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Suggesting novel but related topics: towards context-based support for knowledge model extension

Maguitman, Ana ; Leake, David ; Reichherzer, Thomas

Proceedings of the 10th international conference on intelligent user interfaces, 10 January 2005, pp.207-214

ISBN: 1581138946 ; ISBN: 9781581138948 ; DOI: 10.1145/1040830.1040876

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  • Nhan đề:
    Suggesting novel but related topics: towards context-based support for knowledge model extension
  • Tác giả: Maguitman, Ana ; Leake, David ; Reichherzer, Thomas
  • Chủ đề: Automatic Topic Search ; Concept Mapping ; Context ; Human-Centered Knowledge Acquisition Tools ; Computer Science
  • Là 1 phần của: Proceedings of the 10th international conference on intelligent user interfaces, 10 January 2005, pp.207-214
  • Mô tả: Much intelligent user interfaces research addresses the problem of providing information relevant to a current user topic. However, little work addresses the complementary question of helping the user identify potential topics to explore next. In knowledge acquisition, this question is crucial to deciding how to extend previously-captured knowledge. This paper examines requirements for effective topic suggestion and presents a domain-independent topic-generation algorithm designed to generate candidate topics that are novel but related to the current context. The algorithm iteratively performs a cycle of topic formation, Web search for connected material, and context-based filtering. An experimental study shows that this approach significantly outperforms a baseline at developing new topics similar to those chosen by an expert for a hand-coded knowledge model.
  • Ngôn ngữ: English
  • Số nhận dạng: ISBN: 1581138946 ; ISBN: 9781581138948 ; DOI: 10.1145/1040830.1040876

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