Professional Life:

 

Xin Luna Dong
lunadong@fb.com
9845 Willows Rd.
Redmond, WA 98052
Tel: (650) 788-0228

 


 

Xin Luna Dong

 

I am the head scientist at Meta AR/VR Assistant, leading the ML efforts in building a smart personal assistant. We innovate and productionize techniques on contextual AI, search, question answering, recommendation, knowledge collection and mining, and multi-modal information management.

 

Prior to joining Meta, I spent nearly a decade working on knowledge graphs at Amazon and Google. Before that, I spent another decade working on data integration and cleaning at AT&T Labs and at Univ. of Washington, where I received my Ph.D in Computer Science. I have the great honor to be awarded ACM Distinguished Member for contributions in "data and knowledge integration" and the VLDB Early Career Research Contribution Award for "advancing the state of the art of knowledge fusion". 

 

You can find my (possibly out-of-date) C.V. here and resume here, and an interview at IEEE Industry Leaders in Signal Processing and Machine Learning Series. 

 


 

Research Areas and Selected Publications

 

Below is a list of my projects and selected papers categorized by research area. You can find the full list of my publications here, my DBLP entry here, and my Google Scholar entry here.

 

Knowledge collection, fusion, mining, and search

 

  • Book: Gerhard Weikum, Xin Luna Dong, Simon Razniewski and Fabian Suchanek. Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases. Barnes&Noble. 2021. [Link]
  • Podcast: Building the Product Knowledge Graph at Amazon. This Week in Machine Learning & AI (TWIML). 2021. [Link]
  • Benchmark: Extended SWDE Benchmark for knowledge extraction from semi-structured websites
  • Benchmark: DI2KG Benchmark for knowledge integration

 

  • Projects 

PGAmazon Product Graph We are building an authoritative knowledge graph for every product in the world, with the goal of answering any question about products and related knowledge.
[Podcast][Amazon Blog 1, Blog 2] [Talk1] [Talk2]

SonyaCeres extracts knowledge from semi-structured websites, which contains huge volume of factual knowledge. It supports both ClosedIE and OpenIE, where the former identifies new facts and new entities, and the latter adds new relationships and even new domains. [Talk][Benchmark]

KVSonyaKnowledge Vault / Knowledge-based Trust—Knowledge fusion and trustworthiness evaluation KV collects knowledge from the Web for building a probabilistic knowledge base. KBT evaluates Web source quality from a new angle--correctness of factual information. [Talk 1][Talk 2][Talk 3]

Quotes from Washington Posts [1, 2, 3]: Still, even the possibility of a search engine that evaluates truth is a pretty incredible breakthrough. And it definitely gives new meaning to the phrase "let me Google that for you."

  • Tutorials
    • [e-Commerce] Nasser Zalmout, Chenwei Zhang, Xian Li, Yan Liang, Xin Luna Dong. All you need to know to build a product knowledge graph. Tutorial in KDD'2021. [Website]
    • Colin Lockard, Prashant Shiralkar, Xin Luna Dong, Hannaneh Hajishirzi. Multi-modal information extraction from text, semi-structured, and tabular data on the web. Tutorial in WSDM'2020, ACL'2020, KDD'2020. [Website]
    • Xin Luna Dong, Christos Faloustos, Andrey Kan, Jun Ma, Subhabrata Mukherjee. Graph and tensor mining: for fun and for profit. Tutorial in SigKDD'18. [Website]
    • Xin Luna Dong, Christos Faloustos, Xian Li, Subhabrata Mukherjee, Prashant Shiralkar. Fact checking: theory and practice. Tutorial in SigKDD'18. [Website]
    • Xin Luna Dong and Divesh Srivastava. Knowledge curation and knowledge fusion: challenges, models, and applications. Tutorial in Sigmod'15. [PDF][Presentation]

     

  • Papers on taxonomy and ontology
    • [e-Commerce] Xinyang Zhang, Chenwei Zhang, Xian Li, Xin Luna Dong, Jingbo Shang, Christos Faloutsos, Jiawei Han. OA-Mine: Open-world attribute mining for e-Commerce products with weak supervision. In WebConf, 2022. [Link]
    • [e-Commerce] Xinyang Zhang, Chenwei Zhang, Xin Luna Dong, Jingbo Shang, Jiawei Han. Minimally-supervised structure-rich text categorization via liearning on text-rich networks. In WebConf, 2021. [Link]
    • [e-Commerce] Yuning Mao, Tong Zhao, Andrey Kan, Chenwei Zhang, Xin Luna Dong, Christos Faloutsos, Jiawei Han. Octet: Online catalog taxonomy enrichment with self-supervision. In SigKDD, 2020. [Link]
    • [e-Commerce] Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han. AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. In KDD, 2020. [Link]

