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Welcome to Xin (Luna) Dong's Homepage!
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								<p>&nbsp;<p><b><font face="Arial" size="5">Data 
								Integration</font></b></p>
            <ul>
              <li>Michael Franklin, Alon Y. Halevy, and David 
              Maier. <i>From databases to dataspaces: A new abstraction for 
              information management. </i>Sigmod Record, Dec. 2005. </li>
              <li>Alon Y. Halevy, Naveen Ashishi, Dina Bitton, 
              Michael Carey, Denise Draper, Jeff Pollock, Arnon Rosenthal, and 
              Vishal Sikka. <i>Enterprise information integration: successes, 
              challenges and controversies. </i>Sigmod 2005.</li>
        </ul>
        						<h4 align="left">Information Integration Using 
								Logical Views [<a href="../resources.php#view">Link</a>]</h4>
        						<h4 align="left"><b><a name="data-exchange"></a></b>Data Exchange</h4>
        <ul>
          <li>Ronald Fagin and Phokion G. Kolaitis and Renee J. 
			Miller and Lucian Popa. <i>Data Exchange: Semantics and Query 
			Answering</i>. ICDT, 2003. (<i>First paper on data exchange</i>)</li>
			<li>Ronald Fagin and Phokion G. Kolaitis and Lucian 
			Popa. <i>Data Exchange: Getting to the Core</i>. ACM Transactions on 
			Database Systems, 30(1):174-201, 2005. (<i>Must-read</i>)</li>
			<li>Ariel Fuxman and Phokion G. Kolaitis and Renee J. 
			Miller and Wang Chiew Tan. <i>Peer data exchange</i>. PODS, 2005.
			</li>
			<li>Phokion G. Kolaitis and Jonathan Panttaja and 
			Wang Chiew Tan. <i>The complexity of data exchange. </i>PODS, 2006.</li>
			<li>Georg Gottlob and Alan Nash. <i>Data Exchange: 
			Computing Cores in Polynomial Time</i>. PODS, 2006.</li>
			<li>Leonid Libkin. <i>Data exchange and incomplete 
			information</i>. PODS, 2006.<p><font face="Comic Sans MS" size="1"><a href="../resources.php">Up 
          to top</font></a><br>
</li>
        </ul>
        <h4 align="left"><a name="schema-matching"></a>Schema Matching</h4>
        <ul>
          <li><b>Survey</b> 
          <ul>
            <li>E. Rahm and P. A. Bernstein. <i>A survey of 
            approaches to automatic schema matching</i>. VLDB Journal,<br>
            10(4):334-350, 2001. (<i>Must-read</i>) </li>
            <li>Pavel Shvaiko. <i>A 
            classification of schema-based matching approaches. </i>Unpublished.
            </li>
          </ul>
          </li>
          <li><b>Element-level Matching</b>
          
          <ul>
            <li><b>Schema name &amp; description</b>
            
            <ul>
              <li>P. Mitra, G. Wiederhold, and J Jannink. <i>
              Semi-automatic integration of knowledge sources. </i>Proc. of 
              Fusion, 1999. </li>
              <li>L. Palopoli, D. Sacca, and D. Ursino. <i>
              Semi-automatic, semantic discover of properties from database 
              schemas.</i> IDEAS, 244-253, 1998. </li>
              <li>C. Clifton, E. Housman, and A. Rosenthal. <i>
              Experience with a combined approach to attribute-matching across 
              heterogenenous databases. </i>Proc. 7, IFIP 2.6 Working Conf. 
              Database Semantics, 1997. </li>
              <li>D. W. Embley. <i>Multifaceted exploitation of 
              metadata for attribute match discovery in information<br>
              integration</i>. In WIIW, 2001. </li>
            </ul>
            </li>
            <li><b>Instance</b> 
            <ul>
              <li>A. Doan, J. Madhavan, P. Domingos, and A. 
              Halevy. <i>Learning to map between ontologies on the<br>
              semantic web</i>. In Proc. of the Int. WWW Conf., 2002. 
              </li>
            </ul>
            </li>
            <li><b>Constraint</b> 
            <ul>
              <li>P. Mitra, G. Wiederhold, and M. Kersten. <i>A 
              graph-oriented model for articulation of ontology 
              interdependencies</i>. In Pro. of Extending DataBase Technologies, 
              2000. </li>
              <li>S. Bergamaschi, S. Castano, M. Vincini, and D. 
              Beneventano. <i>Semantic integration of heterogeneous<br>
              information sources</i>. Data &amp; Knowledge Engineering, 36(3), 
              2001. </li>
              <li>J. Kang and J. Naughton. <i>On schema matching 
              with opaque column names and data values</i>. In Proc. of SIGMOD, 
              2003. </li>
            </ul>
            </li>
          </ul>
          </li>
          <li><b>Structure-level Matching</b>
          
