Walter Chang
Principal Scientist
San Jose
Walter joined Adobe’s Advanced Technology Labs in 2004. He is a Principal Scientist and Research Manager of the Natural Language Group in the Media Intelligence Lab of Adobe Research in San Jose, CA. This group develops new technologies for multi-modal content understanding and interaction, intelligent conversational agents, document understanding systems, and systems for knowledge acquisition and representation.
He is currently focused on joint language and vision understanding of multimodal content, and semantic understanding of natural language documents. He is interested in the development of hybrid symbolic and machine learning systems to perform deeper understanding of text, audio, and video content for intelligent assistants, advanced search, content organization, automatic metadata extraction, temporal metadata synchronization, and metadata inferencing.
His related research interests include: computational linguistics, automatic ontology acquisition and generation, semantic parsing, named entity recognition, and extending relational, entity-relationship, and document object models to represent complex knowledge structures. He was a contributor and Adobe representative to the W3C RDF-Schema Working Group and has published in the areas of NLP, Semantic Web knowledge representations, extensible database architectures, and document indexing methods.
Prior to Adobe ATL, Walter was a managing director and systems architect at Scient (now Razorfish) and previously an engineering manager at Oracle Corporation. From 1984–1989, he was an advisory level programmer in the Extensible Database Group at the IBM Almaden Research Center where he had the privilege of being mentored by Prof. Hans Schek, Dr. Guy Lohman, and Dr. Bruce Lindsay.
Walter received his BS degree in electrical engineering and computer science from U.C. Berkeley and also holds a master’s degree in computer architecture from Santa Clara University.
Patents
USPTO #8,060,506: A System For Automatically Selecting Document Categories and Keywords For Matching Ads Provided by Ad Aggregators, W. Chang, issued: Nov. 15, 2011.
USPTO #8,037,108 – An extensible system for automatically capturing, analyzing, and converting relational database schemas and data into RDF-Triplestores, W. Chang, issued: Oct. 11, 2011.
USPTO #7,873,640 – Method for Semantic Analysis of Documents to Select and Rank Contextual Advertising Keywords, W. Chang, issued: Jan. 18, 2011.
USPTO #7,644,052 – System and method for building ontologies to organize, search and classify documents. W. Chang, N. Ghamrawi, issued: Jan. 5, 2010.
USPTO #7,610,315 – System & method for determining and recommending document retention and security polices. W. Chang, L. Masinter, issued: Oct. 27, 2009.
USPTO# 7,580,918 – Method for efficiently representing and searching directed acyclic graph structures in databases. W. Chang, N. Ghamrawi, A. Swami, issued: August 25, 2009.
USPTO #5,737,736 – Oracle Corporation. Method and apparatus for storing resource objects using c-structure bind descriptors. W. Chang, issued: Apr. 7, 1998.
USPTO #5,319,779 – IBM Almaden Research Center. System for searching information using combinatorial signatures. W. Chang, H. Schek, issued: Jun. 7, 1994.
Patents Pending Issuance:
US Patent App. #13/039,177: Adobe Systems, Automatically Classifying Consumers in Marketing Micro-Segments for Targeted Delivery of Content, G Baum, W. Chang, filed: March 2, 2011.
US Patent App. #13/039,207: Adobe Systems, Method and System for Machine Definition and Specification of Marketing Micro-Segments, W. Chang, G. Baum, filed: March 2, 2011.
US Patent App. #13/039,242: Adobe Systems, Sequential Engine that Computes User and Offer Matching Membership into Marketing Micro-Segments, W. Chang, G. Baum, filed: March 2, 2011.
US Patent App. #13/039,257: Adobe Systems, A Scalable Engine that Computes Marketing Micro-Segments, W. Chang, G. Baum, filed: March 2, 2011.
US Patent App. #13/039,266: Adobe Systems, Persistent Metadata for User Controlled Policy for Advertising, G. Baum, W. Chang, filed: March 2, 2011.
US Patent App. #13/153,328: Adobe Systems, A System and Method to Automatically Expand an Ad Offer Inventory and Provide Automatic Offer Matching Based on Explicit and Implicit Consumer Interests, W. Chang, G. Baum, filed: June 3, 2011.