     

  • Papers on knowledge extraction
    • [e-Commerce] Rongmei Lin, Xiang He, Jie Feng, Nasser Zalmout, Yan Liang, Li Xiong, Xin Luna Dong. PAM: Understanding product images in cross product category attribute extraction. In SigKDD, 2021. [Link]
    • [e-Commerce] Jun Yan, Nasser Zalmout, Yan Liang, Christan Grant, Xiang Ren, Xin Luna Dong. AdaTag: Multi-attribute value extraction from product profiles with adaptive decoding. In ACL, 2021. [Link]
    • Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong, Meng Jiang. TCN: Table convolutional network for web table interpretation. In WebConf, 2021. [Link]
    • [e-Commerce] Giannis Karamanolakis, Jun Ma, Xin Luna Dong. TXtract: Taxonomy-aware knowledge extraction for thousands of product categories. In ACL, 2020. [Link]
    • Colin Lockard, Prashant Shiralkar, Hannaneh Hajishirzi, Xin Luna Dong. ZeroShotCeres: Zero-shot relation extraction from semi-structured webpages. In ACL, 2020. [Link]
    • Colin Lockard, Prashant Shiralkar, Xin Luna Dong. OpenCeres: When open information extraction meets the semi-structured web. In NAACL, 2019. [Link]
    • Xiaolan Wang, Xin Luna Dong, Yang Li, Alexandra Meliou. MIDAS: Finding the right web sources to fill knowledge gaps. In ICDE, 2019. [PDF][Presentation]
    • Colin Lockard, Xin Luna Dong, Arash Einolghozati, Prashant Shiralkar. Ceres: Distantly supervised relation extraction from the semi-structured web. In VLDB, 2018. [Link]
    • [e-Commerce] Guineng Zheng, Subhabrata Mukherjee, Xin Luna Dong, Feifei Li. OpenTag: Open attribute value extraction from product profiles. In SigKDD, 2018. [Link]
    • [e-Commerce] Disheng Qiu, Luciano Barbosa, Xin Luna Dong, Yanyan Shen, Divesh Srivastava. DEXTER: Large-scale discovery and extraction of product specifications on the Web. In VLDB, 2016. [PDF]

     

  • Papers on knowledge integration
    • Di Jin, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Danai Koutra. Deep transfer learning for multi-source entity linkage via domain adaptation. In VLDB, 2022. [Link]
    • Zhengbao Jiang, Jialong Han, Bunyamin Sisman, Xin Luna Dong. CoRI: Collective relation integration with data augmentation for open information extraction. In ACL, 2021. [Link]
    • Zhengyang Wang, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Shuiwang Ji. CorDEL: A contrastive deep learning approach for entity linkage. In ICDM, 2020. [Link]
    • Qi Zhu, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, Jiawei Han. Collective multi-type entity alignment between knowledge graphs. In WebConf, 2020. [Link]
    • Wei Zhang, Hao Wei, Bunyamin Sisman, Xin Luna Dong, Christos Faloutsos, David Page. AutoBlock: A Hands-off Blocking Framework for Entity Matching. In WSDM, 2020. [Link]
    • [e-Commerce] Varun R. Embar, Bunyamin Sisman, Hao Wei, Xin Luna Dong, Christos Faloutsos, Lise Getoor. Contrastive Entity Linkage: Mining Variational Attributes from Large Catalogs for Entity Linkage. In AKBC, 2020. [Link]
    • Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Xin Luna Dong, Andrew McCallum. OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference. In NAACL, 2019. [Link]
    • Rakshit Trivedi, Bunyamin Sisman, Jun Ma, Christos Faloustos, Hongyuan Zha, Xin Luna Dong. LinkNBed: Multi-graph representation learning with entity linkage. In ACL, 2018. [Link]

     

