Query Rewriting Using Monolingual Statistical Machine Translation
    Query Rewriting using Monolingual Statistical Machine Translation Stefan Riezler∗ Yi Liu∗∗ Google Google Long queries often suffer from low recall in web search due to conjunctive term matching. The chances of matching words in relevant documents can be increased by rewriting query terms into new terms with similar statistical properties. We present a comparison of approaches that deploy user query logs to learn rewrites of query terms into terms from the document space. We show that the best results are achieved by adopting the perspective of bridging the “lexical chasm” between queries and documents by translating from a source language of user queries into a target language of web documents. We train a state-of-the-art statistical machine translation (SMT) model on query-snippet pairs from user query logs, and extract expansion terms from the query rewrites produced by the monolingual translation system. We show in an extrinsic evaluation in a real-world web search task that the combination of a query-to-snippet translation model with a query language model achieves improved contextual query expansion compared to a state-of-the-art query expansion model that is trained on the same query log data. 1. Introduction Information Retrieval (IR) applications have been notoriously resistant to improvement attempts by Natural Language Processing (NLP). With a few exceptions for specialized tasks1, the contribution of part-of-speech taggers, syntactic parsers, or ontologies of nouns or verbs, has been inconclusive. In this paper, instead of deploying NLP tools or ontologies, we apply NLP ideas to IR problems. In particular, we take a viewpoint that looks at the problem of the word mismatch between queries and documents in web search as a problem of translating from a source language of user queries into a target language of web documents.
    [Show full text]
  • On Using an Automatic, Autonomous and Non-Intrusive Approach for Rewriting SQL Queries
    Simpósio Brasileiro de Banco de Dados - SBBD 2013 Short Papers On Using an Automatic, Autonomous and Non-Intrusive Approach for Rewriting SQL Queries Arlino H. M. de Araújo1;2, José Maria Monteiro2, José Antônio F. de Macêdo2, Júlio A. Tavares3, Angelo Brayner3, Sérgio Lifschitz4 1 Federal University of Piauí, Brazil 2 Federal University of Ceará, Brazil {arlino,monteiro,jose.macedo}@lia.ufc.br 3 University of Fortaleza, Brazil [email protected] 4 Pontifical Catholic University of Rio de Janeiro [email protected] Abstract. Database applications have become very complex, dealing with a huge volume of data and database objects. Concurrently, low query response time and high transaction throughput have emerged as mandatory requirements to be ensured by database management systems (DBMSs). Among other possible interventions regarding database performance, SQL query rewriting has been shown quite efficient. The idea is to rewrite a new SQL statement equivalent to the statement initially formulated, where the new SQL statement provides performance gains w.r.t. query response time. In this paper, we propose an automatic and non-intrusive approach for rewriting SQL queries. The proposed approach has been implemented and its behavior was evaluated in three different DBMSs using TPC-H benchmark. The results show that the proposed approach is quite efficient and can be effectively considered by database professionals. Categories and Subject Descriptors: H.2 [Database Management]: Miscellaneous Keywords: Query processing, Database tuning, Query rewriting 1. INTRODUCTION Database queries are expressed by means of high-level declarative languages, such as SQL (Structured Query Language), for instance. Such queries are submitted to the query engine, which is responsible for processing queries in database mangement systems (DBMSs).
    [Show full text]
  • Towards Practical Privacy-Preserving Data Analytics by Noah Michael
    Towards Practical Privacy-Preserving Data Analytics by Noah Michael Johnson A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Engineering - Electrical Engineering and Computer Sciences in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Dawn Song, Chair Professor David Wagner Professor Deirdre Mulligan Fall 2018 Towards Practical Privacy-Preserving Data Analytics Copyright 2018 by Noah Michael Johnson 1 Abstract Towards Practical Privacy-Preserving Data Analytics by Noah Michael Johnson Doctor of Philosophy in Engineering - Electrical Engineering and Computer Sciences University of California, Berkeley Professor Dawn Song, Chair Organizations are increasingly collecting sensitive information about individuals. Extracting value from this data requires providing analysts with flexible access, typically in the form of data- bases that support SQL queries. Unfortunately, allowing access to data has been a major cause of privacy breaches. Traditional approaches for data security cannot protect privacy of individuals while providing flexible access for analytics. This presents a difficult trade-off. Overly restrictive policies result in underutilization and data siloing, while insufficient restrictions can lead to privacy breaches and data leaks. Differential privacy is widely recognized by experts as the most rigorous theoretical solution to this problem. Differential privacy provides a formal guarantee of privacy for individuals while allowing general statistical analysis of the data. Despite extensive academic research, differential privacy has not been widely adopted in practice. Additional work is needed to address performance and usability issues that arise when applying differential privacy to real-world environments. In this dissertation we develop empirical and theoretical advances towards practical differential privacy.
