Using Semantics to Identify Web Objects

Nathanael Chambers, James Allen, Lucian Galescu, Hyuckchul Jung, William Taysom

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 identification 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.

Subjects: 1.10 Information Retrieval; 13. Natural Language Processing

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