Publications

Li, X., Talburt, J.R., Li, T. & Liu, X. (2019). Scoring Matrix Combined with Machine Learning for Heterogeneously Structured Entity Resolution. Consortium for Computing Sciences in Colleges, Little Rock, 2019

Alsarkhi, A & Talburt, J.R. (2019). An Analysis of the Effect of Stop Words on the Performance of the Matrix Comparator for Entity Resolution. Consortium for Computing Sciences in Colleges, Little Rock, 2019

Ye, Y & Talburt, J.R. (2019). Generating Synthetic Data to Support Entity Resolution Education and Research. Consortium for Computing Sciences in Colleges, Little Rock, 2019

Mahata, D., Kuriakose, J., Shah, R., Zimmermann , R & Talburt, J.R., (2018). Theme-weighted Ranking of Keywords from Text Documents using Phrase Embeddings2018 IEEE Conference on Multimedia Information Processing and Retrieval.

Talburt, J.R., Ye, Y., Zhong , B,. Li, X., True, J. & Srimal, S. (2018). The OYSTER Open Source Project for Introducing Entity Resolution and MDM int Information Systems CurriculaTwenty-fourth Americas Conference on Information Systems, New Orleans, 2018.

Alsarkhi, A. & Talburt, J.R.(2018). A Method for Implementing Probabilistic Entity Resolution. (IJACSA) International Journal of Advanced Computer Science and Applications.

Ye, Y & Talburt, J(2018). A Project-First Approach To Teaching Entity Resolution and Identity ManagementJournal of Computing Sciences in Colleges.

Ye, Y.*, Zhong, B*., Srimal, S.*, Alsarkhi, A.* &  Talburt, J.R.*(2018).  A Study on the Impact of Missing Values in Probabilistic Matching. The 2018 International Conference on Computational Science and Computational Intelligence (CSCI).

Kobayashi, F., Eram, A  & Talburt, J (2018). Entity Resolution Using Logistic Regression as an Extension to the Rule-Based Oyster System.

Li, X., Talburt, J.R. & Li, T (2018). Scoring Matrix for Unstandardized Data in Entity Resolution , The 2018 International Conference on Computational Science and Computational Intelligence. 

Wang, P., Pullen, D., Talburt, J.R.(2017). Comparison of Pre-and Post-Resolution Blocking Strategies for Entity Resolution in a Distributed Computing EnvironmentTwenty-third Americas Conference on Information Systems, Boston, 2017.

Wang, P., Pullen, D., Liu, F., Decker, W.,  Wu, N & Talburt, J.R. (2016). A Case Study on Data Quality, Privacy, and Evaluating the Outcome of Entity Resolution Processes. International Journal of Organizational and Collective Intelligence.

Kobayashi, F. & Talburt, J.R.(2015). Deciding Confidence for Identity Resolution in Closed and Open Universes of Entity Identity InformationThe Fifth International Conference on Business Intelligence and Technology

Chen, C., Pullen, P., Petty, R. &  Talburt, J.R. (2015). Methodology for Large-Scale Entity Resolution Without Pairwise Matching. 2015 IEEE 15th International Conference on Data Mining Workshops

Wang,  P., Pullen, D., Talburt, J.R., Wu, N.(2014). Iterative Approach to Weight Calculation in Probabilistic Entity Resolution. Proceedings of the 19th International Conference on Information Quality (ICIQ-2014).

Kobayashi, F., Talburt, J.R.(2014). Improving the Quality of Entity Resolution for School Enrollment Data through Affinity Scores. Proceedings of the 19th International Conference on Information Quality (ICIQ-2014)

Wang, P., Talburt, J.R., Pullen, D. & Wu, N. (2014). Probabilistic Matching Compared to Deterministic Matching for Student Enrollment Records.  2014 11th International Conference on Information Technology: New Generations.

Yeoh, W., Talburt, J.R. & Zhou, Y. (2014). Information Quality and Governance for Business Intelligence. A volume in the Advances in Business
Strategy and Competitive Advantage (ABSCA) Book Series

Talburt, J.R. & Zhou, Y. (2013). A practical guide to entity resolution with OYSTER. In Shazia Sadiq (Ed.), Handbook on Research and Practice in Data Quality, Springer.

Talburt, J.R. (2013) Overview: The criticality of entity resolution in data and information quality. The ACM Journal of Data and Information Quality (JDIQ), Vol 4, No. 2, pp. 6:1-2.

Zhou, Y., Nelson, E., Kobayashi, F. & Talburt, J.R. (2013). A Graduate-Level Course on Entity Resolution and Information Quality: A Step toward ER Education. The ACM Journal of Data and Information Quality (JDIQ), Vol 4, No. 2, pp. 10:1-10.