  • Papers on knowledge fusion, cleaning and evaluation
    • [e-Commerce] Kewei Cheng, Xian Li, Yifan Xu, Xin Luna Dong, Yizhou Sun. PGE: Robust product graph embedding learning for error detection. In VLDB, 2022. [Link]
    • [e-Commerce] Yaqing Wang, Yifan Ethan Xu, Xian Li, Xin Luna Dong, Jing Gao. Automatic validation of textual attribute values in eCommerce Catalog by learning with limited labeled data. In KDD, 2020. [Link]
    • Junyang Gao, Xian Li, Yifan Ethan Xu, Bunyamin Sisman, Xin Luna Dong, and Jun Yang. Efficient knowledge graph accuracy evaluation. In VLDB, 2019. [Link]
    • Furong Li, Xin Luna Dong, Anno Largen, and Yang Li. Knowledge verification for long tail verticals. In VLDB, 2017. [PDF] [Report]
    • Xin Luna Dong, Evgeniy Gabrilovich, Kevin Murphy, Van Dang, Wilko Horn, Camillo Lugaresi, Shaohua Sun, and Wei Zhang. Knowledge-based trust: estimating the trustworthiness of web sources. In VLDB, 2015. [PDF][Presentation]
    • Xiaolan Wang, Xin Luna Dong, Alexandra Meliou. Data X-Ray: A diagnostic tool for data errors. In Sigmod, 2015. [PDF][Presentation][Demo]
    • Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, Kevin Murphy, Thomas Strohmann, Shaohua Sun, and Wei Zhang. Knowledge Vault: A Web-scale approach to probabilistic knowledge fusion. In SIGKDD, 2014. [PDF]
    • Xin Luna Dong, Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Kevin Murphy, Shaohua Sun, and Wei Zhang. From data fusion to knowledge fusion. In VLDB, 2014. [PDF][Presentation]

     

  • Papers on knowledge mining and search
    • [e-Commerce] Liqiang Xiao, Jun Ma, Xin Luna Dong, Pascual Martinez-Gomez, Nasser Zalmout, Wei Chen, Tong Zhao, Hao He, Yaohui Jin. End-to-end conversational search for online shopping with utterance transfer. In EMNLP, 2021. [Link]
    • [e-Commerce] Yikun Xian, Tong Zhao, Jin Li, Jim Chan, Andrey Kan, Jun Ma, Xin Luna Dong, Christos Faloutsos, George Karypis, S. Muthukrishnan, Yongfeng Zhang. EX3: Explainable Attribute-aware Item-set Recommendations. In RecSys, 2021. [Link]
    • [e-Commerce] Junheng Hao, Tong Zhao, Jin Li, Xin Luna Dong, Christos Faloutsos, Yizhou Sun, Wei Wang. P-Companion: A principled framework for diversified complementary product recommendation. In CIKM, 2020. [Link]
    • Namyong Park, Andrey Kan, Christos Faloutsos, Xin Luna Dong. J-Recs: Principled and scalable recommendation justification. In ICDM, 2020. [Link]
    • Namyong Park, Andrey Kan, Tong Zhao, Christos Faloutsos, Xin Luna Dong. MultiImport: Inferring node importance in a knowledge graph from multiple input signals. In SigKDD, 2020. [Link]
    • Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, and Christos Faloutsos. Estimating node importance in knowledge graphs using graph neural networks. In SigKDD, 2019. [Link]
    • Qi Song, Yinghui Wu, and Xin Luna Dong. Mining summaries for knowledge graph search. In ICDM, 2016. [PDF]
    • Tim Althoff, Xin Luna Dong, Kevin Murphy, Safa Alai, Van Dang, and Wei Zhang. TimeMachine: Timeline generation for knowledge-base entities. In SIGKDD 2015. [PDF][Presentation]

 

 

Data integration (Aspects of data integration)

 

  • Book: Xin Luna Dong and Divesh Srivastava. Big Data Integration (Synthesis Lectures on Data Management). Morgan Claypool Publishers. 2015. [Link]
  • Sigmod blog interview: Courting ML: Witnessing the marriage of relational & web data systems to machine learning. 2018. [Link]
  • Sigmod blog interview: The elephant in the room: getting value from Big Data. 2015. [Link]

  •  

  • Projects

 

  • Tutorials
    • Xin Luna Dong and Theodoros Rekatsinas: Data integration and machine learning: a natural synergy. Tutorial in Sigmod'2018, VLDB'2018, KDD'2019. [Slides][Sigmod video]
    • Xin Luna Dong and Wang-Chiew Tan: A Time Machine for Information: Looking Back to Look Forward. Tutorial in VLDB, 2015. [PDF][Slides][Survey]
    • Xin Luna Dong and Divesh Srivastava. Big data integration. Tutorial in ICDE'13, VLDB'13. [PDF] [Slides (short)] [Slides (long)]
    • Xin Luna Dong and Divesh Srivastava. Large-Scale Copy Detection. Tutorial in ICDE'12, DASFAA'12, Sigmod'11. [PDF][Presentation]
    • Xin Luna Dong and Felix Naumann. Data fusion--Resolving data conflicts for integration. In VLDB, 2009. [PDF][Presentation]