US Patent App. #12/789,708: Adobe Systems, A System to Time Align Movie Scripts to Video and Audio Content. W. Chang, filed: May 28, 2010.
US Patent App. #12/789,785, Adobe Systems: Movie script to text alignment enhancement by nonlinear interpolation, J. Scoggins, W. Chang. filed: May 28, 2010.
US Patent App. #12/789,791, Adobe Systems: Movie Script Align and Replace (automatic text replacement based on confidence scores) and related GUI, D. Kuspa, J, Scoggins, W. Chang, filed: May 28, 2010.
US Patent App. #12/789,720, Adobe Systems: Movie Script and Replace Umbrella Feature including workflows and enhancements, J.Scoggins, W. Chang, D. Kuspa, P. Ellis, C. Van Winkle, S. Hayhurst, filed: May 28, 2010.
US Patent App. #11/946,680: Adobe Systems, System to automatically generate unique global named entity identifiers to resolve named entities in a federated text mining environment. W. Chang, M. Welch, filed: Oct. 9, 2009.
US Patent App. #12/713,008: Adobe Systems: A System for Automatically Capturing, Converting, and Analyzing Movie Scripts. W. Chang, M Welch. filed: July 2009.
US Patent App. #12/471,814: Adobe Systems. An efficient algorithm to generate layout preserved text from PDF. E. Koh, W. Chang, filed: May 26, 2009.
US Patent App. #12/618,353: Adobe Systems, Multimodal Video Indexing, Search, and Content Disambiguation. W. Chang, M. Welch, filed: Sept. 3, 2009.
US Patent App. #12/332,297, A System for Creating Speech-to-Text Language Models for Generic Audio Content, W. Chang, M. Welch, filed: Dec. 10, 2008.
US Patent App. #12/332,309: Adobe Systems, A Multi-core Processing System For Performing Parallel Speech-to-Text Transcriptions, W. Chang, M. Welch, filed: Dec. 10, 2008.
US Patent App. #12/130,607: Adobe Systems. System for automatically extracting reading-order text and semantic entities from unstructured and semi-structured documents. E. Koh, W. Chang, filed: May 30, 2008.
US Patent App. #12/035,617: Adobe Systems. A system for locating and visualizing people expertise and document resources & their inter-relationships. W. Chang, N. Sakunkoo, filed: Feb. 22, 2008.
US Patent App. #12/035,628: Adobe Systems, A system for creating, visualizing and navigating semantic networks of information. N. Sakunkoo, W. Chang, filed: Feb. 22, 2008.
US Patent App. #11/728,069: Adobe Systems. A method of applying keywords from the analysis of documents to analyzed documents to facilitate ad content metadata insertion. W. Chang, N. Ghamrawi, filed: Mar. 23. 2007.
US Patent App. #11/365,198: Adobe Systems. A method for providing a set of information resources to assist in researching semantic entities in a document. W. Chang, filed: Feb. 28, 2006.
Invited Talks
- Chang. 2010.Adobe® Story and Creative Suite 5 – New Semantic Technologies for the Motion Picture and Video Industry. Semantic Technology Conference, June 24, 2010, San Jose, CA.
- Chang. 2009.An Ontology-Driven System for the Semantic Analysis of Multimedia Content. Semantic Technologies Conference, June 17, 2009, San Jose, CA.
- Chang, T. Tague. 2008.Emerging Semantic Ad Platforms. SDForum Semantic Web Special Interest Group, Palo Alto, CA.
- Chang. 2008. The Design of a Semantic Analysis Platform for a Contextual Advertising Application.2008 Semantic Technologies Conference Session, San Jose, CA.
- Chang, D. Bedford. 2007. Semantic Content Management Systems.2007 Semantic Technologies Conference Session, San Jose, CA.
Launched Websites
Ads for Adobe PDF – an online document analysis and contextualized advertising system for ad enabling PDF content in Adobe Reader using the Yahoo! ad network.
MLB.com – Major League Baseball Advanced Media Gameday – was the chief architect that led the engineering team that designed, built, and deployed a real-time multimedia architecture for MLBAM’s live game visualization, player stats, audio and video feeds, live player event capture, event synchronization to video, online video search, and event replay.
