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Titlebook: Database and Expert Systems Applications; 23rd International C Stephen W. Liddle,Klaus-Dieter Schewe,Xiaofang Zho Conference proceedings 20

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發(fā)表于 2025-3-26 21:20:51 | 只看該作者
32#
發(fā)表于 2025-3-27 03:18:56 | 只看該作者
33#
發(fā)表于 2025-3-27 08:08:20 | 只看該作者
Prediction of Web User Behavior by Discovering Temporal Relational Rules from Web Log Dataation systems, web mining has become an essential tool for discovering specific information on the Web. There are a lot of previous web mining techniques have been proposed. In this paper, an approach of temporal interval relational rule mining is applied to discover knowledge from web log data. Com
34#
發(fā)表于 2025-3-27 12:16:47 | 只看該作者
A Hybrid Approach to Text Categorization Applied to Semantic Annotationdel combined with n-grams. Given a specified content this technique takes care of choosing from different categories the one that best matches it. FLERSA is an annotation tool for web content where this technique is being used. The hybrid approach provides to FLERSA the capability for automatically
35#
發(fā)表于 2025-3-27 16:25:49 | 只看該作者
An Unsupervised Framework for Topological Relations Extraction from Geographic Documentssearch project which aims at geo-referencing document contents, hence making the realization of a Geographical Information Retrieval system possible. The driving factor of this research is the huge amount of Web documents which mention geographic places and relate them spatially. Several approaches
36#
發(fā)表于 2025-3-27 20:59:26 | 只看該作者
37#
發(fā)表于 2025-3-28 01:30:42 | 只看該作者
38#
發(fā)表于 2025-3-28 02:41:07 | 只看該作者
Cause Analysis of New Incidents by Using Failure Knowledge Databasehis paper, to better analyze the causes of failed projects and incidents, we propose a novel topic-document-cause(TDC) model that reveals the corresponding relationships among topics, documents, and causes. We use the JST failure knowledge base to construct a TDC model with machine learning methods
39#
發(fā)表于 2025-3-28 07:23:37 | 只看該作者
Modeling and Querying Context-Aware Personal Information Spacesinformation for everyday use. It is characterized by its heterogeneity, its dispersion and its redundancy. In this paper, our reflection focused on the development of a model that will be user-based. It help him create his data model depending on his needs.The meta-model that we propose allows users
40#
發(fā)表于 2025-3-28 13:56:39 | 只看該作者
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