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In this paper, we present a Web content adaptation system that is able to automatically adapt textual elements of Web pages, based on the user profile and preferences. The system employs Web intelligence to perform these automatic adaptations on single elements composing a Web page. In particular, a reinforcement learning algorithm, i.e. Q-learning, based on the idea of reward/punishment is utilized...
This paper presents a multi-agent framework capable of learning teamwork by observation. The system combines proven single entity learning by observation techniques with a multi-agent system shown to exhibit effective teamwork. An effective simulated production team is observed. An off-line training algorithm uses the observed data to develop behavior maps for a Collaborative Context-based Reasoning...
This paper presents an approach to automatically identify potentially nocuous ambiguities, which occur when text is interpreted differently by different readers of requirements written in natural language. We extract a set of anaphora ambiguities from a range of requirements documents, and collect multiple human judgments on their interpretations. The judgment distribution is used to determine if...
Reduction techniques are important tools in machine learning and pattern recognition. In this article, we demonstrate how a kernel-based density estimator can be used as a tool for understanding human category representation. Despite the dominance of exemplar models of categorization, there is still ambiguity about the number of exemplars stored in memory. Here, we illustrate that by omitting exemplars...
An associative memory (AM) system is proposed to realize incremental learning and temporal sequence learning. The proposed system is constructed with three layer networks: The input layer inputs key vectors, response vectors, and the associative relation between vectors. The memory layer stores input vectors incrementally to corresponding classes. The associative layer builds associative relations...
The research in the ontology-based information retrieval has made a significant progress recently, especially in the Web domain. In this kind of retrieval system, the domain ontology is used as the backbone of the searching process. However, with the heterogeneity of data storing formats on the Web, many of ontology-driven systems development approach suffer from inconsistencies during mapping between...
This paper presents a discussion and simulation results which support the case for interaction during the acquisition of conceptual knowledge. Taking a developmental perspective, we first review a number of relevant insights on word-meaning acquisition in young children and specifically focus on concept learning supported by linguistic input. We present a computational model implementing a number...
This paper describes a research project that investigated the feasibility of using contextual reasoning to supervise the collaborative work of knowledge workers. In complex projects that require contributions from various experts but whose interaction may be limited to a web-based collaborative tool, proper management of the project is essential to ensure that the project objectives are met. This...
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