A classification of semantic annotation systems
Semantic Web
A classification of semantic annotation systems
Semantic Web
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In today's Web-linked and data-rich world, there is a growing need to manage burgeoning amounts of information effectively. Although indexing and linking documents and other information sources is an important step, capturing the knowledge contained within these diverse sources is crucial for the effective use of large information repositories. Knowledge acquisition has been a challenging area of research in artificial intelligence, with its roots in early work to develop expert systems. Driven by the modern Internet culture and by knowledge-based industries, the study of knowledge acquisition has a renewed importance.Although there has been considerable work in the area of knowledge capture, activities have been distributed across several distinct research communities. In machine learning, learning apprentices acquire knowledge by nonintrusively watching a user perform a task. In the human-computer interaction community, programming-by-demonstration systems learn to perform a task by watching a user demonstrate how to accomplish it. In knowledge engineering, modeling techniques and design principles have been proposed for knowledge-based systems, often exploiting commonly occurring domain-independent inference structures and reusable domain-specific ontologies. In planning and process management, mixed-initiative systems acquire knowledge about a user's goals by taking commands or accepting advice regarding a task. In natural language processing, tools can process text and create representations of its knowledge content. All of these approaches are related in that they acquire information and organize it in knowledge structures that can be used for reasoning. They are complementary in that they use different techniques and approaches to capture different forms of knowledge.The aim of K-CAP 2001 is to provide a forum in which to bring together disparate research communities whose members are interested in efficiently capturing knowledge from a variety of sources and in creating representations that can be (or eventually can be) useful for reasoning. This new conference will promote multidisciplinary research that could result in a new generation of tools and methodologies for knowledge capture. The twenty six papers included in these proceedings cover many important topics for the conference, including ontologies/knowledge representation, interactive acquisition tools, collaborative/distributed KA, information extraction, knowledge management, semantic markup, adaptive user interfaces, PSMs, and learning from examples.