Ontology-based extraction and structuring of information from data-rich unstructured documents
Proceedings of the seventh international conference on Information and knowledge management
A hierarchical approach to wrapper induction
Proceedings of the third annual conference on Autonomous Agents
Generating finite-state transducers for semi-structured data extraction from the Web
Information Systems - Special issue on semistructured data
An architecture for more realistic conversational systems
Proceedings of the 6th international conference on Intelligent user interfaces
Mixed-initiative, multi-source information assistants
Proceedings of the 10th international conference on World Wide Web
Extraction Techniques for Mining Services from Web Sources
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Using the structure of Web sites for automatic segmentation of tables
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Evaluation metrics for generation
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Demonstration of PLOW: a dialogue system for one-shot task learning
NAACL-Demonstrations '07 Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
PLOW: a collaborative task learning agent
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
No Code Required: Giving Users Tools to Transform the Web
No Code Required: Giving Users Tools to Transform the Web
Extracting significant Website Key Objects: A Semantic Web mining approach
Engineering Applications of Artificial Intelligence
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Many common web tasks can be automated by algorithms that are able to identify web objects relevant to the user's needs. This paper presents a novel approach to web object identificalion that finds relationships between the user's actions and linguistic information associated with web objects. From a single training example involving demonstration and a natural language description, we create a parameterized object description. The approach performs as well as a popular web wrapper on a routine task, but it has the additional capability of performing in dynamic environments and the attractive property of being reusable in other domains without additional training.