Osesina, I. & Talburt, J.R. (2012) A data-intensive approach to named entity recognition combining contextual and intrinsic indicators, International Journal of Business Intelligence Research 3(1) pp. 55-71.

Zhou, Y., Kooshesh, A., & Talburt, J.R. (2012) Optimizing the accuracy of entity-based data integration of multiple data sources using genetic programming methods. International Journal of Business Intelligence Research 3(1) pp. 72-82.

Zhou, Y., Talburt, J.R., & Nelson, E. (2011) The interaction of data, data structures, and software in entity resolution systems. Software Quality Professional 13(4) pp. 32-41.

Zhou, Y. & Talburt, J.R. (2011) Staging a Realistic Entity Resolution Challenge for Students, Journal of Computing Sciences in Colleges, 26(5), pp.88-95.

Talburt, J. (2011) Entity resolution and information quality. Burlington, MA: Morgan Kaufmann (Elsevier).

Holland, G. & Talburt, J.R. (2010). An entity-based integration framework for modeling and evaluating data enhancement products. Journal of Computing Sciences in Colleges, 24(5), 65-73.

Chan, Y., Talburt, J.R., & Talley, T. (Eds.) (2010). Data engineering: Mining, information and intelligence. Norwell, MA: Springer.

Wu, N., Talburt, J.R., Heien, C., Pippenger, N., Chiang, C., Pierce, E., Gulley, E., & Moore, J. (2007). A method for entity identification in open source documents with partially redacted attributes. The Journal of Computing Sciences in Colleges, 22(5), 138-144.

Zhou, Y., Talburt, J.R., & Nelson, E. (2013) User-defined inverted index in Boolean, rule-based entity resolution systems. 10th International Conference on Information Technology: New Generations (ITNG 2013), Las Vegas, Nevada, April 15-17, 2013 (pp. 608-612)

Penning, M. & Talburt, J.R. (2012) Information quality assessment and improvement of student information in the university environment. The 2012 International Conference on Information and Knowledge Engineering (IKE’12), Las Vegas, Nevada, July 16-29, 2012, (pp.351-357).

Syed, H., Talburt, J.R., Liu, F., Pullen, D., & Wu, N. (2012). Developing and refining matching rules for entity resolution. The 2012 International Conference on Information and Knowledge Engineering (IKE’12), Las Vegas, Nevada, July 16-29, 2012, (pp. 345-350).

Zhou, Y., Talburt, J.R., Kobayashi F., and Nelson E. (2012). Implementing Boolean matching rules in an entity resolution system using XML scripts. The 2012 International Conference on Information and Knowledge Engineering (IKE’12), Las Vegas, Nevada, July 16-29, 2012 (pp. 332-337).

Kobayashi, F. & Talburt, J.R. (2012). A review of relationship resolution: Terminology and classification. The 2012 International Conference on Information and Knowledge Engineering (IKE’12), Las Vegas, Nevada, July 16-29, 2012 (pp. 338-344).

Talburt, J.R. & Zhou, Y. (2012). OYSTER: An open source entity resolution system supporting identity information management. ID360 – The Global Forum on Identity, Austin, TX, April 23-24, 2012, Best Paper Award, (pp. 69-86).

Zhou, Y. & Talburt, J.R. (2011) Entity identity information management. International Conference on Information Quality 2011, Adelaide, Australia, November 18-20, 2011, electronic proceedings at http://iciq2011.unisa.edu.au/doc/ICIQ2011_Proceeding_Nov.zip

Kobayashi, F., Nelson, E.D., & Talburt, J.R. (2011) Design consideration for identity resolution in batch and interactive architectures. International Conference on Information Quality 2011, Adelaide, Australia, November 18-20, 2011, http://iciq2011.unisa.edu.au/doc/ICIQ2011_Proceeding_Nov.zip

Zhou, Y. & Talburt, J.R. (2011) The role of asserted resolution in entity identity information management, Proceedings: 2011 Information and Knowledge Engineering Conference (IKE 2011), Las Vegas, NV, July 18-20, 2011 (pp. 291-296).

Nelson, E. & Talburt, J.R. (2011) Entity resolution for longitudinal studies in education using OYSTER. Proceedings: 2011 Information and Knowledge Engineering Conference (IKE 2011), Las Vegas, NV, July 18-20, 2011 (pp. 286-290).

Varol, C. & Talburt, J.R. (2011) Pattern and phonetic based street name misspelling correction. 8th International Conference on Information Technology: New Generations (ITNG 2011), Las Vegas, Nevada, April 11-13, 2011 (pp. 553-558) DOI 10.1109.

