Despite the recent interest in extending Adaptive Hypermedia beyond the closed corpus domain and into the open corpus world of the web, many current approaches are limited by their reliance on closed metadata model re...
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ISBN:
(纸本)9781450313353
Despite the recent interest in extending Adaptive Hypermedia beyond the closed corpus domain and into the open corpus world of the web, many current approaches are limited by their reliance on closed metadata model repositories. The need to produce large quantities of high quality metadata is an expensive task which results in silos of high quality metadata. These silos are often underutilized due to the proprietary nature of the content described by the metadata and the perceived value of the metadata itself. Meanwhile, the Linked Open data movement is promoting a pragmatic approach to exposing, sharing and connecting pieces of machine-readable data and knowledge on the WWW using an agreed set of best practices. In this paper we identify the potential issues that arise from building personalization systems based on Linked Open data.
Policy-based management systems use declarative rules to govern their operation whilst satisfying the goals of the system. One of the fundamental issues in policy engineering remains the inability to automatically ref...
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The state-of-the-art neural network architectures make it possible to create spoken language understanding systems with high quality and fast processing time. One major challenge for real-world applications is the hig...
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This paper proposes a novel method to represent user models in a multilingual manner which caters for multilingual Web search users. Furthermore, an evaluation is presented which examines a result re-ranking algorithm...
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This paper proposes a novel method to represent user models in a multilingual manner which caters for multilingual Web search users. Furthermore, an evaluation is presented which examines a result re-ranking algorithm that is based upon that model.
A key advantage of Adaptive Hypermedia Systems (AHS) is their ability to re-sequence and reintegrate content to satisfy particular user needs. However, this can require large volumes of content, with appropriate granu...
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ISBN:
(纸本)9781450313353
A key advantage of Adaptive Hypermedia Systems (AHS) is their ability to re-sequence and reintegrate content to satisfy particular user needs. However, this can require large volumes of content, with appropriate granularities and suitable meta-data descriptions. This represents a major impediment to the mainstream adoption of Adaptive Hypermedia. Open Adaptive Hypermedia systems have addressed this challenge by leveraging open corpus content available on the World Wide Web. However, the full reuse potential of such content is yet to be leveraged. Open corpus content is today still mainly available as only one-size-fits-all document-level information objects. Automatically customizing and right-fitting open corpus content with the aim of improving its amenability to reuse would enable AHS to more effectively utilise these resources. This paper presents a novel architecture and service called Slicepedia, which processes open corpus resources for reuse within AHS. The aim of this service is to improve the reuse of open corpus content by right-fitting it to the specific content requirements of individual systems. Complementary techniques from Information Retrieval, Content Fragmentation, Information Extraction and Semantic Web are leveraged to convert the original resources into information objects called slices. The service has been applied in an authentic language elearning scenario to validate the quality of the slicing and reuse. A user trial, involving language learners, was also conducted. The evidence clearly shows that the reuse of open corpus content in AHS is improved by this approach, with minimal decrease in the quality of the original content harvested. Copyright 2012 ACM.
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differen...
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ISBN:
(纸本)9789639799455
Ubiquitous computing (ubicomp), as envisaged by Weiser [22], is heavily user-centric and largely concerned with applications specifically designed to meet end-user needs. Sensor populated ubicomp environments differentiate these applications from existing mobile and distributed systems through context awareness. For the system developer, the problems of heterogeneity and scalability are felt most keenly when designing this adaptive behaviour. A context-aware ubicomp system needs to operate reliably over the wide variety of situations that may be encountered. In this paper we present a technical architecture which has been implemented to support scalable, cost-effective, runtime experimentation using a framework of models to support informed decision making in an iterative design cycle.
Nowadays,the personalized recommendation has become a research hotspot for addressing information *** this,generating effective recommendations from sparse data remains a ***,auxiliary information has been widely used...
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Nowadays,the personalized recommendation has become a research hotspot for addressing information *** this,generating effective recommendations from sparse data remains a ***,auxiliary information has been widely used to address data sparsity,but most models using auxiliary information are linear and have limited *** to the advantages of feature extraction and no-label requirements,autoencoder-based methods have become quite ***,most existing autoencoder-based methods discard the reconstruction of auxiliary information,which poses huge challenges for better representation learning and model *** address these problems,we propose Serial-Autoencoder for Personalized Recommendation(SAPR),which aims to reduce the loss of critical information and enhance the learning of feature ***,we first combine the original rating matrix and item attribute features and feed them into the first autoencoder for generating a higher-level representation of the ***,we use a second autoencoder to enhance the reconstruction of the data representation of the prediciton rating *** output rating information is used for recommendation *** experiments on the MovieTweetings and MovieLens datasets have verified the effectiveness of SAPR compared to state-of-the-art models.
WeSeE-Match is a simple, element-based ontology matching tool. Its basic technique is invoking a web search engine request for each concept and determining element similarity based on the similarity of the search resu...
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WeSeE-Match is a simple, element-based ontology matching tool. Its basic technique is invoking a web search engine request for each concept and determining element similarity based on the similarity of the search results obtained. Multi-lingual ontologies are translated using a standard web based translation service. Furthermore, it implements a simple strategy for selecting candidate mappings interactively.
Body surface potential mapping (BSPM) provides high spatial resolution recordings of the electric potential of the heart on the body surface. BSPM can involve up to 200 electrodes, in contrast to standard 12-lead ECG....
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From a dataset, one can construct different machine learning (ML) models with different parameters and/or inductive biases. Although these models give similar prediction performances when tested on data that are curre...
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