          <ul>
            <li>T. Milo and S. Zohar. <i>Using schema matching to 
            simplify heterogeneous data translation</i>. In Proceedings<br>
            of the International Conference on Very Large Databases (VLDB), 
            1998. </li>
            <li>L. Palopoli, D. Sacca, D. Ursino. <i>An automatic 
            technique for detecting type conflicts in database schemas</i>. CIKM, 
            306-313, 1998. </li>
            <li>J. Madhavan, P. Bernstein, and E. Rahm. <i>
            Generic schema matching with Cupid</i>. In Proceedings of the<br>
            International Conference on Very Large Databases (VLDB), 2001.
            </li>
            <li>S. Melnik, H. Garcia-Molina, and E. Rahm. <i>
            Similarity Flooding: A Versatile Graph Matching Algorithm</i>.<br>
            In Proc. of ICDE, 2002. </li>
            <li>Lerner BS. <i>A model for compound type changes 
            encountered in schema evolution. </i>ACM TODS 25(1):83-127, 2000.
            </li>
            <li>K. Zhang and D Shasha. <i>Approximate tree 
            pattern matching. </i>Pattern matching in strings, trees, and 
            arrays, 341-371, 1997. </li>
            <li>D. Calvanese, S. Castano, F. Guerra, D. Lembo, M. 
            Melchiorri, G. Terracina, D. Ursino, and M. Vincini.<br>
            <i>Towards a Comprehensive Framework for Semantic Integration of 
            Highly Heterogeneous Data Sources.</i><br>
            In Proc. of the 8th Int. Workshop on Knowledge Representation meets 
            Databases (KRDB2001), 2001. </li>
            <li>L. Xu and D. Embley. <i>Discovering Direct and 
            Indirect Matches for Schema Elements</i>. In DASFAA,<br>
            2003. </li>
          </ul>
          </li>
          <li><b>Combining Matchers</b>
          
          <ul>
            <li>A. Doan, P. Domingos, and A. Halevy. <i>
            Reconciling schemas of disparate data sources: a machine<br>
            learning approach</i>. In Proc. of SIGMOD, 2001. </li>
            <li>H.-H. Do and E. Rahm. <i>COMA - A System for 
            Flexible Combination of Schema Matching Approaches</i>.<br>
            In Proc. of VLDB, 2002. </li>
          </ul>
          </li>
          <li><b>Cluster-based Matching</b>
          
          <ul>
            <li>W. Wu, C. Yu, A. Doan, and W. Meng. <i>An 
            interactive clustering-based approach to integrating source<br>
            query interfaces on the deep web</i>. In Proc. of SIGMOD, 2004.
            </li>
            <li>B. He and K. C.-C. Chang. <i>Statistical schema 
            integration across the deep web</i>. In Proc. of SIGMOD,<br>
            2003. </li>
            <li>W. Li and C. Clifton. <i>SemInt: a tool for 
            identifying attribute correspondences in heterogeneous<br>
            databases using neural network</i>. Data Knowledge Engineering, 
            33(1), 2000. </li>
            <li>S. Castano, V. De Antonellis, and S. De Capitani 
            di Vemercati. <i>Global viewing of heterogeneous data sources. </i>
            IEEE Trans Data Knowl Eng 13(2):277-297, 2001. </li>
          </ul>
          </li>
          <li><b>Learn from Previous Matching</b>
          