Zhou, Y., Talburt, J.R., Su, Y., & Yin, L. (2010) OYSTER: A tool for entity resolution in health information exchange. 5th International Conference on the Cooperation and Promotion of Information Resources in Science and Technology (COINFO’10), Beijing, China, November 27-29, 2010 (pp. 356-362).

Osesina, I & Talburt, J.R. (2010) Towards a Data-Intensive Approach to Named Entity Recognition. 15th Annual International Conference on Information Quality, Little Rock, AR, November 12-14, 2010, iciq2010.org/proceedings.

Holland, G. & Talburt, J.R. (2010) q-Gram Tetrahedral Ratio (qTR) for approximate pattern matching. . Ninth Annual Conference on Applied Research in Information Technology, University of Central Arkansas, Conway, AR, April 9, 2010, research.acxiom.com/publications (pp. 14-17).

Talburt, J.R., Zhou, Y., & Shivaiah, S. (2009) SOG: A synthetic occupancy generator to support entity resolution instruction and research. 2009 International Conference on Information Quality, Potsdam, Germany, Nov. 2009 (pp. 91-105).

Talburt, J.R. & Nelson, E. (2009) CoDoSA: A light-weight, XML framework for integrating unstructured textual information. 15th Americas Conference on Information Systems, San Francisco, CA, AIS Electronic Library (aisel.asnet.org) Paper 489.

Talburt, J.R. & Chiang, C. (2009) Attributed identity resolution for fraud detection and prevention. 2009 IEEE International Conference on Computing in Engineering, Science and Information, California State University, Fullerton, CA (pp. 97-99).

Talburt, J.R. & Hashemi, R. (2008) A formal framework for defining entity-based, data source integration. H. Arabnia & R. Hashemi (Eds), 2008 International Conference on Information and Knowledge Engineering, Las Vegas, NV: CSREA Press (pp. 394-398).

Chiang, C., Talburt, J.R., Wu, N., Pierce, E., et.al. (2008) A case study in partial parsing unstructured text. Fifth International Conference on Information Technology: New Generations, Las Vegas, NV: IEEE Press (pp. 447-452).

Holland, G. & Talburt, J.R. (2008) A framework for evaluating information source interactions. C. Hu & D. Berleant (Eds), 2008 Conference on Applied Research in Information Technology, University of Central Arkansas, Conway, AR: http://research.acxiom.com/publications.html (pp. 13-19).

Nelson, E. & Talburt, J.R. (2008) Improving the quality of law enforcement information through entity resolution. C. Hu & D. Berleant (Eds), 2008 Conference on Applied Research in Information Technology, University of Central Arkansas, Conway, AR: http://research.acxiom.com/publications.html (pp. 113-118).

Talburt, J.R., Wu, N., Pierce, E., Chiang, C., Heien, C., Gulley, E. & Moore, J. (2007). Entity Identification in Documents Expressing Shared Relationships. N. Mastorakis, S. Kartalopoulos, D. Simian, A. Varonides, V. Mladenov, Z. Bojkovic, E. Antonidakis (Eds.), 11th World Scientific and Engineering Academy and Society International Conference on SYSTEMS (Vol. 2, pp. 223-228). Agios Nikolaos, Crete: WSEAS Press.

Talburt, J.R., Wu, N., Pierce, E., & Hashemi, R. (2007). Entity identification using indexed entity catalogs. In H.R. Arabnia & R.R. Hashemi (Eds.), The 2007 International Conference on Information and Knowledge Engineering (pp. 338-342). Las Vegas, NV: CSREA Press.

Hashemi, R., Talburt, J.R., & Wang, R. (2006). Significance test for the Talburt-Wang Similarity Index. In J. Talburt, E. Pierce, N. Wu, & T. Campbell (Eds.), 11th International Conference on Information Quality (pp. 125-132). Cambridge, MA: MIT IQ Publishing.

Talburt, J.R., Morgan, C., Talley, T. & Archer, K. (2005). Using commercial data integration technologies to improve the quality of anonymous entity resolution in the public sector. In F. Naumann, M. Gertz, & S. Madnick (Eds.), 10th International Conference on Information Quality (pp. 133-142), Cambridge, MA: MIT IQ Publishing.

Talburt, J.R., Kuo, E., Wang, R. & Hess, K. (2004). An algebraic approach to data quality metrics for customer recognition. In S. Chengular-Smith, L Raschid, J. Long, & C. Seko (Eds.), 9th International Conference on Information Quality (pp. 234-247). Cambridge, MA: MIT IQ Publishing.