Catálogo de publicaciones - libros
Discovery Science: 10th International Conference, DS 2007 Sendai, Japan, October 1-4, 2007. Proceedings
Vincent Corruble ; Masayuki Takeda ; Einoshin Suzuki (eds.)
En conferencia: 10º International Conference on Discovery Science (DS) . Sendai, Japan . October 1, 2007 - October 4, 2007
Resumen/Descripción – provisto por la editorial
No disponible.
Palabras clave – provistas por la editorial
Philosophy of Science; Artificial Intelligence (incl. Robotics); Database Management; Information Storage and Retrieval; Computer Appl. in Administrative Data Processing; Computer Appl. in Social and Behavioral Sciences
Disponibilidad
| Institución detectada | Año de publicación | Navegá | Descargá | Solicitá |
|---|---|---|---|---|
| No detectada | 2007 | SpringerLink |
Información
Tipo de recurso:
libros
ISBN impreso
978-3-540-75487-9
ISBN electrónico
978-3-540-75488-6
Editor responsable
Springer Nature
País de edición
Reino Unido
Fecha de publicación
2007
Información sobre derechos de publicación
© Springer-Verlag Berlin Heidelberg 2007
Cobertura temática
Tabla de contenidos
Mining Subtrees with Frequent Occurrence of Similar Subtrees
Hisashi Tosaka; Atsuyoshi Nakamura; Mineichi Kudo
We study a novel problem of mining subtrees with frequent occurrence of similar subtrees, and propose an algorithm for this problem. In our problem setting, frequency of a subtree is counted not only for equivalent subtrees but also for similar subtrees. According to our experiment using tag trees of web pages, this problem can be solved fast enough for practical use. An encouraging result was obtained in a preliminary experiment for data record extraction from web pages using our mining method.
- Regular Papers | Pp. 286-290
Semantic Based Real-Time Clustering for PubMed Literatures
Ruey-Ling Yeh; Ching Liu; Ben-Chang Shia; I-Jen Chiang; Wen-Wen Yang; Hsiang-Chun Tsai
This paper addresses to use the latent semantic topology to real-time cluster the literatures retrieved by PubMed in response to clinical queries and evaluates its performance by professional experts. The result shows that semantic clusters properly offer an exploratory view on the returned search results, which saves users’ time to understand them. Besides, most experts conceive that the documents assigned to the identical cluster are similar and the concepts of clusters are appropriate.
- Regular Papers | Pp. 291-295