          <ul>
            <li>J. Madhavan, P. Bernstein, A. Doan, and A. 
            Halevy. <i>Corpus-basd schema matching</i>. In Proc. of ICDE,<br>
            2005. </li>
            <li>Jayant Madhavan, Philip A. 
            Bernstein, Kuang Chen, Alon Halevy, and Pradeep Shenoy. <i>
            Corpus-based Schema Matching</i>. In Workshop on Information 
            Integration on the Web at IJCAI, 2003. </li>
          </ul>
          </li>
          <li><b>Query Discovery</b> 
          <ul>
            <li>R. J. Miller, L. M. Haas, and M. A. Hernandez. <i>
            Schema mapping as query discovery</i>. In VLDB, 2000 </li>
          </ul>
          <p><font face="Comic Sans MS" size="1"><a href="../resources.php">Up 
          to top</font></a></li>
        </ul>
        <h4 align="left"><a name="metadata"></a>Meta Data Management</h4>
        <ul>
          <li>
          <p align="left"><b>Meta Data Applications</b>
          
          <ul>
            <li>
            <p align="left">Lucian Popa, Yannis Velegrakis, Renee 
			J. Miller, Mauricio A. Hernández, Ronald Fagin: <i>Translating Web Data</i>, VLDB 2002. </li>
            <li>
            <p align="left">Stefano Spaccapietra, Christine 
            Parent: <i>View Integration: A Step Forward in Solving Structural Conflicts</i>. 
            TKDE 6(2): 258-274 (1994) </li>
          </ul>
          </li>
          <li>
          <p align="left"><b>Data Models</b>
          
          <ul>
            <li>
            <p align="left">Natalya F. Noy, 
            Mark A. Musen, Jose L.V. Mejino, and Cornelius Rosse: <i>Pushing the Envelope: Challenges in a Frame-Based Representation of 
            Human Anatomy.</i> SMI Report Number: SMI-2002-0925,
            <a href="http://smi-web.stanford.edu/pubs/SMI_Abstracts/SMI-2002-0925.html">
            http://smi-web.stanford.edu/pubs/SMI_Abstracts/SMI-2002-0925.html</a>.
            </li>
            <li>
            <p align="left">Richard Hull:
            <i>Relative Information Capacity of Simple Relational Database Schemata</i>. 
            PODS 1984: 97-109 </li>
          </ul>
          </li>
          <li>
          <p align="left"><b>Mechanisms</b>
          
          <ul>
            <li>
            <p align="left">Paolo Atzeni, Riccardo Torlone: <i>Management of Multiple Models in an Extensible Database Design Tool</i>. 
            EDBT 1996: 79-95. </li>
            <li>
            <p align="left">Philip A. Bernstein: <i>Applying Model Management to Classical Meta Data Problems</i> 
            submitted for publication </li>
            <li>
            <p align="left">Peter Buneman, Susan B. Davidson, 
            Anthony Kosky: <i>Theoretical Aspects of Schema Merging</i>. EDBT, 152-167, 1992.
            </li>
          </ul>
          </li>
        </ul>
        <blockquote>
          <p align="left"><font face="Comic Sans MS" size="1">
          <a href="../resources.php">Up to top</a></font></p>
        </blockquote>
        <h4 align="left"><a name="record-linkage"></a>Object Matching (a.k.a Record 
        Linkage)</h4>
        <ul>
          <li><b>History and overview: </b>
          <ul>
            <li>
            <p align="left"><b>Origination:</b><i> 
            H. Newcombe, J. Kennedy, S. Axford, and A. James. </i>Automatic 
            linkage of vital records<i>. </i>In Science 130 (1959), no. 3381, 
            pages 954-959, 1959. </li>
            <li><b>First formalization:</b><i> 
            Ivan Felligi and Alan Sunter.</i>
            A theory for record linkage. Journal of the American Statistical 
            Society, 64:1183--1210, 1969. </li>
            <li><b>Survey:</b> 
            <ul>
              <li><i>William Winkler.</i>
              Overview of record linkage and current research directions. 
              Technical Report, Statistical Research Division, U.S. Bureau of 
              the Census, 2006. </li>
              <li><i>Lifang Gu, Rohan 
              Baxter, Deanne Vickers, and Chris Rainsford. </i>
              
