Watch what I do: programming by demonstration
Watch what I do: programming by demonstration
User interface of a Home Page Reader
Assets '98 Proceedings of the third international ACM conference on Assistive technologies
An algorithm for suffix stripping
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Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Visualization and Analysis of Clickstream Data of Online Stores for Understanding Web Merchandising
Data Mining and Knowledge Discovery
Improving pseudo-relevance feedback in web information retrieval using web page segmentation
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Enhanced web document summarization using hyperlinks
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Programming by demonstration: a machine learning approach
Programming by demonstration: a machine learning approach
Automatic Discovery of Semantic Structures in HTML Documents
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
A Web page prediction model based on click-stream tree representation of user behavior
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Relationship-based clustering and cluster ensembles for high-dimensional data mining
Relationship-based clustering and cluster ensembles for high-dimensional data mining
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Computers in Industry - Special issue: Process/workflow mining
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Journal of the ACM (JACM)
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Csurf: a context-driven non-visual web-browser
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Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
CoScripter: automating & sharing how-to knowledge in the enterprise
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Assistive browser for conducting web transactions
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AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
PLOW: a collaborative task learning agent
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Transaction models for Web accessibility
World Wide Web
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Proceedings of the International Cross-Disciplinary Conference on Web Accessibility
Crowd-based recognition of web interaction patterns
Adjunct proceedings of the 25th annual ACM symposium on User interface software and technology
Predictive web automation assistant for people with vision impairments
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LiveAction: Automating Web Task Model Generation
ACM Transactions on Interactive Intelligent Systems (TiiS)
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Screen readers, the dominant assistive technology used by visually impaired people to access the Web, function by speaking out the content of the screen serially. Using screen readers for conducting online transactions can cause considerable information overload, because transactions, such as shopping and paying bills, typically involve a number of steps spanning several web pages. One can combat this overload by using a transaction model for web accessibility that presents only fragments of web pages that are needed for doing transactions. We can realize such a model by coupling a process automaton, encoding states of a transaction, with concept classifiers that identify page fragments "relevant" to a particular state of the transaction. In this paper we present a fully automated process that synergistically combines several techniques for transforming unlabeled click-stream data generated by transactions into a transactionmodel. These techniques include web content analysis to partition a web page into segments consisting of semantically related content, contextual analysis of data surrounding clickable objects in a page, and machine learning methods, such as clustering of page segments based on contextual analysis, statistical classification, and automata learning. The use of unlabeled click streams in building transaction models has important benefits: (i) visually impaired users do not have to depend on sighted users for creating manually labeled training data to construct the models; (ii) it is possible to mine personalized models from unlabeled transaction click-streams associated with sites that visually impaired users visit regularly; (iii) since unlabeled data is relatively easy to obtain, it is feasible to scale up the construction of domain-specific transaction models (e.g., separate models for shopping, airline reservations, bill payments, etc.); (iv) adjusting the performance of deployed models over timtime with new training data is also doable. We provide preliminary experimental evidence of the practical effectiveness of both domain-specific, as well as personalized accessibility transaction models built using our approach. Finally, this approach is applicable for building transaction models for mobile devices with limited-size displays, as well as for creating wrappers for information extraction from web sites.