 

  • Papers on big data integration
    • Theodoros Rehatsinas, Xin Luna Dong, Lise Getoor, Divesh Srivastava. Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration In CIDR, 2015. [PDF][Presentation]
    • Theodoros Rehatsinas, Xin Luna Dong, Divesh Srivastava. Characterizing and selecting fresh data sources. In VLDB, 2014. [PDF][Presentation]
    • Xin Luna Dong, Barna Saha, and Divesh Srivastava. Less is more: Selecting sources wisely for integration. In VLDB, 2013. [PDF][Report] [Slides (short)] [Slides (long)]
    • Mariam Salloum, Xin Luna Dong, Divesh Srivastava, Vassilis J. Tsotras. Online ordering of overlapping data sources. In VLDB, 2014. [PDF][Presentation]
  • Papers on data fusion (Resolving value heterogeneity)
    • Ravali Pochampally, Anish Das Sarma, Xin Luna Dong, Alexandra Meliou, and Divesh Srivastava. Fusing data with correlations. In Sigmod, 2014. [PDF][Presentation][Poster]
    • Xian Li, Xin Luna Dong, Kenneth Lyons, Weiyi Meng, and Divesh Srivastava. Scaling up Copy Detection. In ICDE, 2015. [PDF][Report]
    • Xian Li, Xin Luna Dong, Kenneth Lyons, Weiyi Meng, and Divesh Srivastava. Truth finding on the Deep Web: Is the problem solved? In VLDB, 2013. [PDF][Report][Presentation]
    • Xin Luna Dong and Divesh Srivastava. Compact explanation of data fusion decisions. In WWW, 2013. [PDF][Report][Presentation]
    • Xuan Liu, Xin Luna Dong, Beng Chin Ooi, and Divesh Srivastava: Online data fusion. In VLDB, 2011. [PDF][Presentation]
    • Anish Das Sarma, Xin Luna Dong, Alon Halevy. Data integration with dependent sources. In EDBT, 2011. [PDF][Presentation]
    • Xin Luna Dong, Laure Berti-EquilleYifan Hu, and Divesh Srivastava. Global detection of complex copying relationships between sources. In VLDB, 2010. [PDF][Presentation]
    • Xin Luna Dong, Laure Berti-Equille, and Divesh Srivastava. Truth discovery and copying detection in a dynamic world. In VLDB, 2009. [PDF][Presentation]
    • Xin Luna Dong, Laure Berti-Equille, and Divesh Srivastava. Integrating conflicting data: the role of source dependence. In VLDB, 2009. [PDF][Presentation]
    • Laure Berti-EquilleAnish Das Sarma, Xin Luna Dong, Amelie Marian, and Divesh Srivastava. Sailing the information ocean with awareness of currents: discovery and application of source dependence. In CIDR, 2009. [PDF][Presentation]

 

  • Papers on record linkage (Resolving instance heterogeneity)
    • Wenfei Fan, Zhe Fan, Chao Tian, and Xin Luna Dong. Keys for Graphs. In VLDB 2015. [PDF][Presentation]
    • Pei Li, Xin Luna Dong, Songtao Guo, Andrea Maurino, and Divesh Srivastava. Robust group linkage. In WWW 2015. [PDF][Presentation][Report]
    • Anja Gruenheid, Xin Luna Dong, and Divesh Srivastava. Incremental record linkage. In VLDB 2014. [PDF][Report][Presentation]
    • Pei Li, Xin Luna Dong, Andrea Maurino, and Divesh Srivastava. Linking Temporal Records. In VLDB 2011. [PDF][Presentation][JournalVersion]
    • Songtao Guo, Xin Luna Dong, Divesh Srivastava, and Remi Zajac. Record Linkage with Uniqueness Constraints and Erroneous Values. In VLDB, 2010. [PDF][Presentation]
    • Xin Dong, Alon Y. Halevy and Jayant Madhavan: Reference Reconciliation in Complex Information Spaces. In SIGMOD 2005. [PDF][Presentation]

 