              Record Linkage: Current Practice and Future Directions. 
              Unpublished, 2004. </li>
              <li>
              <p align="left"><i>M. Bilenko, R. Mooney, W. Cohen, 
              P. Ravikumar, and S. Fienberg</i>. Adaptive 
              name matching in information integration. IEEE Intelligent Systems 
              Special Issue on Information Integration on the Web, September 
              2003. (<i>Must-read</i>) </li>
              <li>
              <p align="left"><i>Mohamed G. Elfeky, Vassilios S. 
              Verykios and Ahmed K. Elmagarmid</i>. 
              TAILOR: A record linkage Toolbox. </li>
            </ul>
            </li>
          </ul>
          </li>
          <li><b>Field-wise Matching (String comparison)</b>
          
          <ul>
            <li><b>Survey:<i> </i></b><i>
            William Cohen, Pradeep Ravikumar and Stephen Fienberg.</i>
            A Comparison of String Distance Metrics for Name-Matching Tasks. 
            In Workshop on Information Integration on the Web (IIW), at IJCAI 
            2003. (<i>Must-read</i>) </li>
            <li><i>William Winkler and Edward Porter.</i>
            Approximate String Comparison and its effect on an Advanced Record 
            Linkage System. Technical report, Statistical Research Division, 
            U.S. Bureau of the Census, 1997. </li>
            <li><b>Adaptive string matching</b>
            
            <ul>
              <li><i>Mikhail Bilenko and Raymond Mooney.</i>
              Adaptive Duplicate Detection Using Learnable String Similarity 
              Measures. In Proceedings of the 9th ACM SIGKDD International 
              Conference on Knowledge Discovery and Data Mining (KDD-2003), 
              pp.39-48, Washington, DC, August 2003. </li>
              <li>
              <p align="left"><i>S. Tejada, C. Knoblock, and S. 
              Minton</i>. Learning domain-independent 
              string transformation weights for high accuracy object 
              identification. In SIGKDD, 2002. </li>
            </ul>
            </li>
          </ul>
          </li>
          <li><b>Record-wise Matching</b>
          
          <ul>
            <li><b>Rule-based:</b> 
            <ul>
              <li>
              <p align="left"><i>H. Galhardas, D. Florescu, D. 
              Shasha, E. Simon, and C.-A. Saita</i>. 
              Declarative data cleaning: language, model, and algorithms. In 
              VLDB, pages 371-380, 2001. </li>
              <li>
              <p align="left"><i>L. Jin, C. Li, and S. Mehrotra</i>. 
              Efficient Record Linkage in Large Data Sets. In DASFAA, 2003.
              </li>
              <li>
              <p align="left"><i>M. L. Lee, T. W. Ling, and W. L. 
              Low</i>. Intelliclean: a knowledge-based 
              intelligent data cleaner. In SIGKDD, pages 290-294, 2000. 
              </li>
            </ul>
            </li>
            <li><b>EM Method:</b>
            