Sixdegrees.com – an early dot.com online social networking community, subsequently acquired by Youthstream Media Networks for $125M
My Publications
Published November 4, 2019
Analyzing Sentence Fusion in Abstractive Summarization
EMNLP 2019 Summarization Workshop
Logan Lebanoff, John Muchovej, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu
AI & Machine Learning 
Natural Language Processing
Published August 2, 2019
Scoring Sentence Singletons and Pairs for Abstractive Summarization
ACL 2019
Logan Lebanoff, Kaiqiang Song, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu
- AI & Machine Learning
- Natural Language Processing
Published December 2, 2018
A Comparison Study of Human Evaluated Automated Highlighting Systems
PACLIC
Sasha Spala, Franck Dernoncourt, Walter Chang, Carl Dockhorn
- AI & Machine Learning
- Natural Language Processing
Published September 2, 2018
A Framework for Speech Recognition Benchmarking
Proc. of Interspeech 2018
Franck Dernoncourt, Trung Bui, Walter Chang
- AI & Machine Learning
Audio
Published August 25, 2018
A Web-based Framework for Collecting and Assessing Highlighted Sentences in a Document
Proceedings of the 27th International Conference on Computational Linguistics (COLING): System Demonstrations
Sasha Spala, Franck Dernoncourt, Walter Chang, Carl Dockhorn
- AI & Machine Learning
- Natural Language Processing
Published July 12, 2018
Conversational Image Editing: Incremental Intent Identification in a New Dialogue Task
Proc. of SIGDIAL 2018
Ramesh Manuvinakurike, Trung Bui, Walter Chang, Kallirroi Georgila
Best Paper Award- AI & Machine Learning
Computer Vision, Imaging & Video 
Intelligent Agents & Assistants - Natural Language Processing
Published June 1, 2018
A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
Proceedings of NAACL-HLT 2018
Arman Cohan, Franck Dernoncourt, Doo Soon Kim, Trung Bui, Seokhwan Kim, Walter Chang, Nazli Goharian
- AI & Machine Learning
Document Intelligence - Natural Language Processing
Published May 11, 2018
A Repository of Corpora for Summarization
Eleventh International Conference on Language Resources and Evaluation (LREC)
Franck Dernoncourt, Mohammad Ghassemi, Walter Chang
- AI & Machine Learning
- Natural Language Processing
Published May 7, 2018
PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering
Proc. of LREC 2018
Andrei Dulceanu, Thang Le Dinh, Walter Chang, Trung Bui, Doo Soon Kim, Manh Chien Vu, Seokhwan Kim
- Natural Language Processing
Published May 7, 2018
Edit me: A Corpus and a Framework for Understanding Natural Language Image Editing
Proc. of LREC 2018
Ramesh Manuvinakurike, Jacqueline Brixey, Trung Bui, Walter Chang, Doo Soon Kim, Ron Artstein, Kallirroi Georgila
- Computer Vision, Imaging & Video
- Natural Language Processing
Published July 21, 2017
Relationship Proposal Networks
IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2017
Ji Zhang, Mohamed Elhoseiny, Scott Cohen, Walter Chang, Ahmed Elgammal
- AI & Machine Learning
- Computer Vision, Imaging & Video
- Natural Language Processing
Published February 4, 2017
Towards Richer and Scalable Understanding of facts in Images
AAAI Conference on Artificial Intelligence
Mohamed Elhoseiny, Scott Cohen, Walter Chang, Brian Price, Ahmed Elgammal
- AI & Machine Learning
- Computer Vision, Imaging & Video
- Natural Language Processing
Published February 4, 2017
Sherlock: Scalable Fact Learning in Images
Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
Mohamed Elhoseiny, Scott Cohen, Walter Chang, Brian Price, Ahmed Elgammal
- AI & Machine Learning
- Computer Vision, Imaging & Video
- Natural Language Processing
Published April 2, 2016
Automatic Annotation of Structured Facts in Images
Vision and Language workshop
Mohamed Elhoseiny, Scott Cohen, Walter Chang, Brian Price, Ahmed Elgammal
- Computer Vision, Imaging & Video
- Natural Language Processing