  • Papers on schema mapping and Dataspaces (Resolving structure heterogeneity)
    • Anish Das Sarma, Xin Dong, and Alon Y. Halevy: Bootstrapping Pay-as-you-go Data Integration Systems. In SIGMOD, 2008. [PDF]
    • Xin Dong, Alon Y. Halevy and Cong Yu: Data Integration with Uncertainties. In VLDB, 2007. [PDF][Presentation][DBClip][JournalVersion in "Best papers of VLDB 2007"]
    • Xin Dong and Alon Y. Halevy: Indexing Dataspaces. In SIGMOD, 2007. [PDF][Presentation]
    • Xin Dong and Alon Y. Halevy: A Platform for Personal Information Management and Integration. In CIDR 2005. [PDF][Presentation]
    • Xin Dong, Alon Y. Halevy, Jayant MadhavanEma Nemes and Jun Zhang: Similarity Search for Web Services. In VLDB 2004. [PDF][Presentation]
    • Xin Dong, Alon Y. Halevy and Igor Tatarinov: Containment of Nested XML Queries. In VLDB 2004. [PDF][Presentation][Tech-report]

 

 


 

 

Recent Talks

  • Next-Generation Intelligent Assistants for AR/VR Devices [PPT]

o   Keynote at SIAM International Conference on Data Mining (SDM), Online, April 2022.

o   Invited talk at Trustworthy Data Science and AI Seminar Series, Simon Fraser University, April 2022.

  • Zero to One Billion: The Path to a Rich Product Knowledge Graph [PPT]

o   Keynote at Northwest Database Scociety Annual Meeting, Seattle, WA, May 2022.

o   Keynote at AAAI Workshop on Deep Learning on Graphs: Method and Applications (DGL), Online, February 2022.

o   Keynote at WSDM Workshop on Machine Learning on Graphs (MLoG), Online, February 2022.

o   Keynote at AKBC Workshop on Unstructured/Structured KBs, Online, October 2021.

o   Keynote at SigKDD Workshop on Data Quality Assessment for Machine Learning (DQAML), Online, August 2021.

o   Keynote at SigIR Industry Track, Online, July 2021.

o   Keynote at European Semantic Web Conference (ESWC), Online, June 2021.

o   Lecture at Stanford CS520 Knowlege Graphs--Data Models, Knowledge Acquisition, Inference and Applications, May, 2021

  • Ceres: Harvesting Knowledge from Semi-Structured Web [PPT1] [PPT2]

o   Invited talk at SigKDD Workshop on Deriving Insights from User-Generated Text (WIT), Online, August 2021.

o   Keynote at Text Analysis Conference--Knowledge Base Population (TAC-KBP), Online, February 2021.

o   Invited talk at UCSB NLP Seminar, Santa Barbara, January 2021.

o   Keynote at Conference on Information and Knowledge Management (CIKM), Dublin, Iceland, October 2020.

o   Invited talk at Automated Knowledge Base Construction Conference (AKBC), Irvine, CA, June 2020.

o   Invited talk at Northwest Database Society Annual Meeting, Seattle, WA, January 2020.

o   Keynote at SigKDD Workshop on Truth Discovery and Fact Checking: Theory and Practice, Anchorage, AL, August 2019.

o   Keynote at SigIR Workshop on ExplainAble Recommendation and Search (EARS), Paris, France, July 2019.

o   Invited talk at Amsterdam Data Science at Sigmod/PODS'2019, Amsterdam, Netherland, July 2019.

o   Invited talk at ICML Workshop on Learning with Limited Labeled Data (LLD), New Orleans, LA, May 2019.

o   Keynote at SigKDD Workshop on Mining and Learning with Graphs (MLG), London, UK, August 2018.

 