            <ul>
              <li><i>William Winkler.</i>
              Using the EM Algorithm for Weight Computation in the 
              Felligi-Sunter Model of Record Linkage. Technical Report 
              RR2000/05, Statistical Research Division, Bureau of Census, 2000.
              </li>
              <li><i>William Winkler</i>: 
              Advanced methods for record linkage. Technical Report, 1994.
              </li>
            </ul>
            </li>
            <li><b>Learning:</b> 
            <ul>
              <li><i>Jose C. Pinheiro and Don X. Sun.</i> 
              Methods for linking and mining massive heterogeneous databases. 
              AAAI, 1998. </li>
              <li>
              <p align="left"><i>W. Cohen and J. Richman.</i> 
              Learning to match and cluster large high-dimensional data sets for 
              data integration, 2002. </li>
              <li>
              <p align="left"><i>Sunita 
              Sarawagi and Anuradha Bhamidipaty.</i>
              Interactive Deduplication using Active Learning. In 
              Proceedings of the ACM SIGKDD, 2002. </li>
              <li>
              <p align="left"><b>Decision Tree:</b>
              <i>S. Tejada, C. Knoblock, and S. Minton</i>: Learning 
              domain-independent string transformation weights for high accuracy 
              object identi&Oslash;cation. In SIGKDD, 2002. </li>
              <li>
              <p align="left"><b>Bayes and SVM:<i> </i>
              </b><i>S. Sarawagi and A. Bhamidipaty</i>: 
              Interactive deduplication using active learning. In SIGKDD, 2002.
              </li>
            </ul>
            </li>
            <li>
            <p align="left"><b>Secondary Knowledge</b>
            
            <ul>
              <li>
              <p align="left"><i>A. Doan, Y. Lu, Y. Lee, and J. 
              Han</i>. Object matching for information 
              integration: a pro&Oslash;ler-based approach. In IIWeb, 2003. 
              </li>
              <li>
              <p align="left"><i>X. Dong and A. Halevy</i>. 
              A Platform for Personal Information Management and Integration. In 
              Proc. of CIDR, 2005. </li>
              <li>
              <p align="left"><i>M. Michalowski, S. Thakkar, and 
              C. A. Knoblock</i>. Exploiting secondary 
              sources for unsupervised record linkage. In IIWeb, 2004. 
              </li>
            </ul>
            </li>
          </ul>
          </li>
          <li><b>Collective Model</b>
          
          <ul>
            <li><i>William Cohen, David McAllester, and Henry 
            Kautz.</i>
            Hardening Soft Information Sources. In Proceedings of ACM SIGKDD, 
            2000, 255-259. </li>
            <li><i>Hanna Pasula, Bhaskara Marthi, Brian Milch, 
            Stuart Russell, and Ilya Shpitser.</i>
            Identity Uncertainty and Citation Matching. In Proceedings of 
            the International Conference on Advances in Neural Information 
            Processing Systems (NIPS) 15, 2003. </li>
            <li><i>Andrew McCallum and Ben Wellner</i>. 
            Toward conditional models of identity uncertainty with application 
            to proper noun coreference. IJCAI 2003. </li>
            <li>
            <p align="left"><i>Parag and P. 
            Domingos</i>. Multi-relational record linkage. 
            In MRDM, 2004. </li>
            <li>
            <p align="left"><i>R. Ananthakrishna, S. Chaudhuri, 
            and V. Ganti</i>. Eliminating Fuzzy Duplicates 
            in Data Warehouses. In Proc. of VLDB, 2002. </li>
            <li>
            <p align="left"><i>I. Bhattacharya and L. Getoor</i>. 
            Iterative record linkage for cleaning and integration. In DMKD, 
            2004. </li>
            <li>
            <p align="left"><i>D. V. Kalashnikov, S. Mehrotra, 
            and Z. Chen</i>. Exploiting relationships for 
            domain-independent data cleaning. In SIAM Data Mining (SDM), 2005.
            </li>
            <li>
            <p align="left"><i>Xin Dong, 
            Alon Halevy, Jayant Madhavan. </i>Reference 
            reconciliation in complex data spaces. In Sigmod, 2005. </li>
          </ul>
          </li>
          <li><b>Efficiency and Scalability</b>
          