    [Show full text]
  • Data Management 09 Transaction Processing
    1 SCIENCE PASSION TECHNOLOGY Data Management 09 Transaction Processing Matthias Boehm, Arnab Phani Graz University of Technology, Austria Computer Science and Biomedical Engineering Institute of Interactive Systems and Data Science BMK endowed chair for Data Management Last update: Dec 06, 2020 2 Announcements/Org . #1 Video Recording . Link in TeachCenter & TUbe (lectures will be public) . Due to second lockdown: webex recording . #2 Exercise Submissions . Exercise 1: grading done . Exercise 2: in process of being grading . Exercise 3: published on Dec 01, submit by Dec 22 11:59pm . Issues dataset (Nov 19) / expected results (Nov 16, Nov 26) . Two approaches of handling actors . Incorrect expected results 5 extra points INF.01017UF Data Management / 706.010 Databases – 09 Transaction Processing Matthias Boehm, Graz University of Technology, WS 2020/21 3 Transaction (TX) Processing User 2 User 1 User 3 read/write TXs #1 Multiple users Correctness? DBS DBMS #2 Various failures Deadlocks (TX, system, media) Constraint Reliability? violations DBs Network Crash/power failure Disk failure failure . Goal: Basic Understanding of Transaction Processing . Transaction processing from user perspective . Locking and concurrency control to ensure #1 correctness . Logging and recovery to ensure #2 reliability INF.01017UF Data Management / 706.010 Databases – 09 Transaction Processing Matthias Boehm, Graz University of Technology, WS 2020/21 4 Agenda . Overview Transaction Processing . Locking and Concurrency Control . Logging and Recovery . Exercise
    [Show full text]
  • Distributed Complex Event Processing with Query Rewriting
    Distributed Complex Event Processing with Query Rewriting Nicholas Poul Matteo Migliavacca Peter Pietzuch Schultz-Møller Department of Computing Department of Computing Department of Computing Imperial College London Imperial College London Imperial College London United Kingdom United Kingdom United Kingdom [email protected] [email protected] [email protected] ABSTRACT is first stored and indexed and only queried afterwards. The nature of data in enterprises and on the Internet is In contrast, complex event processing (CEP) systems re- changing. Data used to be stored in a database first and gard new data (or updates to existing data) as a stream of queried later. Today timely processing of new data, repre- events [19]. Users can specify queries as high-level patterns sented as events, is increasingly valuable. In many domains, of events. The CEP system detects complex events matching complex event processing (CEP) systems detect patterns of these queries and notifies clients of matches in soft real-time. events for decision making. Examples include processing of For example, a credit card processing company may monitor environmental sensor data, trades in financial markets and fraudulent credit card use by specifying patterns that detect RSS web feeds. Unlike conventional database systems, most concurrent transactions caused by the same credit card at current CEP systems pay little attention to query optimi- geographically distant locations. sation. They do not rewrite queries to more efficient rep- Detecting complex patterns in high-rate event streams re- resentations or make decisions about operator distribution, quires substantial CPU resources. To make a CEP system limiting their overall scalability.
    [Show full text]
  • Probabilistic Query Rewriting for Efficient and Effective Keyword
    Probabilistic Query Rewriting for Efficient and Effective Keyword Search on Graph Data Lei Zhang Thanh Tran Achim Rettinger Karlsruhe Institute of Karlsruhe Institute of Karlsruhe Institute of Technology Technology Technology 76128 Karlsruhe, Germany 76128 Karlsruhe, Germany 76128 Karlsruhe, Germany [email protected] [email protected] [email protected] ABSTRACT connecting them, which represent final answers covering all The problem of rewriting keyword search queries on graph query keywords. The space of possible subgraphs is gener- data has been studied recently, where the main goal is to ally exponential in the number of query keywords. Through clean user queries by rewriting keywords as valid tokens ap- grouping keywords into larger meaningful units (called seg- pearing in the data and grouping them into meaningful seg- ments), the number of keywords to be processed and the ments. The main solution to this problem employs heuris- corresponding search space is reduced. tics for ranking query rewrites and a dynamic programming The two main tasks involved in query cleaning (henceforth algorithm for computing them. Based on a broader set of also called query rewriting) are token rewriting, where query queries defined by an existing benchmark, we show that the keywords are rewritten as tokens appearing in the data, and use of these heuristics does not yield good results. We pro- query segmentation, where tokens are grouped together as pose a novel probabilistic framework, which enables the op- segments representing compound keywords. Query rewrit- timality of a query rewrite to be estimated in a more princi- ing helps to improve not only the result quality but also the pled way.
    [Show full text]
  • Agent Based System for Realtime Database Audit Monitoring
    UNIVERSITY OF NAIROBI SCHOOL OF COMPUTING AND INFORMATICS AGENT BASED SYSTEM FOR REALTIME DATABASE AUDIT MONITORING BY BONIFACE AKUKU P58/73079/2009 SUPERVISOR MR. CHRISTOPHER MOTURI August 2011 A research report submitted in partial fulfillment for the requirements of Master of Science in Computer Science University of NAIROBI Library 0439225 4 Table of Contents Table of Contents........................................................................................................................................ „... ii Abstract............................................................................................................................................................. iii Dedication......................................................................................................................................................... iv Acknowledgement..............................................................................................................................................v Declaration........................................................................................................................................................ vi Abbreviations...................................................................................................................................................vii List of Tables...................................................................................................................................................viii List of Figures...................................................................................................................................................ix
    [Show full text]
  • Negative Database for Data Security
    Negative Database for Data Security Anup Patel Niveeta Sharma Magdalini Eirinaki Computer Engineering Department San Jose State University [email protected], [email protected], [email protected] Abstract high database security levels. This framework is a collection of some algorithms that manipulate the input Data Security is a major issue in any web-based data and store it in the database. This populated database application. There have been approaches to handle is referred to as the negative database. A negative intruders in any system, however, these approaches are database can be defined as a database that contains huge not fully trustable; evidently data is not totally protected. amount of data which consists of counterfeit data along Real world databases have information that needs to be with the actual data. A few approaches that describe this securely stored. The approach of generating negative concept have been proposed but have not yet been database could help solve such problem. A Negative implemented to work for real world databases [5]. All Database can be defined as a database that contains the proposed algorithms had issues related to the huge amount of data consisting of counterfeit data along reversibility of the data, converting back to the original with the real data. Intruders may be able to get access to form from the negative representations [3] and the fact is such databases, but, as they try to extract information, that they have not yet been implemented. [2, 4]. they will retrieve data sets that would include both the Contrary to previous work, the proposed framework actual and the negative data.
    [Show full text]