Previous Talks

  • Self-Driving Product Understanding for Thousands of Categories. PHKG'2021 Keynote, DeMaL'2021 Keynote, NorthEast Univ. DATA lab speaker series 2020, KG & E-Commerce Workshop 2020 Keynote, KR2ML'2019 Invited talk. [PPT]
  • Knowledge Graph And Machine Learning: A Natural Synergy. Lecture at Stanford CS520 Knowlege Graphs--How should AI explicitly represent knowledge, 2020 [PPT, Class notes by course organizer]
  • Building A Broad Knowledge Graph for Products. ICDE'19 Keynote, SigIR eCOM'19 Keynote, AI NEXTCon Seattle'2019 Invited talk, EMNLP FEVER workshop'2019 Invited talk, Duke CS Colloquium 2018, Berkeley RISE Seminar 2018, SigKDD ADS Invited talk 2018, VLDB PhD workshop'2018 Keynote [PPT]
  • Challenges and Innovations in Building a Product Knowledge Graph. GRADES'18 Keynote, BIG'18 Invited talk, MoDas'18 Invited talk, KBCOM'18 Invited talk, Northwest DB Day'18 Invited talk, AKBC'17 Invited talk. [PPT]
  • Leaving No Valuable Data Behind: the Crazy Ideas and the Business. AMW'17 Keynote, Machine Learning Conference Seattle'17 Invited talk, Distinguished speaker series: Oxford Women in CS 2017, Methods to Manage Heterogenous Big Data and Polystore Databases Workshop 2016 Keynote, VLDB Early Career Research Contribution Award talk 2016 [PPT]
  • How Far Are We from Collecting the Knowledge in the World. WebDB'16 Keynote, ICWE'16 Keynote [PPT]
  • Knowledge Fusion and Knowledge-Based Trust. Quora Invited talk'15, Stanford Computer Systems Colloquium (EE380)'15 Invited talk, NorCal DB Day'15 [PPT]
  • From Data Fusion to Knowledge Fusion. WISA'14 Keynote, APWeb'14 Tutorial, WACCK'14 Keynote, DEOS'14 Keynote. [PPT]
  • Truth Finding on the Deep Web. WAIM'13 Distinguished Young Lecturer Series, DESWEB'13 Keynote. [PPT]
  • Linking Records w. Value Diversity. [PPT]
  • Develop Your Big Ideas. Sigmod new-researcher symposium'11. [PPT]
  • Large-Scale Copy Detection. Tutorial at DASFAA'12, ICDE'12, Sigmod'11. [PPT]
  • Solomon: Seeking the Truth Via Copying Detection. BEWEB'11 Invited talk,  QDB'10 Keynote. [PPT][Video]
  • Sailing the information ocean with awareness of currents: discovery and application of source dependence. Invited talk at Person Validation and Entity Resolution Conference'11 (US Census Bureau),  ISAT "What's Data Worth?" Workshop'10, NDBC'09, SKG'09. [PPT]
  • Data fusion--Resolving data conflicts for integration. Tutorial at VLDB'09, NDBC'09.[PPT]
  • Data integration with uncertainty. [PPT]
  • Managing a space of heterogeneous data. [PPT]
  • Semex: A platform for personal information management and integration. [PPT]

 

 


 

Patents

  • Similar but Different (SBD): Presenting Item Recommendations in Dynamically Generated Groups with Explanations. Andrey Kan, Christos Faloustos, and Xin Dong. United States Patent 10.891.676, issued 1/2021.
  • Providing User-Interactive Graphical Timelines. Xin Dong, Tim Althoff, Kevin Murphy, Safa Alai, Van Dang, and Wei Zhang. United States Patent, filed 9/2015, to be issued.
  • Method and Apparatus for Exploring and Selecting Data Sources. Xin Dong and Divesh Srivastava. United States Patent 20130138480, issued 5/30/2013.
  • Online Data Fusion. Xuan Liu, Xin Dong, Ben Chin Ooi and Divesh Srivastava. United States Patent, 20130144843, issued 12/5/2011.
  • Update Certificates. Su Chen, Xin Dong, Laks Lakshmanan, and Divesh Srivastava. United States Patent, filed 9/2010, to be issued.
  • Detecting Dependence Between Sources in Truth Discovery. Xin Dong, Laure Berti-Equille, Divesh Srivastava. United States Patent 8190546, issued 5/29/2012.
  • Minimal difference query and view matching. Raghav Kaushik, Venkatesh Ganti and Xin Dong. United States Patent 7251646, issued 7/31/2007.
  • Method and apparatus for updating XML views of relational data. Philip L. Bohannon, Xin
    Dong, Henry F. Korth, Suryanarayan Perinkulam. United States Patent 20050165866, filed Jan 28, 2004, to be issued.

 

 


 

Recent Professional Activities

 

 


 

Resources

  • Here is a long and growing list of papers in database, IR and AI that I have collected during my research and my readings.
  • Here is a collection of wisdoms on career, research, life, etc.

 

 

 

 

Personal Life:

 

Xin Luna Dong 董欣 
lunadong@gmail.com
Tel: (201) 650-3494


 

In my personal life, I am

 


 

Here are what I learned about research from my life.

  • Challenge yourself.

"I want to prove P<>NP!"

"Got it! It's because of the 'N'!"

  • Work hard.

    

  • Don't offend reviewers.

 

 

 

 

 

 

 

 

 

 

 

Last update: 3/2013