          <ul>
            <li><i>Mauricio Hernandez and Salvatore Stolfo.</i>
            The Merge/Purge Problem for Large Databases. In Proceedings of 
            the ACM SIGMOD Conference, 1995. </li>
            <li><i>Andrew McCallum, Kamal Nigam and Lyle Ungar.</i>
            Efficient Clustering of High-Dimensional Data Sets with Application 
            to Reference Matching. In Proceedings of the ACM SIGKDD, 2000. (<i>Must 
            read -- classical paper for canopy)</i> </li>
            <li><i>Surajit Chaudhuri, Kris 
            Ganjam, Venkatesh Ganti, and Rajeev Motwani.</i>
            Robust and Efficient Fuzzy Match for Online Data cleaning. In 
            Proceedings of the ACM SIGMOD, 2003. </li>
            <li><i>Rohit Ananthakrishna, 
            Surajit Chaudhuri, and Venkatesh Ganti.</i>
            Eliminating Fuzzy Duplicates in Data Warehouses. VLDB 2002.
            </li>
          </ul>
          <p><font face="Comic Sans MS" size="1"><a href="../resources.php">Up 
          to top</a></p></font>
          </li>
        </ul>
        						<h4><a name="fusion"></a><b>Data </b>
								Fusion</h4>
								<ul>
									<li><b>Survey &amp; Tutorial</b><ul>
									<li><i>J. Bleiholder and F. Naumann. </i>Conflicting handling strategies in an 
									integrated information system. In <i>WWW'06.</i></li>
									<li><i>J. Bleiholder and F. Naumann. </i>
									Data fusion. <i>ACM Computing Surveys, 
									41(1):1–41, 2008.</i></li>
									<li><i>Xin Luna Dong and Felix Naumann</i>. 
									Data fusion--Resolving data conflicts for 
									integration. Tutorial in <i>VLDB</i>, 2009.</li>
								</ul>
        							</li>
									<li><b>Truth Discovery</b><ul>
									<li><i>M. Wu and A. Marian. </i>Corroborating answers from multiple web 
									sources.<i> </i>In <i>WebDB'07. (Initial 
									thought for conflict resolving)</i></li>
									<li><i>X. Yin, J. Han, and P. S. Yu. </i>Truth discovery with multiple conflicting 
									information providers on the web. In <i>SIGKDD'07. 
									(First Bayesian model considering source 
									accuracy)</i></li>
									<li>Xin Luna Dong, Laure Berti-Equille, and 
									Divesh Srivastava. Integrating conflicting 
									data: the role of source dependence. In <i>
									VLDB</i>, 2009. <i>(Refine Yin et al.'s 
									Bayesian model, and consider source copying)</i></li>
									<li><i>A. Galland, S. Abiteboul, A. Marian, 
									and P. Senellart. </i>Corroborating 
									information from disagreeing views. In<i> 
									WSDM, </i>2010<i>. (Cosine model and other 
									models; consider in addition accuracy on 
									each data item)</i></li>
									<li><i>A. Marian and M. Wu. </i>Corroborating 
									information from Web 
									sources.<i> IEEE Data Eng. Bull,</i> 34(3): 
									11-17 (2011). </li>
									<li><i>J. Pasternack and D. Roth. </i>
									Knowing what to believe (when you already 
									know something). In<i> COLING, </i>pages 
									877–885, 2010. <i>(Other models and a-priori 
									knowledge of truth for a subset of data 
									items)</i></li>
									<li><i>J. Pasternack and D. Roth. </i>Making 
									better informed trust decisions with 
									generalized fact-fiding. In <i>IJCAI, </i>
									pages 2324–2329, 2011. <i>(Consider 
									probabilistic claims, value similarities, 
									group beliefs, etc.)</i></li>
									<li><i>X. Yin and W. Tan. </i>
									Semi-supervised truth discovery. In <i>WWW,
									</i>2011<i>. (a-priori knowledge of truth 
									for a subset of data items)</i></li>
									<li>Xuan Liu, Xin Luna Dong, Beng Chin Ooi, 
									and Divesh Srivastava: Online data fusion. 
									In<i> VLDB'11.&nbsp; (First work on <b>
									online</b> fusion)</i></li>
								</ul>
        							</li>
									<li><b>Copy Detection</b><ul>
									<li>Xin Luna Dong and Divesh Srivastava. 
									Large-Scale Copying Detection. Tutorial in
									<i>Sigmod</i>, 2011.</li>
									<li>Xin Luna Dong, Laure Berti-Equille, and 
									Divesh Srivastava. Integrating conflicting 
									data: the role of source dependence. In <i>
									VLDB</i>, 2009. <i>(First work on copying 
									detection for structured data)</i></li>
									<li>Xin Luna Dong, Laure Berti-Equille, 
									Yifan Hu, and Divesh Srivastava. Global 
									detection of complex copying relationships 
									between sources. In <i>VLDB</i>, 2010 <i>
									(Extension for global detection)</i></li>
									<li>Anish Das Sarma, Xin Luna Dong, Alon 
									Halevy. Data integration with dependent 
									sources. In <i>EDBT</i>, 2011</li>
								</ul>
        							</li>
									<li><b>Fusion and Copying in a Dynamic World</b><ul>
									<li>Xin Luna Dong, Laure Berti-Equille, and 
									Divesh Srivastava. Truth discovery and 
									copying detection in a dynamic world. In <i>
									VLDB</i>, 2009.</li>
								</ul>
        							</li>
								</ul>
        <blockquote>
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								<h4><a name="uncertainty"></a><b>Data 
								Integration with Uncertainty</b></h4>
								<ul>
									<li><b>Probabilistic Schema Matching</b><ul>
										<li><i>Xin Dong, Alon Halevy, and Cong 
										Yu. </i>Data integration with 
										uncertainty. <i>VLDB'07.</i></li>
										<li><i>Carmel Domshlak, Avigdor Gal, and 
										Haggai Roitman. </i>Rank aggregation for 
										automatic schema matching. <i>TKDE 19(4)</i>, 
										2007</li>
										<li><i>Avigdor Gal. </i>Why is schema 
										matching tough and what can we do about 
										it. <i>Sigmod Record</i>, 35(4), 2006</li>
										<li><i>Avigdor Gal, Ateret Anaby-Tavor, 
										Alberto Trombetta, Danilo Montesi</i>. A 
										framework for modeling and evaluating 
										automatic semantic reconciliation. <i>
										VLDB Journal</i>, 2003.</li>
										<li><i>Henrik Nottelmann and Umberto 
										Straccia</i>. A probabilistic, 
										logic-based framework for automated web 
										directory alignment. </li>
										<li><i>Henrik Nottelmann and Umberto 
										Straccia</i>. Information retrieval and 
										machine learning for probabilistic 
										schema matching. <i>Information 
										Processing and Management 43:552-576</i>, 
										2007.</li>
									</ul>
									</li>
									<li><b>Generating Probabilistic Mediated 
									Schemas</b><ul>
										<li><i>Anish Das Sarma, Xin Dong, and 
										Alon Halevy. </i>Bootstrapping 
										pay-as-you-go data integration systems.<i> 
										Sigmod'08.</i></li>
										<li><i>M. Magnani, N. Rizopoulos, P. 
										Brien, and D. Montesi</i>. Schema 
										integration based on uncertain semantic 
										mappings. <i>Lecture Notes in Compute 
										Science, </i>2007.</li>
									</ul>
									</li>
								</ul>
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